Summer 2019 issue of the Expert Witness newsletter (volume 23, issue 1)

Contents:

In this issue of The Expert Witness, we present two articles:

From the Desk of Christopher Bruce: Farewell

Christopher Bruce publishes his final Expert Witness newsletter. In this article, Chris writes about his achievements and the founding of Economica.

Selecting the Productivity Factor

In this article, the economists discuss the real rate of growth earnings, methods of predicting the real rate of growth earnings, and how to select a forecast.

We would also like to share; A Word from the Consultants of Economica.

A Pdf. version of the Newsletter can be found here.

From the Desk of Christopher Bruce: Farewell

In three judgments issued on January 19, 1978 –Teno v. Arnold, Thornton v. School District No. 57, and Andrews v. Grand and Toy – the Supreme Court of Canada set the stage for a change in the role of experts in personal injury cases. The Court’s clear preference for statistical evidence and expert opinion in those cases induced many litigants to employ financial experts, such as economists, accountants, and actuaries, to support their positions concerning loss of earning capacity.

As I had just completed my Ph.D. in Labour Economics (the study of wages and employment), I was attracted by the challenge of contributing to the development of new theories and techniques in this area, at the intersection of law and economics.

Those of us who worked in personal injury litigation – not only judges, lawyers and economists, but also vocational psychologists, cost of care experts, and accountants – will remember the subsequent decade as a period of experimentation, as we all worked to develop new techniques and precedents. In the 1980s, because the principles on which damages were to be calculated had not yet been clearly established, it was common for those of us working in this field to appear in court frequently. By the mid-1990s, however, fewer and fewer cases made it to court as the underlying principles became commonly accepted.

As the case law began to develop, it became apparent that it would be useful to collect the developing economic techniques into one place. For this purpose I wrote The Assessment of Personal Injury Damages. Although the intention behind this book was to provide a guide to those who were not experts in economics, it also had the effect of requiring that I ensure that every aspect of my practice was up to date on the latest legal, statistical, and theoretical work. I am pleased to report that Assessment was well-received by the legal community and that in July 2019, its sixth edition (with two co-authors – Kelly Rathje and Laura Weir) will be published.

By the late 1980s, I realised that if I was to meet the demand for expert opinion, I would have to bring in assistants. Accordingly, in 1988 I formed Economica Ltd. and began to employ individuals with MAs in Economics. I was fortunate, early on, to hire two individuals who still remain with me – Derek Aldridge, in 1995, and Kelly Rathje, in 1999. In 2006 I made another excellent hire, in Laura Weir. All three proved adept at identifying the key issues in the cases presented to them, developing informed opinions about those issues, and in communicating their opinions to our clients.

When I retired from 41 years as a Professor of Economics at the University of Calgary in January 2015, I devoted more time to personal injury work. But after more than thirty years as president of Economica and twenty-five years as editor of the Expert Witness, I have decided to retire from both positions.

Effective August 1, 2019 ownership will be transferred to Derek, Kelly, and Laura who, I am confident, will continue to offer the professional service that has been our trademark.

I have enjoyed my involvement in the personal injury field. The issues have been intellectually challenging and the individuals who work in the field have all acted in a most professional and collegial manner. Thanks to all of you who have entrusted your files to Economica. I will maintain my interest in economics, which has been a lifelong passion, and will continue to follow the personal injury litigation field where I have made so many friends and acquaintances. I wish all of you the very best.

A Word from the Consultants of Economica

We would like to say thank you to Dr. Christopher Bruce. You have been a great mentor for us throughout our careers with Economica. You have provided direction, leadership, advice, and have groomed us to be one of the leading firms in the industry. Your knowledge, guidance, and support throughout the years have been a major contributor to our success, and we truly appreciate everything we have learned from you.

We are thankful for the opportunity you have given us, and we will strive to maintain the level of professionalism, integrity, and service that Economica is known for, and continue to be one of the leading firms in this industry.

Thank you and enjoy your retirement Chris.

 

Selecting the Productivity Factor

One of the most important determinants of the plaintiff’s future earnings is the rate at which those earnings will grow. There are two broad determinants of this rate. First, each individual benefits from increases that arise from gains in experience, promotions, and job changes. Second, as the economy grows, the earnings of all individuals rise with it – the source of the popular aphorism “a rising tide lifts all boats.” The purpose of this article is to summarise the most recent research concerning the latter rate, which economists call the real rate of growth of earnings, and which the courts often refer to as the productivity factor.

We divide our discussion into three parts: In the first, we define what we mean by real rate of growth of earnings. In the second, we provide two types of statistical evidence concerning that rate. Finally, we argue that the most reliable projections of that rate are obtained from agencies that specialise in making such projections. We conclude that those projections indicate that real earnings will grow at approximately 1.25 to 1.50 percent per year in the long run.

1. Definition: Real rate of growth of earnings

Assume that it has been observed that economy-wide earnings have increased at five percent per year. This “observed” rate is referred to as the nominal rate of growth of earnings. Economists divide this rate into two factors: those due to increases in the average level of prices, the rate of price inflation, and those due to increases in the purchasing power of wages, the real rate of growth of earnings.

For example, if the rate of price inflation has been two percent per year, the first two percent of a five percent nominal increase will be needed just to allow individuals to buy the same set of goods that they had been able to purchase before the price increase. The remaining approximately three percent will be available to purchase additional goods. That three percent is called the real rate of growth of earnings.

As there is a strong consensus in the financial community that the long-run rate of price inflation will be approximately two percent, the forecast of wage growth can focus on the real rate of growth. [The financial community widely believes that the rate of inflation will be two percent because (a) that is the rate that the Bank of Canada has targeted since 1996; and (b) the Bank has managed to maintain the actual rate of inflation near its target since the latter was introduced.]

 

2. Methods of predicting the real rate of growth of earnings

In the long run, if workers are to be able to purchase more goods with their earnings (that is, if real wages are to rise), they must produce more goods. Hence, it is commonly argued that long-run increases in average real earnings must approximate long-run increases in average output per worker. As the latter is often called the rate of growth of productivity, the terms “real rate of growth of earnings” and “rate of growth of productivity” are often used interchangeably in the courts. Although this conflation could be misleading in the short run, when deviations between the two are common, if we are concerned with lifetime changes in a plaintiff’s earnings, projections of productivity growth can substitute for projections of real wage growth.

In this section, we provide two types of data concerning the growth of both real earnings and productivity. In the first, projections assume that past growth rates will continue into the future. In the second, models of the growth of the economy are used to derive predictions concerning growth of wages and productivity.

2.1 Historical data

In Table 1, we compare Alberta wage and price inflation, from 2001/2002 through 2017/2018. It is seen from this table that over the 2012-2018 time frame, which coincided with a considerable economic downturn in the Alberta economy (2014-2016), price inflation was higher than wage inflation. However, a longer-term perspective finds that wage inflation averaged approximately 0.78 percent higher than price inflation over the ten-year period 2008-2018; and approximately 1.0 percent higher than price inflation over the seventeen-year period 2001-2018.

 

If it is assumed that the experience of the last two decades or so is indicative of what will happen in the next few decades, then the data in Table 1 suggest that the real rate of growth of wages will be approximately 1.0 percent per year.

The data reported in Table 2, obtained from Statistics Canada, suggest that Canadian labour productivity has increased at an average annual rate of approximately 1.23 percent over the past 37 years (from 1982 through 2018), and 0.88 percent over the last five years (2014-2018).

Again, a forecast of 1.0 to 1.25 percent seems to be supported by the data.

 

2.2 Forecasting Agencies

We have identified five reputable, independent agencies that provide public projections of either real wages or labour productivity. We summarise their long-run projections in Table 3, below.

Table 3 suggests that reputable forecasting agencies are predicting that real wages will grow at approximately 1.25 to 1.50 percent per year over the next two or three decades.

3. Selecting a forecast

Our experience is that most financial experts have relied on historical figures, such as those we reported in Tables 1 and 2, to project the rate of growth of real wages/productivity. For two reasons, we caution against acceptance of this approach.

First, there is no theoretical basis for assuming that what has happened in the past will continue into the future. For example, advances in computer technology are introducing changes to the economy that may differ in significant ways from those that have occurred in the past; the wave of “baby boomers” is about to retire from the labour force; and interest rates have fallen to historical lows.

Second, with very few exceptions, the financial experts who testify in personal injury cases have not devoted significant amounts of time to the analysis of long-run changes in labour productivity. Given a choice between the testimony of individuals whose primary expertise is in the preparation of personal injury reports and that of individuals who devote their professional lives to the forecasting of long-term trends in the economy, it seems to us clear that it is the latter that should be preferred.

Accordingly, we recommend that the courts rely on the forecasts of the five agencies identified in Table 3, and on others with similar expertise, when determining the “productivity factor” to be employed in personal injury and fatal accident actions.

 

 

 

The Impact of a Mid-Career Change on Earnings

by Derek Aldridge and Christopher J. Bruce 

Vocational psychologists often recommend that injured plaintiffs retrain for a new occupation. An important question that arises in this situation is whether plaintiffs will start that occupation at an “entry-level” income (say the income of a 25 year-old) or at the income of an individual of the plaintiff’s calendar age. The importance of this issue can be seen in Table 1, which reports that, in two occupations that are commonly recommended as retraining possibilities – partsman and drafting technologist/technician – incomes for middle-aged workers can be 50 to 100 percent higher than those for 20-24 year-olds.

If it has been recommended that, say, a 40 year-old male retrain to enter one of these occupations, the economic expert is faced with determining which of the income levels from Table 1 best represents the income at which the plaintiff will begin his new career. If experience in the occupation, or movement along a career ladder, are important determinants of income, then we would expect that the plaintiff would begin at one of the lower incomes suggested by the census data. Perhaps with his greater maturity the 40 year-old would not start at the income level of a 20-25 year-old; but with no experience in this occupation, it seems unlikely that he would start at the income of a 40 year-old.

Fortunately, a number of empirical studies that provide information concerning this issue have been published in economics journals recently. We summarise the results of these studies here, to provide assistance both to vocational experts, who may not be familiar with the economics literature, and to economists, who may have been asked to calculate a loss in a case in which no vocational expert has provided a relevant opinion.

In the earliest of these studies, Goldsmith and Veum (2002) used a detailed survey that followed 1400 young workers from 1979 to 1996 to compare the effects of additional years of experience on wages when individuals: remained in the same occupation and industry, remained in the same occupation but moved between industries, remained in the same industry but changed occupations, and changed both occupations and industries. What they found was that the value that was placed on previous experience was approximately the same for all individuals except those that had changed both occupation and industry. In their words:

…experience acquired while a real estate agent is valued similarly as tenure at other occupations, such as accounting, within the real estate industry. In addition, the experience as a real estate agent is valued similarly to tenure at other industries, such as the pharmaceutical industry, if continuing in the occupation of sales. If the real estate agent becomes an accountant in the pharmaceutical industry, however, the experience as a real estate agent is of less value than that within accounting or the pharmaceutical industry.

(p. 442)

 

Referring to the examples in Table 1, Goldsmith and Veum’s findings suggest that the 40 year-old who retrains as a partsman may be able to earn an income comparable to that of a 40 year-old partsman with 15 years experience, if the retrained individual remains within his previous industry. For example, if an individual who had previously worked on oil rigs becomes a partsman in a shop that provides equipment to oil rigs, he might be expected to obtain a starting salary much higher than he would have obtained if he had become a partsman in an automobile dealership.

Subsequently, however, a number of studies cast doubt on Goldsmith and Veum’s findings. Both Zangelidis (2008), and Kambourov and Manovskii (2009) found evidence to suggest that occupation is much more important than industry. Zangelidis concluded, for example, that “[o]ccupational experience is expected to make an important contribution in determining wages…[whereas the] evidence on industry specificity… is not very supportive.” (p.439) And Kambourov and Manovskii (2009) concluded that “[job] tenure in an industry has a very small impact on wages once the effect of occupational experience is accounted for.”(p. 64)

The findings from these two studies suggest that if the plaintiff has not yet started a new post-accident job (and, hence, the wage at that job is not known), it may be appropriate to assume that she will begin that new job at an “entry-level” wage if she has re-trained for a new occupation (regardless of whether she remains in the same industry she was employed in before the accident); and will begin at a wage commensurate with others of her calendar age only if she has not changed occupations.

Hence, contrary to Goldsmith and Veum’s findings, these studies suggest that the 45-year old welder who retrains as a partsman will begin her new career at the earnings of a partsman at the start of her career.

Finally, two recent studies have asked whether the impact of retraining is a function of the worker’s initial occupation. For example: will craftsmen suffer a greater income loss if they are forced to change occupations than will salespeople? Sullivan (2010), using detailed information from the National Longitudinal Survey of Youth (NLSY), found that changes of occupation and industry each had significant negative effects on the earnings of professional workers and clerical workers; that changes in occupation, but not industry, had negative effects on craftsmen and service workers; and that changes in industry, but not occupation, had negative effects on managers, salespeople, and laborers.

All of these studies imply that the reduction in earnings is likely to be greater, the greater is the difference between the tasks performed in the worker’s previous job and those in his or her new job – especially if the individual had initially been in a high-skill occupation, such as a professional or craftsman. As a first approximation, therefore, the empirical literature suggests using the earnings of individuals in entry-level jobs when estimating the starting income of an individual who has been forced to retrain, regardless of that individual’s calendar age. Of course, this recommendation will have to be modified when information specific to the plaintiff is found to be inconsistent with the statistical data presented here.

References

Gathmann, Christina, and Uta Schonberg.

“How General is Human Capital? A Task-Based Approach.”  Journal of Labor Economics 28 (1) (2010) : 1-49.

Goldsmith, Arthur, and Jonathan Veum. “Wages and the Composition of Experience.” Southern Economic Journal 69(2), (2002): 429-443.

Kambourov, Gueorgui, and Iourii Manovskii. “Occupational Specificity of Human Capital.”  International Economic Review 50 (1) (2009): 63-115.

Sullivan, Paul.  “Empirical Evidence on Occupation and Industry Specific Human Capital.” Labor Economics 17 (2010): 567-580.

Zangelidis, Alexandros.  “Occupational and Industry Specificity of Human Capital in the British Labour Market.” Scottish Journal of Political Economy 55(4) (2008): 420-443

A version of this article was published in the Journal of Legal Economics, 24(1-2), September, 37-41.

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Christopher Bruce is the President of Economica; he has a PhD in economics from  the University of Cambridge

Derek Aldridge has been a consultant with Economica since 1995 and has a master of arts degree in economics from the University of Victoria.

 

 

The Cost of Household Services, Alberta, 2018: A Survey

by Christopher J. Bruce and Jody Prevost

The cost of hiring individuals to perform household services such as housecleaning, snow removal, and handyman repairs can amount to a significant percentage of the damages in a personal injury or fatal accident claim. Yet, despite the importance of these costs, reliable estimates of the components of a household services claim are very difficult to obtain. In order to assist the court in this respect, Economica has conducted a number of surveys of household services costs since 1997.

In those surveys, for example, we found that the average hourly cost of housecleaners in Calgary rose from approximately $13.50 in 1997, to $30.00 in 2014; and for handymen the rates rose from $24.00 in 1997 to $35.00 in 2014.

As four years have passed since our last survey, and as our experience suggests that rates tend to increase appreciably over time, we undertook a new survey of providers in 2018. In each case, we conducted exhaustive searches of relevant quotes using Kijiji and Google (the two most common sources of advertisements). This article summarises our findings.

Housecleaning

Using the internet, we identified sixteen professional agencies (for example, Mango Maids) in Calgary and fourteen in Edmonton that provide house cleaning; and we identified six ads from individuals (on Kijiji) in Calgary and seven in Edmonton.

In Calgary, the average rate among professional agencies was $41.38 per hour, with a range from $25.00 to $56.80. The comparable average for Edmonton was $39.28, ranging from $25.00 to $65.66. Among those individuals who advertised on sites such as Kijiji, the average hourly rate in Calgary was $26.67 and in Edmonton was $30.57.

In the smaller cities, most of our data came from Kijiji. In those cities, the average hourly rates (with numbers of ads in brackets) were: Lethbridge (6), $29.16; Red Deer (7), $29.71; Medicine Hat (5), $29.00; and Grande Prairie (7), $29.30.

We conclude that rates for individual suppliers average approximately $29.00 per hour across all Alberta cities; and that comparable rates for professional agencies average approximately $40.00 per hour (where such services are available).

These data raise two important question: first, if individuals listed on Kijiji charge approximately $29 per hour, why do consumers hire professional agencies at $11 per hour more than that? Second, why do the rates for individual suppliers exceed the hourly wages paid to individuals who work for professional agencies?

Professional agencies versus individuals

We suspect that the answer to the first of these questions derives from three factors.

First, agencies may be able to offer a higher quality of service than can private individuals. For example, they might provide training to their employees, use screening interviews to select the most skilled workers, or offer to replace workers who proved to be unacceptable to the client.

Second, it is possible that agencies might be able to complete their tasks more quickly than would private contractors, thereby lowering the effective hourly rate of the former.

Finally, commercial firms may be better able than individual cleaners to develop reputations for reliable service. If a cleaner is sick or otherwise unable to work, a firm can often replace that individual with another employee; whereas if self-employed individuals are unable to meet their commitments, their jobs go undone. Customers may be willing to pay a premium for the more reliable service.

Regardless of the answer to this question, however, the fact is that it would be very difficult to hire a reliable housecleaner in Calgary or Edmonton for less than $30 per hour – and that cost would rise to more than $40 per hour if the client wished to hire a bonded cleaning service.

Self-employed suppliers versus employees

A second puzzle raised by our findings is that, according to the Alberta Wage and Salary Survey, “light duty cleaners” earned an average of $16.08 per hour in 2017, with a range of $12.75—$20.13, more than $10.00 per hour less than the rates charged by individuals advertising on Kijiji. What is the source of this differential? One possibility is that the individuals identified by the Survey are working as employees for large cleaning companies and, therefore, have security of employment; whereas those advertising on Kijiji are self-employed, with the attendant uncertainties and with the requirement, in many cases, that they provide their own cleaning supplies. Another possibility is that it is the more productive, reliable individuals who choose self-employment. Regardless of the answer, our evidence suggests that individual plaintiffs will not be able to hire housecleaners at the wage found in the Alberta Wage and Salary Survey. It is the rates found on Kijiji and on the websites of professional agencies that best reflect the cost of hiring a housecleaner for an hour.

A caveat

It should be noted, however, that even if it costs, say, $30 to hire a housecleaner for one hour, it does not follow that it will cost $30 to replace one hour of a plaintiff’s time. The reason for this is that professional cleaners may be able to complete more work in an hour than could non-professionals (i.e. than plaintiffs). The best information we have available, for example, suggests that this differential is approximately 25 percent; that is, to replace one of the plaintiff’s hours will require only 0.75 hours of a professional’s time. In this case, the cost of replacing an hour will be $22.50 (= 0.75 x $30). [Note: this argument with respect to the greater efficiency of professional providers applies to all of the other services identified in this report, except child care.]

Handyman

With respect to handyman services, we obtained quotes from Yelp, Google and Kijiji. In each case, we requested a quote to “replace several fence boards, clean and repair the gutters, and paint the step rails and trim.”

In Calgary, where we received responses from four individuals and five professional companies, the average hourly rate was $45.28. Three companies had minimum charges of two hours.

In Edmonton, where we received responses from six professional companies and four individuals, the average hourly rate was $47.50. Only two companies specified a minimum number of hours billed.

In both cities, the preponderance of quotes fell between $40.00 and $50.00.

 Lawn care and snow removal

Lawn care

In our search for lawn care rates in Calgary and Edmonton we asked for quotes for a 2400 square foot lot with an 1800 square foot house, front and back. Of sixteen lawn care companies surveyed in Calgary, fifteen ads were from professional companies and one from an individual. In Edmonton, of fourteen lawn care companies surveyed, eleven were from professional services and three from individuals.

In Calgary the average cost was $36.73 per visit for lawn care and $200 per month for lawn cutting. In Edmonton these rates were $46.63 and $157.80, respectively.

Snow removal

With respect to snow removal, we surveyed businesses in Calgary and Edmonton for quotes to remove snow from a home with a two-car driveway, stairs, entry, and city sidewalk.

Twelve companies in Calgary responded, with an average per visit rate of $36.33 and a monthly “unlimited” rate of $176.05. In Edmonton, eleven companies responded, with an average per visit rate of $41.14 and a monthly “on demand program” of $182.05.

Child care

We identified six methods of providing (commercial) child care: day care, day home, live-in nanny, live-out nanny, before- and after-school care, and (hourly) babysitting. We obtained all of our information from Google and kijiji.

Day homes

We identified six day homes in Calgary and nine in Edmonton. In Calgary, the rates averaged $57.50 per day, or $845 per month; whereas the comparable rates in Edmonton were $45 per day, or $759 per month.

Day care

Our findings with respect to the monthly cost of day care are reported in Table 1. There, we provide rates by four age groups: infants (0 to 18 months), pre-toddlers (18-24 months), toddlers (24-36 months) and pre-school (four and five years).

Before- and after-school care

The average monthly rate for before- and after-school care, for children in grades one to six, was found to be $532 per month in Calgary (nine agencies) and $603 in Edmonton (six agencies).

Nannies

The average monthly rate for the three live-in nannies we identified in Calgary was $2,466, and for three live-out nannies it was $3,200. We also obtained hourly rates, averaging $17.50 (approximately $3,500 per month) for fifteen live-out nannies in Calgary.

In Edmonton, the monthly rate for the six live-in nannies we identified was $2,300; and for the five live-out nannies in our survey it was $2,600. We were also able to obtain hourly wages for fifteen live-in and fifteen live-out nannies in Edmonton. The average rates for those samples were $16.00 and $16.47, respectively (approximately $3,200 and $3,300 per month, respectively).

Babysitting

In each of Calgary and Edmonton, we obtained twenty quotes for babysitting services. In each city, eleven of the quotes came from Kijiji and nine came from a website called nannyservices.ca. The average hourly quote from Kijiji was $14.55 in Calgary and $13.23 in Edmonton. The average quote from nannyservices was $15.77 in Calgary and $16.33 in Edmonton. In both cities and for both sources, the most common rate was $15 per hour. (The slightly higher rate from nannyservices appears to have arisen because many of the individuals advertising on that site offered ancillary services such as dog walking and light housekeeping.)

 Home care and meal preparation

Generalized home care services range in price by the level of assistance required. We obtained information from five professional agencies in Calgary and Edmonton – Home Care Assistance Calgary, Miraculum Home Care, Wild Rose Caregivers, Classic Life Care, and Paramed Home Health – concerning the costs of caring for “a relative that had been injured in an accident and was recuperating at home”.

Home Care Assistance Calgary provided quotes for both daily and monthly care for: meal preparation, light housekeeping, grocery shopping, grooming and dressing, bathing assistance and in some cases medical assistance. Their rates were $128 per day for part-time care and $256 per day for full-time care. Weekly rates varied from $384 to $1,792; and monthly rates from $1,164 to $7,765, depending on the number of hours required.

We found that hourly rates for the five agencies varied according to the qualifications of the workers who were required. Health care aides cost from $27 to $32 per hour; licensed practical nurses approximately $37 per hour; and registered nurses approximately $60 per hour.

We also obtained rates from individuals advertising on the website nannyservices.ca. Searching under companion and health care aide, we found that health care aides and personal service workers charge an average hourly rate of $21 in Calgary and $18 in Edmonton. In both cities, full time services cost $2,800 per month.

Summary

In this article, we have reported the results of a survey of household services providers in Alberta. Two outcomes are very clear. First, it is inappropriate to use a single, hourly rate to evaluate all such services. Whereas child care services cost less than $10 per hour, ($45 to $57 per day), housecleaning services cost almost $30 per hour, and lawn care and snow removal cost over $35 per visit.

Second, the convention of using $12 to $16 per hour for household services is unsupportable. With the exception of child care, all of the services that were identified in our survey cost significantly more than that, even after allowing for the greater efficiency of professionals.

Our findings also strongly support the view that hourly rates for housekeeping services should not be obtained by simply averaging the figures that have been adopted in previous cases. We are pleased to note that Madame Justice D. C. Read agreed with our conclusion on the latter point in her decision in Palmquist v. Ziegler, 2010 ABQB 337, at para [271] (emphasis added):

By using an average of numbers accepted in other cases in order to establish a number used to make an assumption in this case, all of the possible errors, either of the trial judge or of the economists who gave evidence in those cases, are incorporated into the number to be used in this case. Courts rely upon economists to determine what assumptions are reasonable to make and their decisions are only as reasonable as are the assumptions used. I have no means of evaluating the expert evidence that was before those other courts to determine whether or not I accept the assumptions made. It is circular to accept that an average of numbers accepted by another courts has any validity in respect to the issue of what economic assumptions are reasonable for me to make in this case.

Proposal

Statistics Canada provides data concerning the amounts of time spent on six types of “household work and related activities.” These are: cooking/washing up, house cleaning and laundry, maintenance and repair, other household work, shopping for goods and services, and primary child care. For the purposes of calculating the costs of household services, in our reports we will combine “cooking/washing up” with “shopping” and evaluate that category at the approximate average rate for home care and meal preparation, $32.00 per hour (up from $25.00 per hour in our 2014 survey).

We will combine “maintenance and repair” with “other household work” (a large portion of which consists of “gardening and ground work”) and evaluate the resulting services at the landscaping, snow removal, and handyman services rate of approximately $38.00 per hour (up from $35.00 in 2010).

We will evaluate “house cleaning and laundry” at the rate for housecleaning services. For the purposes of our reports, we propose to use the conservative rate of $29.00 per hour in all regions of Alberta (down from $30 per hour in Calgary and Edmonton in 2014, but up from $25.00 per hour elsewhere).

For each of the preceding services, however, we will assume that professionals will be 25 percent more efficient than the plaintiff would have been. Hence, our assumption is that the cost of those services is 25 percent less than the rate that has been quoted per hour.

We will assume that it in Calgary it costs $1,200 per month to care for each infant (the approximate mid-point of day care and home care costs), or $900 in Edmonton; $1,000 to care for each toddler/pre-school child in Calgary, ($800 in Edmonton); and $525 per month to provide before- and after-school care for each school-aged child in Calgary ($600 in Edmonton).

Finally, for the purposes of quantifying child care costs on an hourly basis, we propose to employ $15.00 per hour, (the most common rate quoted for babysitting in Calgary and Edmonton).

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Christopher Bruce is the President of Economica; he has a PhD in economics from  the University of Cambridge

Jody Prevost is the administrative assistant at Economica

 

The Cost of Managing the Expenditures of a Plaintiff with Reduced Mental Capacity

by Christopher J. Bruce

When referring to plaintiffs with normal mental capacity, the term “management fee” usually refers to expenses that plaintiffs incur for advice concerning investment decisions. Decisions concerning how their awards are to be spent – on medical care, accommodation, transportation, etc. – can generally be left to the plaintiffs themselves.

Plaintiffs who have suffered an impairment in their mental capacity – usually children injured at birth or adults injured in catastrophic accidents – however, may require assistance with many, if not most, of the decisions concerning expenditure of their awards. In this article, I propose to include the cost of this assistance in the term “management fee” and to investigate what the determinants of this fee will be in the case of plaintiffs with reduced mental capacity.

In the first section of this article, I enumerate the various types of assistance that will be required by these plaintiffs. I call this the “hierarchy of needs,” as the responsibility for this assistance involves a pyramid, or hierarchy, of decision-makers. In the second section, I investigate the costs of this assistance.

A Hierarchy of Needs

The management of the plaintiff’s award requires four types of agents:

Financial manager: Once the court award has been paid to the plaintiff, that amount will have to be invested. This will require either that a trust company invest the award in a portfolio of conservative financial assets, or that a structured settlement be purchased from an insurance company. In either case, a fee may be charged for the management of the plaintiff’s finances. (These are the fees that were discussed in the first article in this edition of the Expert Witness, “The Cost of Managing the Plaintiff’s Investments.”)

Guardian – The role of the guardian is to determine how the invested funds are to be spent: to ensure that the plaintiff is provided food, clothing, shelter, transportation, health care, and emotional care. Generally, it is not intended that the guardian will provide these services directly but will, instead, be responsible for hiring an agent called a case manager (see below), and for providing that individual with directions concerning the types and levels of services that are required. The guardian, for example, might decide that the plaintiff should be moved from his or her own home to a nursing home, but leave the decision about the selection of a specific nursing home to the case manager.

Often, the guardianship function will be performed by a committee which might, for example, include family members, legal representatives, social workers, and a life care planner/cost of care expert. The latter are experts who assist the guardian with the development and implementation of a plan for the care of the plaintiff.

Rehabilitation case manager – The guardian will often consider it necessary to contract with an agent to implement the plan that was developed in coordination with the life care planner. This individual is usually called a rehabilitation case manager, or simply case manager. He or she takes direction from the guardian and reports to the trustee (see below).

These individuals are responsible for:

  • the physical safety and emotional and social well-being of the individual in the community – for example, contracting with rehabilitation specialists, physical therapists, educational consultants, and speech and language consultants;
  • contracting with care personnel, such as rehabilitation assistants, home support workers, and nursing staff as warranted by the nature and extent of the injuries sustained and the impact of the impairments on functional ability; and
  • purchasing and maintaining goods and services, including medically-required equipment, such as wheelchairs and modifications to automobiles.
  • They are also responsible for monitoring all of the service-providers that have been hired, to ensure that their functions are being carried out as specified, and for replacing any employees who have resigned or been laid-off.

[As the case manager’s role is primarily to arrange for the purchase of goods and services, he or she may hire a subsidiary set of agents who make the actual purchases. Hence, there may be an additional layer of agents in the hierarchy: purchasing agents.]

Trustee: The trustee performs a “gatekeeping” role, ensuring that the bills incurred on behalf of the plaintiff are paid, that relevant income taxes are remitted, and that expenditures are not mismanaged (or misappropriated). Although one person (for example, a close relative) could act as both guardian and trustee, it is generally recommended that these two functions be separated, in order to provide independent checks on spending patterns.

Management fees

Payment may have to be made to each of the four categories of agents described above. I consider each of them separately here.

Financial Manager: As brain injured plaintiffs and children cannot make their own financial decisions, a third party will have to be employed to invest plaintiffs’ awards. Two options are available: a trust company may act as an investment manager, or an insurance company may provide a structured settlement.

If a trust company has been employed, it will provide its services for a fee that normally varies from about 1.0 percent to 2.0 percent of the value of the investment. Thus, for example, if the trust company is able to obtain a rate of return of 4.0 percent on the investment, from which it deducts a fee of 1.0 percent, the net rate of return will be 3.0 percent. Technically, the financial manager’s fee could be included as one of the costs of caring for the plaintiff. However, the data we recommend the courts use when calculating discount rates – the return on balanced portfolio funds (discussed in the first article in this edition of the Expert Witness,) – and the discount rates that are mandated by many provinces, are already net of investment companies’ management fees. Thus, in practice, no additional allowance will be required.

Similarly, insurance companies’ prices for structured settlements incorporate their costs of management. Hence, if the plaintiff’s award has been paid as a structured settlement, it may not be necessary to provide a separate allowance for the insurer’s management fee.

Note, however, that although it is generally not necessary to include a fee for the financial manager, it may be necessary to include a fee for the trustee (see below).]

Guardian/life care planner: There are three potential sources of guardians: the relatives of the plaintiff, a public agency (often referred to as the Public Trustee’s Office), or a private agent.

Relatives: When brain damage arises from negligence at birth, the parents of the injured child will often act as guardians; and when injury occurs later in life, guardians may be selected from spouses, parents, siblings, adult children, or other relatives. To the extent that these individuals are willing to work for free, it might be argued that no claim for their services can be made against the defendant. However, two counterarguments can be made.

First, for the same reason that relatives are often able to claim for the costs of providing household services or nursing care to the plaintiff, they may also be able to claim compensation for the time and effort required to act as guardians. Second, some allowance must be made for the possibility that the relative guardian will die before the plaintiff and, therefore, that a third party will be needed.

When either of these arguments is accepted, the cost of guardianship can be calculated as the cost that would have been charged by a public or private guardian. (For these, see below.)

Public Agency: Depending on the jurisdiction, Public Guardians may not charge fees for their services, or may charge a below-market fee. It should be noted, however, that all of the experts we have consulted have recommended that, if plaintiffs have large awards, they should not rely on the office of the Public Guardian, as the latter generally deals with relatively small sums.

Private Guardian or life care planner: If it is felt that the Public Guardian is not appropriate, it may be necessary to hire a private guardian. A number of knowledgeable individuals have suggested to me that a life care planner might fill this role. As the function of this individual is to develop a plan for the care of the plaintiff and to ensure that that plan is implemented as intended, it may require only a limited number of hours – perhaps five to ten per month – at approximately $200 per hour. Thus, an annual allowance of approximately $20,000 would not be unreasonable.

A guardian committee may also include a lawyer. If we assume five hours per month at $300 per hour, the annual fee would be $18,000.

Rehabilitation case manager: The costs of hiring rehabilitation case managers vary significantly depending on the severity of the injury to the plaintiff. A U.S.-based life care consulting firm, Caragonne and Associates, has developed an “assessment protocol” for calculating the number of hours of case management that will be required for seriously injured clients. The protocol identifies five dimensions of care, and scores each dimension on the degree of involvement required from the case manager: from low, through moderate, to high. The five dimensions are:

  1. Level of client’s independence: This dimension measures the extent to which the client needs advice and encouragement. It ranges from high independence, in which the client requires only “periodic encouragement” from the case manager, to low independence/high need, in which frequent intervention is required to assist and orient the client.
  2. Number of providers of needed services: This dimension ranges from low intervention, in which the client has obtained the resources needed, to high intervention, in which the case manager will have to contact multiple agencies and providers to arrange for the goods and services needed by the client.
  3. Frequency of appraisal: The more often can the client’s status be expected to change, the greater will be the need for reappraisals by the case manager.
  4. Coordination of providers: Once a life care plan has been put into place, the case manager will have to coordinate the implementation of that plan. The greater is the number of providers that have to be coordinated, and the more frequent is the number of interventions, the greater will be the number of hours worked by the case manager.
  5. Travel: The further the case manager has to travel in order to meet with the client and his or her providers, the greater will be the number of hours required.

Caragonne and Associates estimate that if the client’s needs are rated as “high” on four or more of these dimensions, case management will require eight to twelve hours per month. If the client’s needs are rated as “moderate” on most of the dimensions, case management will require five to seven hours per month. Even a “low” rating on most dimensions will require one to four hours per month.

As many brain-injured clients and child plaintiffs will require a high level of services on most of the Caragonne dimensions, it can be expected that case management will require eight to twelve hours per month. Assuming ten hours per month, at $100 per hour, a case manager would cost approximately $12,000 per year.

Trustee: When trust companies act both as financial managers of the plaintiff’s award and as trustees of the plaintiff’s expenditures, they may offer a rate that is lower than the sum of the financial management fee and the trustee’s fee. As practices will vary among companies, it is important that counsel receive clear quotations for the sum of the two services.

If the Public Trustee acts as trustee, it may charge for its services. In Alberta, for example, that fee equals three-eighths of a percent of the total size of the investment – that is, $3,750 per year for each $1million.

When a structured settlement has been purchased from an insurance company, the insurer will not act as trustee. Hence, an additional fee for that service will often have to be calculated. RBC, for example, will act as trustee of a structured settlement for a charge of 5% of the annual annuity payment, subject to a minimum annual fee of $7,500. Tax preparation services would be in addition, at hourly rates, likely under $1,000/yr.

Summary

It has been our observation at Economica that when the courts use the term “management fee” they are usually referring to the fee for a financial manager, to supervise the investment of the plaintiff’s award. What I have argued in this article is that, when the plaintiff is a child or has been brain injured, there are at least three other classes of agents who will be responsible for managing the expenditure of the award, and who may also have to be compensated. In those cases, therefore, the “management fee” may extend well beyond the value normally considered by the courts.

Most importantly, allowance may have to be made for compensation of the guardian, the life care planner, and the case manager; and, when the award has been invested in a structured settlement, allowance may have to be made for trustee fees. As these fees could well exceed $50,000 per year, they could add over $1million to the size of the award to a young person. Hence, it is crucial that these sources of cost be considered seriously.

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Christopher Bruce  is the President of Economica; he has a PhD in economics from  the University of Cambridge

The Cost of Managing the Plaintiff’s Investments

by Christopher J. Bruce

As most individuals are unaccustomed to managing large sums of money, it may be appropriate for plaintiffs to employ advisors to assist them with the investment of their awards. In these cases, it has often been argued that the cost of hiring such advisors should be added to the value of the award. This cost is referred to as a management fee or financial management fee.

The fees that are charged by financial advisors are almost universally quoted as a percentage of the total value of the amount that has been invested. For example, the fee charged by a bank or trust company for managing an investment of $1 million might be 2.0 percent of that investment, or $20,000 per year. This percentage normally declines as the size of the investment increases. For example, on an investment of $3 million, it might be 2.0 percent on the first $2 million and then 1.5 percent on the next $1 million.

The effect of the management fee is to reduce the net value of the rate of interest, or discount rate, obtainable by the plaintiff. For example, assume that a trust company is able to obtain a rate of return of 5.0 percent (after accounting for inflation) on an investment of $1 million, and that the management fee is 2.0 percent. The income earned in each year will be 5.0 percent of $1 million, or $50,000. But from that will be deducted a 2.0 percent management fee, or $20,000. Thus, the net return on the investment will be $30,000 ($50,000 – $20,000), which represents a 3.0 percent net rate of return on the investment.

When calculating the value of the plaintiff’s award, the financial management fee could be taken into account either by adding the dollar cost of the financial advisor to each year’s losses, or by discounting the future losses by the net rate of return on investments. The former approach requires the calculation of the management fee for each year in the future, whereas the latter requires only that the rate of return on investments be replaced by the net rate of return (3.0 percent is used in the example above instead of 5.0 percent). Thus, as both approaches produce the same estimate of the award, economists generally prefer to use the simpler approach: the net rate of return.

Assume that it has been agreed that plaintiffs should place their awards in a particular type of investment portfolio, and that the projected rate of return on that portfolio is, say, 4.5 percent. If the financial management fee is 1.75 percent, the appropriate discount rate would be 4.5 percent minus 1.75 percent, or 2.75 percent.

This is the basis of the argument that is often made in court: that a (financial) management fee must be deducted from the discount rate to obtain a “true” net discount rate.

Although this argument sounds reasonable, it is not – for the simple reason that in most cases in which financial experts testify concerning the value of “the discount rate”, it is a net discount rate to which they are referring. That is, they are referring to a rate from which the management fee has already been deducted. Thus, it is not necessary to deduct a further management fee from the recommended discount rate – the latter already includes a management fee.

What I wish to show in the following two sections is that whether it is necessary to deduct the management fee will depend upon the way the discount rate has been determined.

In the first of these sections, I will consider four situations in which the court has used testimony from expert witnesses to select the discount rate. In the second section, I will consider those cases in which the discount rate has been mandated by government regulation.

Court Selected Discount Rate

The courts have been clear that plaintiffs are expected to invest their awards in financial assets that do not expose them to unreasonable risk. For example, in its seminal decision in Lewis v. Todd (1980 CarswellOnt 617), the Supreme Court of Canada approved of the expert’s use of “high grade investments [of] long duration.” [para. 17] Financial experts have generally held that this implies that the plaintiff’s award should be invested in a balanced portfolio of conservative financial assets – for example in a mix of government bonds, highgrade corporate bonds, and “blue chip” stocks.

In this section, I will consider four approaches that plaintiffs could take to the investment of their awards; and investigate whether it would be appropriate to deduct a management fee in each of them. These approaches assume that the plaintiff will either:

  • Purchase mutual funds that spread their investments across balanced portfolios of financial assets.
  • Employ a financial advisor to assist them with decisions concerning their investments.
  • Use their own expertise to invest in financial markets.
  • Purchase a structured settlement.

Under the first three of these approaches, I assume that the plaintiff, and his or her advisors, will attempt to balance two goals: maximize the rate of return on investments, and minimize the risks associated with the purchase of financial assets. This balance is achieved by investing in a balanced portfolio of assets spread across a range of potential instruments. (Under the fourth, structured settlement approach, the plaintiff leaves the choice of investments to the provider of the structured settlement.)

Balanced portfolio funds: One method of achieving a balanced portfolio is to purchase a type of mutual fund called a balanced portfolio fund. Each of these funds – which are offered by all of Canada’s banks, by many investment houses, and by insurance companies – invests in a balanced blend of asset classes. These funds offer numerous advantages to the plaintiff. They reduce risk by spreading their investments across different types of assets, in different industries, and different countries. They offer clearly identified choices concerning the degree of risk that the plaintiff is willing to accept, often ranging from “very conservative“ to “aggressive growth-oriented”, and the selection of the assets to be incorporated in each fund is made by experts who are supported by teams of researchers.

Furthermore, balanced portfolio funds offer the attractive feature that the rates of return that they have earned are publicly available. Thus, not only can the plaintiff-investor determine easily what any fund’s performance has been; but the rates of return on those funds can be used by the courts as objective measures of the returns that are available to plaintiffs when they invest in conservative, balanced portfolios.

The interest rates that are reported publicly, on balanced portfolio funds, are net of management fees. For example, if a fund earns 4.5 percent on its investments, and the fund’s operators charge a fee of 2.0 percent, the published rate will be 2.5 percent. It is information concerning these published rates – that is, rates that are net of the fund operators’ rates – that Economica uses when discounting plaintiffs’ future losses. [See Selecting the Discount Rate, Expert Witness, Vol. 21, Spring 2017.] As these rates are net of the operators’ fees, there is no need to add a “management fee.”

Financial advisor: Instead of purchasing a mutual fund “off the shelf,” the plaintiff could employ a financial advisor to purchase a balanced portfolio of investments, specific to the preferences of the plaintiff. Generally, these advisors charge a fee that equals approximately 1.0 to 2.0 percent of the value of the assets that they are managing. Is there an argument for adding the cost of this advice to the plaintiff’s award, as a management fee? I will argue that the answer is “no.”

To see why, consider the following example: assume that a financial advisor who charges a management fee of 2.0 percent is able to obtain a rate of return of 5.0 percent. The net rate of return received by the advisor’s clients will be 3.0 percent. [For example, $100,000 invested at 5.0 percent will generate a return of $5,000 per year and, with a management fee of 2.0 percent, will cost $2,000 per year. Thus, there is a net gain of $3,000, which is 3.0 percent of the invested amount.]

In this case, the appropriate discount rate will be the net rate of interest obtained by the advisor, or 3.0 percent. For example, to determine how much would have to be invested today to replace a $103,000 loss a year from now, one would divide $103,000 by 1.03 (= 1 + the interest rate), to get $100,000. When future losses are discounted by this rate, the costs of the advisor’s services have been accounted for in the calculation – the $3,000 gain after one year equals the return on the investment, $5,000, minus the advisor’s fee, $2,000.

Thus, if the discount rate that is used by the court to calculate the value of the plaintiff’s award equals the net investment return obtainable by the financial advisor, no additional allowance needs to be made for a management fee.

Although the rates of return obtainable by financial advisors are not publicly available, a reliable objective measure of that rate is the rate of return on balanced portfolio funds. As
independent financial advisors generally rely on the same research that is available to the operators of mutual funds (they usually work for the same financial institutions), they can be expected invest in portfolios of financial assets that are similar to those that are contained in balanced portfolio funds. They can, therefore, be expected to generate similar rates of return net of management fees.

If that is true, then the estimate of the return available to independent advisors includes an allowance for the management fee, and no additional management fee need be awarded.

Self investment: In those cases in which plaintiffs are expected to use their own skills to invest their awards, there will be no (or only minor) management fees and, hence, no call for such fees.

Structured settlement: The cost of any structured settlement includes the cost to the issuer of managing that settlement. Hence, again, there would be no need for an additional management fee.

Summary: I can find no situation in which it would be necessary to award a management fee to a plaintiff who is mentally competent.

Mandated Discount Rate

An argument might be made for the award of management fees in those cases in which the discount rate mandated by the government exceeds the rate predicted by the experts before the court.

Assume, for example, that the mandated rate was 3.0 percent and that the best evidence before the court was that the net rate of return available on a balanced portfolio of funds was 2.0 percent. It could be argued that the difference between the two rates had arisen because the mandated rate reflected the rate of return available before deduction of management fees. In that case, it might be appropriate to award a management fee of 1.0 percent, to bring the net discount rate to 2.0 percent.

It must be pointed out, however, that the rates currently mandated in British Columbia, Ontario, and Saskatchewan are significantly lower than the net rates available on balanced portfolio funds. Hence, although there is a case for awarding management fees in some cases, the conditions for those cases do not exist at this time.

Conclusion

In virtually every situation in which financial experts testify concerning the value of the discount rate, the rate of return that they refer to is net of the cost of investment. Hence, it is not necessary to deduct a financial management fee. And, although such a deduction might be necessary in cases in which a mandated discount rate had been used, the rates that have been mandated in Canada in recent years are so low that it must be concluded that they are also net of management fees.

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Christopher Bruce  is the President of Economica; he has a PhD in economics from  the University of Cambridge

Spring 2018 issue of the Expert Witness newsletter (volume 22, issue 1)

Contents:

This issue contains one article. Christopher Bruce investigates the principles that the courts have developed to determine whether experts and their evidence should be admitted into court.

Admissibility of Expert Evidence: Personal Injury Litigation

  • Dr. Bruce argues that these principles can usefully be divided into four categories: the requirement that expert testimony be useful; the identification of whether the expert is qualified; the determination of whether the expert’s testimony is reliable; and the evaluation of the weight that is to be attached to the expert’s opinion.
  • In his article, Dr. Bruce reviews these principles and summarises a number of recent rulings in Canada and the United States with respect to each of them. He finds that the courts are less likely to disqualify witnesses than they are to accept a witness’ qualifications subject to the understanding that opposing counsel will exercise its right to subject the witness to vigorous cross-examination, or to caution that the expert’s testimony will be given reduced weight.

A Pdf. version of the newsletter can be found here.

Admissibility of Expert Evidence: Personal Injury Litigation

by Christopher J. Bruce

The admission of expert evidence has required that the courts maintain a fine balance between, on the one hand, caution against the possibility that witnesses may usurp the court’s role of forming opinions and drawing conclusions; and, on the other hand, recognition of the fact that juries and triers of fact may lack the technical expertise to draw inferences from the facts as presented.

This dichotomy has led the courts and legal commentators to develop a lengthy set of principles concerning the admissibility of experts and their evidence. These principles can usefully be divided into four categories: the requirement that expert testimony be useful; the identification of whether the expert is qualified; the determination of whether the expert’s testimony is reliable; and the evaluation of the weight that is to be attached to the expert’s opinion.

In this article, I summarise some recent rulings in Canadian and American law with respect to each of these categories. I find that although it is rare in western Canada for the courts to disqualify a witness who has been tendered as an “expert,” there are many instances in which the court will accept a witness’ qualifications subject to the understanding that opposing counsel will exercise its right to subject the witness to vigorous crossexamination. And in many others, the court will caution that an expert’s testimony is to be given reduced weight.

1. Useful
The first requirement that must be met before an expert can be permitted to testify – often referred to as the “gatekeeper” component – is that the expert’s testimony must be shown to be “necessary in assisting the trier of fact.” (R. Mohan, [1994] 2 S.C.R. 9). This requirement has a number of implications.

First, the expert’s testimony must not have the effect of usurping the court’s function, of weighing evidence, evaluating the credibility of witnesses, making findings of fact, reaching conclusions concerning legal matters, etc. In Snelgrove, (2015 ONSC 585, at para 12), for example, the court disqualified a witness, in part because he “…purports to come to legal conclusions,” specifically concerning the defendant’s intent, negligence, misrepresentations, and misconduct.

Second, the expert’s report must offer an opinion concerning the issues in dispute. See, for example, Hoang v Vicentini (2012 ONSC 1358) in which an accident reconstruction expert’s report was dismissed on this ground.

Third, for expert evidence to be admissible:

[t]he subject matter of the inquiry must be such that ordinary people are unlikely to form a correct judgment about it, if unassisted by persons with special knowledge. (Kelliher (Village of) v. Smith, [1931] S.C.R. 67 quoting from Bevan on Negligence)

Or, as Lawton, LJ concluded in R. v. Turner ([1975] Q.B. 834, at 841):

An expert’s opinion is admissible to furnish the court with scientific information that is likely to be outside the experience and knowledge of a judge or jury. If on the proven facts a judge or jury can form their own conclusions without help, then the opinion of an expert is unnecessary.

In Canada, there has been little debate about the definition of the term “scientific information” as used in Turner. In the United States, however, two decisions of the Supreme Court – Daubert v. Merrell Dow Pharmaceuticals, Inc ((1992) 509 U.S. 579) and Kumho Tire Co. v. Carmichael ((1999) 131 ) – have ruled on the interpretation of the terms “scientific, technical, or other specialized knowledge” contained in Rule 702 of the U.S. Federal Rules of Evidence. Of particular importance to Canadian practitioners is that the Supreme Court of Canada, in R. v. J.-L. J. ([2000] 2 S.C.R. 600, 2000 SCC 51) explicitly approved of the four criteria set out in Daubert for determining whether expert testimony met the requirement that it constitute “scientific knowledge.” These are:

  1. Whether the theory or technique “can be (and has been) tested”.
  2. Whether the “theory or technique has been subjected to peer review and publication”.
  3. In the case of a particular technique, what “the known or potential rate of error” is or has been.
  4. Whether the evidence has gained widespread acceptance within the scientific community.

The Daubert criteria proved less applicable to issues involving “technical” than “scientific” knowledge, such as that often proffered by engineers, however. Accordingly, the United States Supreme Court agreed to hear Kumho Tire. In that case, an expert in tire failure analysis relied in part on his own (extensive) experience to determine whether a failure in a tire was caused by a defect and not by misuse on the part of the plaintiff. As the expert’s testimony did not meet any of the criteria set out in Daubert, the issue in Kumho was whether “technical and other specialized knowledge,” as defined in Rule 702, was to be subjected to the same criteria as was “scientific knowledge.”

The Court ruled that it was not. Testimony about a technical matter could be considered to be “expert” if it:

…focuses upon specialized observations, the specialized translations of those observations into theory, a specialized theory itself, or the application of such a theory in a particular case.

The function of Rule 702 was not to restrict expert testimony to a narrow set of “scientific” disciplines, but to:

… make certain that an expert, whether basing testimony upon professional studies or personal experience, employs in the courtroom the same level of intellectual rigor that characterizes the practice of an expert in the relevant field.

It was the application of “intellectual rigor” that distinguished an expert from a layman, as much as did the possession of specialised, formal training.

2. Qualified
As the expert’s role is to provide information that is not within the “experience and knowledge of a judge or jury,” it is necessary to show that those individuals who are presented as “experts” possess the requisite training and experience. With respect to scientific knowledge, this has generally meant that the witness must have obtained a graduate degree, such as an M.Sc. or Ph.D., or a professional designation, such as a law or accounting degree. With respect to technical skills, an individual (such as the tire expert in Kumho) may develop “expertise” through long personal experience with the matter before the court. In both cases, however, the witness is expected to apply intellectual rigour to the interpretation of the evidence before the court.

Furthermore, the expert’s testimony may not be admitted if his or her qualifications are inferior to those of other witnesses who have been tendered as experts in the same action. It was for this reason that, in Levshtein v Ramirez (2013 ONSC 521), a chiropractor’s opinion concerning the plaintiff’s ability to perform household tasks was not admitted. Although the chiropractor had performed a number of tests of the plaintiff’s hand strength and weight-lifting ability, the court found that other witnesses were more qualified to testify concerning the extent to which the plaintiff’s physical disabilities had affected his activities in the home.

In a recent survey of more than 12,000 American decisions, PWC (formerly Price Waterhouse Cooper) found that the courts had focussed on two factors: relevant academic credentials and relevant experience, when evaluating qualifications. The courts generally ruled that extensive experience might be sufficient to outweigh lack of credentials (for example, working as an bookkeeper in a role relevant to the case, such as franchising); and appropriate credentials might not be enough if the area of specialization was not relevant (for example, an expert testifying on loss of earnings might have a PhD in economics, but in international trade). (PWC, Challenges to Financial Experts: 2000-2016, (pwc.com).)

3. Reliable
Two broad issues are canvassed when determining whether the testimony of the expert is of sufficient reliability to be of value to the court. First, the evidence presented by the expert must be “relevant;” that is, it must be “… so related to a fact in issue that it tends to establish it.” (Mohan, at 20) Second, the expert must provide an “objective and unbiased” opinion.

Relevant

To be relevant, expert evidence must meet two criteria. First, any factual evidence must meet standard tests of statistical reliability. Data must be collected in a manner that ensures that it is representative of the group to which it is to be applied. For example, if a doctor’s opinion is based on observation of his or her own patients, precautions must be in place to ensure that those patients are similar to the plaintiff in question. Similarly, if evidence is drawn from reports published by third parties, the expert must be careful to ensure that the definitions used in those studies refer to the same concepts that are of importance to the case at hand. [For further elaboration on these points, see Christopher Bruce, “The Reliability of Statistical Evidence Concerning the Impact of Disability” The Expert Witness, 2004 (3).]

Second, there must be a compelling logical and/or statistical correlation between the evidence that has been presented and the conclusion that the expert purports to draw. This is particularly problematic when the expert misunderstands or misrepresents statistical studies that have been published by third parties.

Objective and unbiased

If an expert has a financial, personal, or professional interest in the outcome of a case, which may induce that expert to bias his or her opinion, the court may either disqualify the expert or place reduced weight on that opinion. [The following discussion is informed largely by the decisions in United City Properties v. Tong, 2010 BCSC 111 and R. v Klassen, 2003 MBQB 253; and by Paul Michell and Renu Mandhare, “The Uncertain Duty of the Expert Witness,” Alta L Rev 42.3 (2005).]

Financial: A number of factors have been identified by the courts that may have led the expert to have a financial interest in the outcome of the case. These include:

  • A contingency fee,
  • A long association, or exclusive association, with one lawyer or party,
  • Employment by either the plaintiff or defendant.

Personal: The witness’s objectivity may also be questioned if he or she had:

  • A personal interest in the outcome, either because that outcome would directly affect the witness or because it would set a precedent that would affect him or her,
  • A personal relationship, such as friendship or a family connection, to one of the litigants.

Professional: If the witness has taken a strong stance on a contentious issue facing the courts – such as the manner in which the discount rate is to be determined – that witness may come to consider his or her professional reputation to be dependant on acceptance of that view by the court. This may lead the expert to discount or ignore evidence contrary to his or her professed view.

Even in the absence of evidence that an expert has an interest in the outcome of the case, the court may still find bias, based on the content of the expert’s statements, report, or testimony. Evidence of such bias has been found when:

  • The witness has been found to have made statements publicly that show philosophical hostility towards certain subjects,
  • The expert’s report has been withdrawn or modified without reasonable explanation,
  • The expert’s opinion has been found to differ, for unexplained reasons, between occasions on which the expert appeared for the defence and those when he/she appeared for the plaintiff,
  • The expert has departed from any governing ethical guidelines established in the expert’s field of expertise,
  • The expert has persistently failed to recognize other explanations or to provide a reasonable range of opinion,
  • The witness has operated beyond his or her field of stated expertise, such as when an economist comments on the appropriate costs of caring for an injured plaintiff,
  • The expert has failed to substantiate his or her opinions,
  • The expert has acted as an “…informed champion or enthusiastic supporter of the retaining party’s cause.” (Michell and Mandhare at 648, quoting Halpern v. Canada (A.G.) (2002), 215 D.L.R. (4th) 223 at paras. 143-44 (Ont. Div. Ct.).)

Nevertheless, in Moore v Smith Construction (2013 ONSC 5260), a scientist who worked for an advocacy group that provided legal services to the respondent was allowed to testify as an expert. The court found, following a voir dire, that there was no evidence of bias or partiality. Instead of disqualifying the scientist, the court ruled that the “… fact that the proposed expert is employed by the party can be taken into account when the trial judge assesses the weight and value of the evidence”. (at para 47)

4. Weight

If the court has found a degree of bias in the expert’s testimony, it can choose among: disqualifying the expert, announcing that it will allow the expert’s testimony but give lesser weight to that evidence, or leaving criticism of the expert’s report to cross-examination by opposing counsel.

Of these, the first would seem to be of primary importance in cases that were tried before a jury, and the second and third to cases that were heard before a judge. As a judge will, presumably, be less influenced by biased and unqualified witnesses than would be a jury, it may be less harmful to permit questionable testimony when the case was being tried by judge alone than when it was being heard before a jury. On these grounds, we would expect experts to be disqualified more often in Canadian courts in criminal cases than in tort cases; and more often in tort cases in the United States than in equivalent cases in Canada.

In Gutbir v University Health Network (2010 ONSC 6394), a medical malpractice case, the court allowed the treating physician to testify to fact; but, on the ground that he had a personal interest in the outcome of the case, it denied him qualification as an expert.

Contrary to our speculation above, however, the PWC survey found that American courts are reluctant to exclude expert testimony. Rather they apply a “light hand on the gate”, preferring to subject the expert’s opinion to vigorous cross-examination, especially if the disagreement concerns the choice of an appropriate or inclusive set of data. They were also found to be willing to allow experts to revise their reports in light of objections from opposing counsel.

Summary

The courts admit the testimony of expert witnesses only with a good deal of apprehension. First, they are reluctant to cede their role of weighing evidence, evaluating the credibility of witnesses, making findings of fact, reaching conclusions concerning legal matters, etc. And, second, they have qualms about the qualifications and independence of witnesses who have been tendered as “experts”.

As a result, the courts have developed lengthy lists of requirements that witnesses must meet before they can be accepted. The purpose of this article has been to review these requirements and to ask how they have been applied in practice. The most important finding of this review has been that the requirements have become sufficiently well known that it is uncommon for legal counsel to put forward individuals who fail to meet the court’s assessment. Rare cases remain in which experts are disqualified; but, more commonly, where an expert has been challenged, the court has allowed the expert: to re-write his or her report, to submit the report subject to the condition that it will be given reduced weight, or to testify subject to the understanding that opposing counsel has the right to cross-examine “vigorously”.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary.

Selecting the Discount Rate (2017)

by Christopher J. Bruce, Derek W. Aldridge, Kelly Rathje, Laura Weir

When calculating the lump sum award that is to replace a stream of losses in the future, it is first necessary to determine the rate of interest, or discount rate, at which the award will be invested. In Canada, this rate is set equal to the real rate of interest, that is, to the nominal (or “observed”) interest rate net of the rate of inflation.1

Whereas most provinces mandate the discount rate that is to be used when calculating the present value of future losses, Alberta has left the determination of that rate to the courts. Accordingly, the testimony of financial experts on this matter has become an important element of most personal injury actions.

Over the last forty years, Economica has made important contributions to the debate concerning the choice of a discount rate. These contributions have come in the form of chapters in our textbook, Assessment of Personal Injury Damages (now in its fifth edition), articles in this newsletter, and submissions to reviews of the mandated rates in Ontario, Saskatchewan, and British Columbia.

In this article, we argue that whereas virtually all financial experts (including ourselves) have implicitly applied what we will call here the active management approach to the determination of the discount rate, it can be argued that an alternative technique, which we will call the annuity approach, is often more appropriate.

In Section I of this article, we describe these two approaches and investigate their relative merits. In Section II, we employ the principles developed in the first section, to examine how numerical measures of the discount rate might be obtained when discounting two types of future costs: medical expenses and losses of earnings. Finally, in Section III, we summarise our findings.

In that Section, we argue that:

  • if the plaintiff chooses to self-manage the investment of his or her award, the appropriate discount rate (net of inflation) is 2.5 percent; whereas
  • if the plaintiff chooses to purchase a life annuity, or have the defendant purchase a structured settlement, the appropriate discount rate (net of inflation) is zero percent. We argue that it is to the advantage of plaintiffs to make this choice in most cases in which their losses are expected to continue into ages of high mortality (usually after age 75 or so).

I. Two Approaches to Selecting the Discount Rate

There are two broad approaches to the determination of the discount rate, the annuity approach and the active management approach. In the former, it is assumed that plaintiffs will use their lump sum awards to purchase annuities. In the latter, it is assumed that they will invest their awards in a portfolio of stocks, bonds, mutual funds, and other financial assets.

In this section, we define the two approaches and investigate their relative merits. We conclude by identifying the circumstances in which each approach might be preferred to the other.

1. The Two Approaches Defined

The Annuity Approach

If the plaintiff has been awarded a lump sum award to replace a stream of losses from the date of trial until some specified termination date – most often the plaintiff’s projected date of retirement or date of death – he or she will be able to replace the future losses by purchasing an annuity, usually from a life insurance company. This purchase can take the form of either a life annuity or, under the auspices of the court, a structured settlement. In either case, the plaintiff will receive a specified stream of benefits until the termination date.

The purchase price of the annuity will be determined by three main factors: the value of the annual payments, the number of years to the termination date (which will, in part, be determined by the life expectancy of the plaintiff), and the rate of interest at which the insurance company is able to invest the funds received from the plaintiff (or defendant, in the case of a structured settlement).

It is this rate of interest that is known as the discount rate. In the case of an annuity, the discount rate is determined primarily by the requirement (arising both from regulation and accepted accounting practices) that the stream of payments the insurance company has contracted to make is matched by the stream of income that the company will receive from its investment. That is, at the time the annuity contract is signed, the insurance company will invest a sufficient amount, in secure financial instruments, that the income generated from that investment will be sufficient to fund the stream of payments the company has contracted to pay.

What this implies is that for each promised future payment, the insurance company will, implicitly make a separate investment that will generate sufficient returns that it will be able to cover the contracted payment at the appropriate date. For example, if it has contracted to pay $50,000 per year for ten years, it will make ten separate investments, each of which has a maturity value of $50,000.

The discount rate applicable to the payment that must be made one year from now is the interest rate currently available on one-year investments (such as one-year bonds); the rate applicable to the payment to be made two years from now is the interest rate currently available on two-year investments; etc. Thus, there could, in principle, be as many discount rates as there are time periods in the plaintiff’s stream of losses. (In practice, however, investments for more than ten or fifteen years tend to have the same interest rate, so a thirty-year annuity might require ten discount rates.)

Note, first, that there is not “a” discount rate. Rather, there is one rate for each year over which the stream of payments is to be made into the future.

More importantly, note also that it is not necessary to “predict” the discount rate(s). As the investments are to be purchased today (i.e. at the date of settlement), it is the interest rates that are available today that are to be used – and these rates are readily available.

Structured settlement: If it is assumed that a structured settlement is to be purchased, the argument concerning choice of a discount rate is similar to that for a life annuity. Again, the insurance company will place the lump sum received from the defendant in a series of investments, each of which will mature on the date that the payment is due. As the insurance company can be expected, once again, to purchase secure investments, the rates of return that are currently available on such investments can be used to determine the discount rate(s).

The Active Management Approach

Alternatively, the plaintiff might use his or her award to purchase a mixed portfolio of financial assets – for example, stocks, bonds, and mutual funds – selling and buying components within that portfolio as changes occur in financial markets. Because the individual is continuously selling old investments and purchasing new ones, the returns on those investments will reflect rising (and falling) rates that are available in the financial markets.

The complication that this approach introduces is that the rates of return that will be available at the times the plaintiff reinvests his or her funds are not known at the time that the court award is made. These rates must be predicted – in contrast to the rates employed in the annuity approach, which are known at the time the award is made.

2. Comparison of the Two Approaches

As the plaintiff’s award is intended to replace an ongoing loss, it is important that the income the plaintiff receives from investment of that award is sufficient, in each period, to provide the desired compensation. In turn, this requires that the rate of return on that investment be as predictable as possible. The less predictable is the rate of return, the less certain can the courts be that the award will be sufficient for its purposes.

The predictability of the rates of return obtained under the annuity and active management approaches differs with respect to three characteristics: volatility of the rate of return on the invested funds, uncertainty concerning the plaintiff’s life expectancy, and protection against unanticipated increases in the rate of inflation. In this section, we compare the two investment approaches with respect to each of these characteristics in turn.

Volatility

The volatility of a class of investments refers to the variability in the rate of return earned on those investments over time. According to one source:

… volatility refers to the amount of uncertainty or risk about the size of changes in a security’s value. A higher volatility means that a security’s value can potentially be spread out over a larger range of values. This means that the price of the security can change dramatically over a short time period in either direction. A lower volatility means that a security’s value does not fluctuate dramatically, but changes in value at a steady pace over a period of time. [investopedia.com, emphasis added]

The more volatile is the price of a security, the more likely it is that the rate of return on that security will deviate from its long run average. In some periods the return will rise above the average and investors will experience a windfall; but in other periods, the return will fall below average and investors will experience a shortfall.

In the very long run, high returns and low returns may average out, and the rate of return obtained will trend towards the long run value. However, many plaintiffs do not invest for a period long enough that they can be confident that the rate of return on investment of their awards will settle on the long run average. This will particularly be true if plaintiffs are unlucky enough to make a major investment shortly before markets enter a sharp downturn such as was experienced in 2008, (or lucky enough to invest shortly before an upturn, such as in 2010).

To avoid the uncertainty that may result if the plaintiff’s award is invested in volatile financial instruments, it is often recommended that they concentrate their investments on secure, non-volatile stocks, bonds, and mutual funds. The Canadian courts have confirmed this recommendation. For example, in its seminal decision in Lewis v. Todd (1980 CarswellOnt 617), the Supreme Court of Canada approved of an expert witness’s use of “high grade investments [of] long duration.” [para. 17]

Investments in life annuities offer the lowest volatility possible: essentially, the rate of return is guaranteed as long as the insurer, and its re-insurers, remains viable.

Investments in an actively managed portfolio experience two forms of volatility that are not found with annuities. First, all but the most conservative, high grade investments experience variations in returns from year to year.

Second, even if a sophisticated investor could avoid most year-to-year variations in the rate of return, no investor can protect him- or herself against variations that occur due to long-term changes in the economy. For example, assume that it had been anticipated that the plaintiff would be able to obtain a two percent rate of return on investment of his/her award, because the economy was expected to grow at that rate. If broad economic fundamentals should change, such that long run growth fell to one percent per year, it is unlikely that the individual investor would be able to maintain a two percent return on investments.

To conclude, if the goal is to minimize volatility in the returns on the plaintiff’s investments, life annuities and structured settlements are superior to active management, especially in the long run. For short periods of time, perhaps five or ten years, an actively managed “portfolio of high grade investments” may offer almost as much security as an annuity.

Life Expectancy

Assume that a plaintiff will require medical expenses of $50,000 per year for the rest of his life. In a personal injury action, his award will be calculated to ensure that if he invests that amount in a fund composed of secure investments, it will provide $50,000 per year for the lifetime of the average Canadian of his age and sex. For example, if he is a 50-year-old Canadian male his life expectancy is approximately 31 years, to age 81. Thus, his award will be calculated to ensure that he can remove $50,000 per year until his age 81, at which point the award have been drawn down (approximately) to zero.

This puts the plaintiff in a quandary: that the life expectancy of 50-year-old males is 31 years implies that (approximately) half of 50 year old males will live longer than 31 years (and half less than that). Thus, if the plaintiff spends $50,000 per year on medical expenses there is a 50 percent chance that his investment fund will be exhausted before he dies.

Alternatively, if he spends less than $50,000 per year, to leave money in the fund for the possibility that he will live beyond age 81, he will have insufficient funds in every year to pay for his required expenses. Even if it happens that the plaintiff lives less than 31 years, he will have been inadequately compensated for his necessary expenses, because he will have been taking the (reasonable) precaution of spending less than $50,000 per year to create a buffer for the possibility he will live longer than average.

In short, if plaintiffs invest their awards in actively managed investment funds, it is virtually certain that their awards will be insufficient to compensate them fully.

Furthermore, it can easily be shown that this outcome also arises when the amount to be replaced is a loss of income – although the shortfall will be less in this case than in the case of most medical expenses, because the impact of mortality is much lower when the loss continues only to retirement ages (when mortality rates are still low) than when it continues to the end of life.

If the plaintiff’s award is placed in a life annuity or structured settlement, however, payment of the desired annual compensation will be guaranteed from the date of settlement to the end date of the compensation period.

In short, whereas a life annuity will pay the plaintiff an amount equal to his or her loss in every year, an award invested in a portfolio of funds will, in most cases, undercompensate the plaintiff. This under-compensation will often be less when the award is intended to compensate for a loss of earned income than when it is to compensate for long term costs of care. Thus, on this ground, life annuities are slightly preferred to mixed portfolios of investments when there has been a loss of earnings; but annuities are definitely preferred when there is a long-term requirement for payment of medical expenses.

Unanticipated Inflation

A drawback to the annuity approach is that the stream of income that it provides may prove to be inadequate if inflation rates rise unexpectedly. For example, if an annuity provided for $10,000 per year, increasing each year at two percent (to allow for anticipated inflation), it would pay $12,190 in year ten. But if inflation proves to be four percent per year, the plaintiff will require $14,800 in year ten to buy what $10,000 would have bought in year one. The annuity will pay $12,190 when $14,800 is required.

It is often possible to buy annuities whose annual payouts increase with the actual rate of inflation. However, as the risk facing the sellers of annuities is quite high in this case, the price of these annuities may be higher than many buyers are willing to pay.

An alternative method of protecting against the effect of unanticipated inflation is to invest in an actively managed portfolio of assets. Under this approach, the individual is assumed to buy and sell financial assets on a continuing basis, replacing low-earning assets with higher-earning ones as market conditions change. If inflation increases, so will the returns on investments, particularly bonds, allowing the plaintiff to maintain a real rate of return (i.e. a rate net of inflation) that is consistent over time.

On this ground, if the rate of inflation cannot be predicted easily, the active management approach may be preferred to the annuity approach. However, central banks around the world have become convinced that one of their primary functions is to maintain a steady, low rate of inflation. The Bank of Canada, for example, has successfully targeted a rate of two percent since the early 1990s. This policy has been so well received that virtually all financial analysts expect this rate to be maintained well into the future.

As there is no reason to expect that the future rate of inflation will deviate significantly from the rate that has been experienced for the last twenty years, there is little reason to base the selection of the investment approach on the need to protect against unanticipated changes in the rate of inflation.

We conclude, therefore, that the ability of the active management approach to provide protection against unanticipated inflation does not offer a compelling reason to choose that approach in preference to the life annuity approach.

3. Summary

We summarise this section by investigating the merits of using the two investment approaches to replace (i) costs of medical care and (ii) losses of earnings.

Costs of Medical Care

For two reasons, if the plaintiff’s award is intended to provide compensation for medical expenses, particularly expenses that extend well into the future, we recommend that the award be invested in a life annuity (or structured settlement). First, as medical expenses are often required for the plaintiff’s entire life, it is important that the award is able to provide benefits should the plaintiff live beyond the average life expectancy. Whereas this can be achieved easily using a life annuity, it cannot be done through the active management approach.

Second, as the requirement for medical expenses often extends many decades into the future, the returns on awards invested in actively managed funds may be subjected to significant volatility, hence placing the risk of inadequate compensation on the plaintiff. The returns on a life annuity, however, are guaranteed by the insurer, thereby removing the risk of volatility from the plaintiff.

The contrary argument, for using the active management approach to the funding of future medical expenses, is that this approach allows for protection against unanticipated inflationary changes. We have argued, however, that such changes are not expected to be so large as to counter the arguments for use of life annuities. Furthermore, if the courts decide that inflation is likely to become an important factor, they can require that plaintiffs purchase inflation-protected life annuities.

We conclude that, in most cases, it should be assumed that when the plaintiff’s award is to provide for medical expenses, it will not be invested in actively managed funds but will, instead, be used to purchase life annuities. The exception occurs when medical expenses are required for only a short period of time.

Loss of Earnings

When the purpose of the plaintiff’s award is to replace a future stream of lost earnings, the argument in favour of life annuities is weaker than it was with respect to medical expenses. The reason for this is that earnings losses will generally end at an age at which the annual rate of mortality is still quite low.

For example, as we argued above, if a 50-year-old man has a life expectancy of 81, there is (approximately) a fifty percent chance that he will live beyond that age and will exhaust any award for medical expenses. Assume, however, that that individual had planned to retire at age 60, bringing any loss of earnings to an end at that age. As the probability of dying before age 60 is very small, the difference between an award that allowed for that probability and one that did not would also be small. Thus, any “error” that arose from using the active management approach might be compensated by other factors.

If we assume again that the risk of unexpected changes in inflation is small, then the primary difference between the annuity approach and the active management approach (with respect to losses of earnings) will arise with respect to volatility. On this basis alone, the annuity approach will be preferred as it offers less risk that an unanticipated fall in interest rates will leave the plaintiff’s award inadequate.

However, it is possible that this uncertainty concerning the rate of return on investments might be offset if the active management approach provided higher average rates of return. For example, if those rates were two or three percentage points higher than those offered by the sellers of life annuities, plaintiffs might prefer to manage their own funds rather than rely on an annuity.

For this reason, we suggest that the active management approach be employed only if it is clear that the plaintiff does not wish to invest his or her award in an annuity (as, in this case, the plaintiff has signaled that the rate of return on actively managed assets is high enough to compensate for the increased risk).

II. Evidence Concerning the Value of the Discount Rate

1. The Annuity Approach

If it is assumed that the plaintiff will purchase a life annuity, the appropriate discount rate will be the rate(s) of return that life insurance companies use when pricing those annuities. In this section, we argue that these rates will approximate the rates of interest that are available on Government of Canada bonds of the appropriate durations.

In Table 1, we summarise those rates for five-year, ten-year, long-term, and real rate of return bonds and for GICs of one-year, three-year, and five-year terms. In this table, the term “long-term bond” applies to government bonds with maturation dates of fifteen years or more. “Real rate of return bonds” are bonds whose rate of return is specified as a fixed value (the real rate of return) plus the actual rate of inflation. Thus, for example, if the fixed value is 1.0 percent and the rate of inflation proves to be 2.5 percent, the bond will pay (approximately) 3.5 percent.2

Table 1 reports both the nominal (observed) and real (net of inflation) rates of return on five- and ten-year bonds, long-term bonds, and GICs. In each case, the real rate has been calculated by reducing the nominal rate by the expected rate of inflation, two percent.3 As the interest rate on real rate of return bonds is reported as a real rate, we report only the real rate of return on those bonds.

In Table 1 it can be seen, first, that the real rates of return on government bonds increase as the duration of those bonds increase; thus confirming that there is not a single discount rate but rather a different rate for each length of investment.

Second, it is also seen that the real interest rates on secure bonds have not recently risen above 0.5 percent for investments of any duration; and have risen above 0.0 percent only on real rate of return bonds.

Our contention is that these rates can be used as indicators of the rates at which life insurance companies will invest the funds they receive for life annuities and structured settlements. We can test this contention by comparing the interest rates employed to determine the prices of structured settlements against the rates reported in Table 1.

This we have done by obtaining quotes for several alternative structured settlements. From these we have been able to determine the interest rates that were employed to obtain those quotes. In Table 2 we report six such structured settlements, for males receiving $1,000 per month ($12,000 per year).4

Three scenarios represent payments that end at age 60 and three represent payments that continue to the date of the plaintiff’s death. (Those that end at age 60 are assumed to be typical of awards for loss of earnings; and those that continue for life are assumed to be typical of awards for medical expenses.) The assumed ages for the plaintiffs, at the date of trial, are, respectively, 20, 35, and 60. Furthermore, in each case we report quotes for both the situation in which the annual payment is to increase by two percent per year and for that in which it will increase by the actual rate of inflation.

Column (4) of Table 2 reports the quotes we received, assuming that the annual payment was to increase by the actual rate of inflation; while column (6) reports the quotes assuming that the annual payment was to increase by two percent per year. Columns (5) and (7) then report our calculation of the implied interest rates that were used to obtain the costs of the various annuities.

For example, the first figure in column (4) indicates that it would cost $489,176 to purchase an annuity that paid a male plaintiff $12,000 per year, indexed for inflation, for the next 40 years (i.e. from age 20 to age 60). The first figure in column (5) then indicates that the insurance company that quoted this amount had implicitly assumed that its investments would earn an average real rate of interest, (i.e. nominal interest net of inflation), of -0.27 percent over the 40-year period in question. Similar costs and real interest rates are reported for the other eleven scenarios.

Notably, in every case in which the payments were fully indexed for future inflation (column 5), the implied real rate of interest was negative – between -1.24 percent and -0.27 percent. It is only when the payments did not provide full protection against inflation – column 7, in which increases were limited to two percent per year – that insurers offered a positive real interest rate. Even then, rates were less than one percent.

We would note that the implied discount rates of the annuities presented in Table 2 are consistent with the implied discount rates of annuities offered  by private insurance firms such as Sun Life Financial and RBC Insurance. For example, the Sun Life Financial annuity calculator indicates that as of April 2017, a $1,000,000 annuity for a 50-year old female will provide an annual income of approximately $41,819 per year (with no inflation adjustment). This implies a discount rate of approximately 0.13 percent. The annuity calculator provided by RBC Insurance indicates that as of April 2017, a $1,000,000 annuity will provide a 55-year old male with annual payments of approximately $50,931 (with no inflation adjustment), for an implied discount rate of 0.15 percent.5

It is informative to compare the rates employed in the calculation of structured settlements (and private annuities) with the rates reported for government bonds, in Table 1. The two annuities with the shortest durations – ten years, from age 50 to 60 – had implied discount rates of -1.24 and -1.02 percent, both very similar to the figure of -1.23 percent reported in Table 1 for five-year bonds in 2016. Similarly, the two annuities with the longest durations – from age 20 for life – had implied discount rates of -0.57 percent and +0.65 percent, with an average very close to the figure of -0.08 percent reported in Table 1 for long-term government bonds.

We conclude from Tables 1 and 2 that, in cases in which the plaintiff purchases a life annuity or structured settlement – particularly one that is fully indexed for inflation – the discount rate can be estimated with some accuracy from the real rates of return currently available on Government of Canada bonds of appropriate durations.

2. Active Management Approach

In the active management approach, it is assumed that plaintiffs will re-allocate funds within their investment portfolios as conditions in financial markets change. Because these changes will be made in the future, the active management approach requires that estimates of future rates of return be calculated.

In this section, we first identify the type of financial instrument in which we assume the plaintiff will invest. We then contrast two methods of forecasting the rates of return on those instruments. Finally, we provide estimates of those rates of return.

Selection of the Appropriate Financial Instrument

The courts have been clear that, as the lump-sum award is intended to replace the plaintiff’s lost earnings, the investments in the plaintiff’s portfolio must not expose the plaintiff to unreasonable risk. For example, in its seminal decision in Lewis v. Todd (1980 CarswellOnt 617), the Supreme Court of Canada approved of the expert’s use of “high grade investments [of] long duration” [para. 17].

As the rates of return on investments in the stock market have historically been very volatile, it is usually recommended that plaintiffs do not restrict their investments to equities. Table 3, for example, reports the value of the Toronto Stock Exchange composite index for July of each year since 2000. It can be seen there that rates of return have been highly volatile, indicating that the rate available to an individual whose investments tracked the market would have depended importantly on the year in which those investments were made. For example, whereas the nominal return on investment in such a portfolio would have averaged 2.2 percent per year between 2000 and 2015, a similar investment would have averaged 6.2 percent per year between 2002 and 2015.

In light of this issue, two approaches might meet the court’s requirement that plaintiffs invest in high grade investments: it could be assumed that plaintiffs will purchase long-term Government of Canada bonds; or that they will invest their awards in financial instruments that offer higher yields than government bonds, but with greater risk – for example, in a mixed portfolio of “blue chip” stocks, corporate bonds, and mutual funds. In the discussion that follows, we will consider both.

Forecasting the Returns on Government Bonds

Two methods have commonly been used to forecast the rate of interest that will be available on government bonds. The first of these, the historical approach assumes that future rates will equal those that were observed in the past. The second, the efficient market approach, assumes that the rates that are currently available in the market reflect the rates that investors believe will prevail in the long run. We explain here why we prefer the efficient market approach.

The historical approach: A fundamental problem with the historical approach is that real interest rates have varied significantly over the last sixty years. As can be seen from Table 4, real rates were as low as 1.50 percent in two decades (1951-1960 and 1971-1980) and as high as 4.70 percent in two others (1981-2000). From this record, it would be possible to find support for almost any long-run rate between 2.0 and 5.0 percent.

More importantly, as indicated in Figure 1, real rates of return have declined virtually continuously for the past twenty years, from approximately 5.5 percent to -0.5 percent. Even if it was to be argued that real rates of interest will return to, say, 3.0 percent over the next twenty years, most plaintiffs will experience rates of return well below that over most of the period in which their award is invested.

A third problem with the use of historical rates is that there is no theory to support it. Adherents simply assume that because real rates took some value in the past, rates will return to that value in the future. Furthermore, they make this assumption in the face of the long run decline in real interest rates reported in Figure 1. If the markets expected the real rate of interest to return to “long-run” levels soon, sophisticated investors would not continue to purchase financial instruments that paid long-run rates as low as -0.08 percent (Table 1).

Finally, the evidence is not just that the real interest rate has declined significantly; this decline is consistent with theoretical predictions. Importantly, as central banks have adopted a policy of maintaining inflation within a narrow band of rates (in Canada, between 1.0 and 3.0 percent), uncertainty about the rate of inflation has been minimized. This reduction in risk has led to an increase in demand for bonds, and an associated reduction in real interest rates.

The Congressional Budget Office of the United States also predicts that interest rates will be lower in the future than in the past, resulting in part from slower growth rates of both the labour force and of productivity, thereby reducing the rate of return on capital; and in part from a shift of income to high-income households who tend to have high savings, thereby increasing the supply of money to the bond market.

The efficient market approach: The second source of information concerning future real rates of interest is the money market. When an investment firm that believes that inflation will average two percent per year purchases twenty-year Government of Canada bonds paying three percent, it is revealing that it expects the real rate of interest on those bonds will average approximately one percent over those twenty years. Thus, if the rate of inflation that investors were forecasting was known, that forecast could be used to deflate the nominal rates of interest observed in the market to obtain the implicit, underlying forecasts of real rates.

A strong case can be made for using an expected inflation rate of two percent. The reason for this is that in the last decade the Bank of Canada has not only made this its target rate of inflation, it has been successful in keeping the actual (long-run) rate of inflation very close to that target (which, in turn, has led most financial institutions to predict that future inflation will average two percent).6

Furthermore, in choosing to target a low rate of inflation, the Bank has been following a view that has achieved widespread acceptance in the economics community – that is, that control of inflation, at a low level, should be one of central banks’ primary roles.

On this basis, at the end of 2016 the real rate of interest on long-term government of Canada bonds appeared to be as little as 0.00 percent. (See the figures for long-term bond rates in Table 1.)

An alternative approach is to rely on information concerning bonds whose rate of return is denominated in terms of real interest rates – called real return bonds, or RRBs. By observing the rates of return at which these bonds sell, the risk free real rate of return that investors believe will prevail over the long run can easily be determined. That is, even if plaintiffs do not purchase RRBs, the real rate of interest that is observed on those bonds provides an unbiased indicator of the rate of interest that is expected by sophisticated investors. In Table 1, it is seen that the return on these bonds has recently fallen to as little as 0.41 percent.7

Forecasting Returns on a Mixed Portfolio

Forecasting the returns on a conservative, mixed portfolio is complicated by the fact that there is no common agreement about what the components of such a portfolio should be. Hence, not only is it difficult to obtain the current rates of return on conservative investments, there is also very little information about how such returns have varied over the past. Both issues complicate the forecasting process.

An approach that we suggest might mitigate this problem would be to rely on the rates of return that have been available on conservative portfolios offered by Canadian banks. We have been able to obtain information about four of these: the RBC Select Very Conservative Portfolio, CIBC Managed Income Portfolio, TD Comfort Conservative Income Portfolio, and ScotiaBank Selected Income Portfolio-Series A. Although these funds differ from one another in their details, they all have investment objectives similar to those stated for the RBC portfolio:

To provide income and the potential for modest capital growth by investing primarily in funds managed by RBC Global Asset Management, emphasizing mutual funds that invest in fixed-income securities with some exposure to mutual funds that invest in equity securities. The portfolio invests in a mix of Canadian, U.S. and international funds.

To achieve this goal, RBC invests primarily in bond funds. The result, seen in the first columns of Table 5 below, is that since 2011 this fund has consistently earned a nominal rate of return between 2.5 and 5.0 percent – with one deviation, to 6.74 percent, in 2014 – suggesting a real rate of return over that period of approximately 1.0 to 3.5 percent. Table 5 reports similar results for the other three portfolios (again, with 2014 being the only year that each of them achieved a nominal return that exceeded 5.00 percent).

The volatility in the rates of return on all four portfolios reported in Table 5 is considerably less than that on investments in the Toronto Stock Exchange, as reported in Table 3.

But that does not necessarily mean that plaintiffs would be advised to invest in a conservative mixed portfolio. Although the returns on such portfolios may be higher than that on life annuities, the returns on the latter are fixed once they are purchased, and hence have lower (zero) volatility than the returns on all other investments. The question remains: do the higher rates of return on mixed portfolios compensate the plaintiff for the higher volatility of their returns? This is a question that cannot be answered by financial experts, but only by the courts or government regulators.

What Table 5 does suggest, however, is that if plaintiffs had purchased mixed conservative portfolios in the last five years they would have achieved average nominal returns of between 3.5 and 4.5 percent per annum – or approximately 2.0 to 3.0 percent in real terms. This suggests that 2.5 percent represents a conservative estimate of the real rate available to plaintiffs seeking conservative investments.

III. Summary

In personal injury and fatal accident actions, the plaintiffs are assumed to invest their awards in such a way as to provide streams of returns that will replace their future annual losses. Two factors may intervene to hinder plaintiffs’ ability to achieve this goal. First, they may live longer than average. Second, the rate of return on investments may fall below the level that was anticipated when calculating their awards. In both cases, the award will be exhausted before the plaintiff’s death.

One approach plaintiffs can employ to avoid these problems is to invest their awards in life annuities or structured settlements, as these instruments guarantee a specified annual payment for life, and as the rates of return available on them are fixed.

The drawback to annuities is that the interest rates that insurance companies use to price their products are much lower than the rates of return that have been available on conservative mixed portfolios of financial assets. We showed in Section II that, whereas the implicit interest rates on life annuities are similar to the rates available on long-term Government of Canada bonds, or approximately 0.0 to 0.5 percent, the interest rates available on conservative portfolios of assets have been approximately 2.0 to 3.0 percent.

If a loss will not continue into the years beyond which mortality rates begin to rise substantially, the advantage of buying a life annuity may be relatively small compared to investing in a portfolio of assets. In that case, it may be appropriate to assume that that the discount rate can be estimated from the return on a portfolio of assets.

If the loss will continue into years of high mortality, however, the benefits of a life annuity (protection against exhaustion of the award) may exceed the costs (a lower rate of interest).

As it is only the plaintiff who can determine whether the benefits of a life annuity exceed the costs, it seems appropriate that the discount rate be chosen based on the plaintiff’s decision whether to self-manage the investment of his or her award or to use that award to purchase a life annuity (or structured settlement).

  • If the plaintiff chooses to self-manage his or her award, we recommend that the discount rate be set at 2.5 percent.
  • If the plaintiff chooses a life annuity or structured settlement, we recommend that the discount rate be set at zero percent.
  • We anticipate that plaintiffs will make the latter choice in virtually all cases in which their losses will continue into years of high mortality.

 

The Structure of a Cost of Care Report

by Christopher J. Bruce, Kelly A. Rathje

As economists, we are often asked to calculate the present value of future costs of care. As these calculations are based on the reports of cost of care experts (CCEs), we have become uniquely familiar with the structure and content of those reports.

In this article, we provide a review of the format and contents of cost of care reports, drawn from our experience using those reports as inputs into our own calculations. We anticipate that this review will be of greatest use to:

  1. members of the bar: as a checklist against which to evaluate the cost of care reports that have been provided for them and their opponents;
  2. individuals who have recently begun preparing cost of care reports: to provide them with an understanding of how those reports will be used; and
  3. experienced cost of care experts: as an analysis of some of the complexities that can arise in personal injury actions. For these experts, most of our suggestions will be familiar; but we hope that we raise sufficient questions to make this report of interest to them also.

Incremental Costs

One of the most difficult questions facing the cost of care expert (CCE) is that of distinguishing between those costs that would have arisen had the plaintiff not been injured and those that have arisen as a result of the plaintiff’s injuries. This issue is particularly important when the item required with-accident differs only in quality or type from a similar item that would have been purchased without-accident, for example when the plaintiff now requires a different type of automobile than she would have purchased had she not been injured.

A number of issues arise with respect to incremental costs:

1) When the item required by the plaintiff costs more than the equivalent item for a non-injured person, it is important to be very clear about what is being assumed about the characteristics of the item that would have been purchased by the non-injured person. For example, assume that it has been recommended that a paraplegic purchase a van that costs $45,000 per year. As the incremental cost is the difference between that $45,000 and the cost of the car the plaintiff would have purchased if he had not been injured, it is important that the CCE be able to defend any assumption that has been made about the cost of the latter. Would the plaintiff have owned a Honda that cost $20,000, or a Lexis that cost $50,000? On what basis has that conclusion been reached?

2) Following from the preceding point, it is also important to alert the reader to the possibility that the item that has been recommended by the CCE may be of a different quality than the item the plaintiff would have purchased had she not been injured. Would a $45,000 van, for example, “replace” a $50,000 Lexis? And would the quality of accommodation and food in, say, a nursing home replace the equivalent items in the plaintiff’s own home?

3) An important example of quality differentials arises with respect to the care of injured children. Assume that a child’s injuries are sufficiently severe that the CCE has recommended that professional child care be provided for her – for example, 24-hour attendants. Assume also that the child has a stay-at-home mother; that is, one who would have provided 24-hour care before the child began school. Can it be argued that, as the child would have received 24-hour care in the absence of the accident, the accident has not caused any increment in costs? The answer to this question depends on whether the type and extent of care (i.e. the “quality” of care) that the child now needs exceeds that which would normally have been provided by her parents. For example, during the ten hours that the child normally sleeps, incremental care might be recommended because she will wake more often than normal, or because specialized medical care will be required during those hours. If so, it would be useful if this was specified in the cost of care report. Similar specifications may also be necessary with respect to time that a non-injured child would have spent at school or in day-care.

4) When estimating what the plaintiff would have spent on a category of items if he had not been injured, a distinction must be made between the expenditures that he is currently incurring and those that he would have incurred if he had not been injured. For example, if the accident has reduced the plaintiff’s income, it is quite possible that he will now be living in an apartment with a lower monthly rent than he would have incurred had he not been injured. It is the difference between the rent of the apartment the CCE has recommended (with-accident) and the rent of the apartment he would have lived in (without-accident) that is the incremental cost due to the accident.

5) If the item owned by an injured plaintiff has a longer or shorter life expectancy than the equivalent item owned by a non-injured person, the CCE should identify what that difference is. For example, the van required for a paraplegic might have a five-year use life, whereas the car that the plaintiff would have driven if she had not been injured might have had a ten-year life. In such a case, it would not be appropriate to calculate the incremental cost by deducting the purchase price of the car the plaintiff would have bought from the purchase price of the van, as two vans will have to be purchased for each car.

Variations over Time

The requirements for many items will vary over the plaintiff’s lifetime. It is important to identify when such changes will occur and what their effect will be on annual costs:

1) The plaintiff would have incurred some of the costs of care at various times in his lifetime even if he had not been injured. For example, at age 80, the plaintiff may have hired a housekeeper. Thus, if the CCE had recommended housekeeping services from the date of the accident, for life, the cost that would have been incurred after 80 must be deducted from the recommended expense. In such cases, it would be useful if the CCE was to indicate the age at which the plaintiff would have incurred the stated expense (in the absence of the accident), and what the difference is between the cost of the recommended level of housekeeping and the level that would have been purchased had the accident not occurred.

2) It is important to be clear about variations in expenses over the course of a year – such as due to school holidays and vacations – and over a lifetime – such as because the plaintiff would have started elementary school, entered university, had children, or retired.

3) If the plaintiff will have to undergo surgery in the future, the CCE should indicate how long the recovery period will be and how much the extra costs will be during that period. Also, it will be useful to the economist to know whether the plaintiff will be able to return to work before the end of the recovery period.

Ranges of Estimates

We often find that CCEs provide a range of estimates for the cost of a recommended item. For example, it might be reported that the cost of personal care attendants will vary from $14,500 per year to $21,400. When the CCE wishes to report such a range, we recommend that a reason be provided why a single number would not be appropriate, and the source was of each of the costs in the range be identified. For example, if there is more than one cost, that might be because:

  • the CCE received more than one quote, from more than one provider (and if so, why was the lowest quote not chosen?);
  • there were different costs for different qualities of the product;
  • different costs were appropriate to different potential medical outcomes;
  • costs varied among cities in which the plaintiff might live; etc.

Housekeepers and Personal Care Attendants

The CCE report should clearly specify the sources for the hourly costs of individuals who provide housekeeping services, such as housecleaners, yard workers, and maintenance workers. Otherwise the cost of care report may be subject to criticism from experts, such as economists, who are familiar with data concerning the wage rates of these individuals.

Once it has been determined how many hours are required for each type of personal care attendant (for example, nurses and LPNs), there are two basic approaches to estimating the cost of those individuals. The first of these, the agency approach, is to obtain the cost of hiring an agency that will be responsible for all of the specified activities. The second, the hourly wage approach, is to obtain an hourly wage for each type of attendant and then multiply those wages by the specified hours for each type.

Although the latter approach often appears attractive, in the sense that it yields a lower estimate of costs than does the former, there are many reasons to be cautious about use of this approach. First, unless the plaintiff is capable of handling his/her own affairs, the hourly wage approach often assumes that there is a family member who will work without compensation to hire and supervise attendants. But, even if such individuals are available currently, there is no assurance they will be available over the entire course of the plaintiff’s disability. Furthermore, in those years in which family members are available to assist the plaintiff, the courts will generally allow them to claim for the costs of their time, invalidating the assumption that their time is “free”.

Second, the hourly wage approach may not take into account that substitutes will have to be provided for attendants who are ill, wish to take vacations, or who quit without warning.

Third, allowance has to be made for the possibility that attendants will not provide adequate care. This requires that the family or plaintiff have some expertise in both the investigation of the backgrounds of potential hires and in the provision of supervision of existing employees.

Finally, the hourly wage approach would have to provide an allowance for the hiring of additional personnel when emergencies arose. Whereas most agencies will be able to call on their own nurses, and will have close contacts with doctors, ambulances, and hospitals; the plaintiff and his/her family will generally have no expertise in hiring these experts.

Other Factors

We also make the following recommendations concerning the cost of care report:

1) The report should indicate whether GST is included or excluded in the costs recommended.

2) As some items will be GST-exempt while others will not, it is important to distinguish between the two.

3) Indicate whether the costs identified for a particular item are for a different year than the one in which the report was written. For example, if a report was written in 2015, the costs may have been collected from 2014 price lists, or may have been forecasted for a settlement date in 2016. [We generally assume that a report written in 2015 uses “2015 prices”.]

4) It may be advisable, particularly in contentious cases, to have a physician read the CCE’s report and approve the medical expenses, in writing.

Presentation

In addition to the recommendations we have made above, concerning the content of the cost of care report, we also have a number of (minor) suggestions concerning the format, or presentation, of that report:

1) We appreciate it when the CCE provides a summary table in which the annual cost of each item is clearly set out, along with the number of years each cost is to be repeated. We acknowledge that at times, a unit cost, such as medication costs per unit, plus the number of units required over a specific time period is provided. This is just as useful to us, as from this information we can easily determine an annual cost1.

2) If an expenditure is to be made less often than annually – for example, replacement of a car or wheelchair once every five years – it is not necessary for our purposes that the CCE averages the costs over the life of the item. Provide only the replacement cost and the number of years between replacements.

3) On items like cars, houses, and wheelchairs, the cost of care report should, however, provide the annual costs of repair, maintenance, and operation. For a car, for example, provide estimated costs of repairs, of oil changes, and gasoline and tires.

4) The report should be clear about time ranges. For example, it is confusing to say that an item will cost $600 per year from age 25 to 35 and $450 from age 35 to 45, as that leaves it unclear what the cost will be at age 35. We would recommend, instead, that the report say something like: the item will cost $600 per year from 25 to 35 and $450 per year from 36 to 45.

5) There is no need to “round” numbers up or down as economists use spreadsheets for their calculations.

A Sample Economist’s Report

As the economist’s report is always written after the cost of care expert’s report, we suspect that many CCEs will not have seen very many economist reports. As it may help the CCE to understand what types of information are required for an economist report, and in what format that information should be provided, in the table presented below we provide a sample copy of a cost of care calculation for a hypothetical seven-year old male plaintiff.

In the footnote to the table, we have also provided an example of a typical assumption we would make when a range of replacement times has been provided by the CCE.

The columns in the table have the following interpretations:

Tax creditable expense: “Y” in this column indicates that the item can be claimed as a medical expense for income tax purposes.

Cost including tax: the cost of the item, including all taxes.

Replacement life: This column reports the frequency of expenditure. “0” in this column means that the item is purchased only once (there is no frequency); “1” means that the item is purchased every year; “2” means that it is purchase once every two years, etc. For example, under “Mobility” the “Ankle/foot orthotic (adult)” is to be replaced once every three years; the “Adapted bike,” however, is to be purchased only twice, at ages seven and fourteen.

Starting age: The age at which the item is first to be purchased. As the hypothetical plaintiff is seven years old, most purchases begin at seven. However, it is seen, for example, that many items in this table are not to be incurred until the plaintiff is eighteen.

Ending age: Many of the items are to be purchased only over a portion of the plaintiff’s life. Often, as in this case, the costs are different when the plaintiff is a child than when he/she is an adult, and costs may change again when the plaintiff retires or enters a senior’s facility.

Present value of costs: This is the lump sum that would have to be invested today to provide the plaintiff with sufficient funds to replace the stream of future costs in each row. For example, a “Before/after school, weekend care” expenditure of $56,060.76 per year from age seven to thirteen will cost $309,468. This figure varies according to the annual cost, the duration of the expenditure, the discount rate, and the plaintiff’s life expectancy.

 Multiplier: Assume that the cost of care expert has recommended an expenditure of $1,000 per year for the next ten years, and that the present (lump-sum) value of this cost has been calculated to be $8,300. If that expenditure was to be doubled, to $2,000 per year over the same time span, the present value of the cost would also double, to $16,600. Alternatively, we can represent this by saying that for every $1.00 of annual costs (over this ten-year span), the present value of future costs will be $8.30. Any lump-sum cost can be obtained by multiplying the annual cost by 8.30. The latter figure is called the “multiplier.” It can be used by the court to recalculate the present value of future costs if the court should conclude that the annual costs are different from those recommended by the cost of care expert.

     For example, if the court was to rule that annual before/after school costs were $40,000 (instead of the $56,060.76 reported in the table, the present value would be $40,000 multiplied by the reported multiplier, 5.52, yielding $220,800. [Note: there is a separate multiplier for each starting/ending age combination. Multipliers also differ if a different discount rate or life expectancy is used.]

Sample Cost of Care Calculation for Seven-year-old Plaintiff

 * The cost of care expert recommended that the wheelchair be replaced approximately every three to five years. It was also indicated that once the child’s chair had reached its maximum capacity, it would have to be replaced with an adult chair. For the purposes of our calculations, we have assumed that the chair will require replacement every four years until the plaintiff is eighteen.

We would like to thank Stephen Kuyltjes of Rehab Works, Calgary; Sharon Kaczkowski of Kaczkowski Occupational Therapy, Calgary; and Everett Dillman of International Business Planners, El Paso, Texas, all of whom were kind enough to comment on earlier drafts of this article. We are responsible for any remaining errors or omissions.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

 

The Effect of Incarceration on Future Earnings

by Christopher J. Bruce, Derek W. Aldridge

In personal injury and fatal accident claims, the courts are often required to determine what effect a criminal record would have had on the earnings of the plaintiff. We suspect that most individuals would expect that criminals will have lower wages and higher unemployment rates than the average citizen.

In this paper, we summarise the most reliable research that has been conducted into this question. We divide this summary into four lines of investigation: the impact of incarceration on earnings and employment; the effect of an increase in the duration of incarceration; the determinants of a successful transition from jail to civilian life; and the determinants of the probability of recidivism.

Incarceration

Although the raw data indicate that those who have been incarcerated have lower earnings and higher unemployment rates than those who have no criminal record, research indicates that this is an example of “correlation, not causation.” (For further information on the misuse of statistics in legal proceedings, see Bruce, 2004.) That is, careful analysis of the data have shown that individuals with low earnings and high unemployment rates are more likely to commit (and be convicted of committing) crimes than are those with high earnings and low unemployment rates. Hence, the primary reason that earnings are low among those who have been incarcerated is that those individuals are drawn from a population of individuals who have low earnings, not because the incarceration changed their employment prospects.

Grogger (1995), for example, found that neither arrests nor jail terms had long term effects on the earnings or employment of young men. And Kling (1999) concluded that, for most individuals, incarceration only reduced earnings by 0 to 3 percent, five to eight years after release. The only group for whom incarceration had a significant effect on post-release earnings was white collar criminals (such as accountants and stockbrokers). Similarly, Richey (2015) found that the effect of conviction on earnings was small or zero. Western (2002), however, found that although conviction had no effect on employability, it reduced the rate of growth of earnings by approximately 33 percent. (Note, however, that as rates of growth are often approximately two or three percent per year, a 33 percent reduction implies a reduction in rate of growth of approximately one percent or less.)

Duration of incarceration

A number of recent articles have attempted to determine whether an increase in the length of a jail sentence, holding the severity of the crime constant, has an effect on post-incarceration employment and earnings. One study found that there “…. is no substantial evidence of a negative effect of incarceration length on employment or earnings.” (Kling, 2006) Another found that the length of prison sentence for drug offences had no significant effect on earnings; but that length of sentence had a very significant effect with respect to incarceration for fraud and embezzlement. (Lott, 1992)

Transition from prison into the workplace

A small number of studies have investigated the factors that influence the success of transition out of prison. Typical of these is Visher and Travis (2003) in which the authors found that men with close ties to families and friends made the most successful transitions into the workplace, particularly if they lived with their wives and children. Families appeared to be especially important if they provided emotional support and housing assistance.

Recidivism

Numerous studies – e.g. Gendreau et. al. (1996), Jones (2005), and Motiuk and Vuong (2005) – have concluded that those who have been released from prison are more likely to reoffend if they have experienced high levels of unemployment or job instability, lack a skill or trade, or are drug users. They are also more likely to reoffend the younger they are.

The finding that it is younger individuals who are most likely to re-offend implies that most offenders have left the criminal population by the time they are in their late 20s. One Canadian study (Correctional Service of Canada, 1993), found that, at age 32, the average age at which respondents had committed their last offence was 23. A subsequent study (Ouimet and LeBlanc, 1996), based on interviews with 238 young men who had previously been young offenders, found that whereas more than half had been criminally active between the ages of 18 to 25, only 18 percent had been criminally active after 25.

Summary

The scientific literature suggests that incarceration has a relatively small effect on lifetime earnings. Although those who have been incarcerated earn lower incomes than those who have not been incarcerated, it is primarily because they are drawn from a group that tends to have relatively low earnings, not because the incarceration “causes” low earnings. Further, the data appear to indicate that the likelihood of being convicted and sent to jail decreases as an individual ages. Hence, those 30 and 40 year olds who were incarcerated in their early 20s are not likely to become repeat offenders.

It appears, therefore, that once a plaintiff reaches the age of approximately 25, the best predictors of his future earnings are standard factors like earnings history, education, and occupation. Whether or not that individual has been incarcerated will not add a significant amount of information to the factors that are used to forecast earnings of non-incarcerated individuals.

Sources

  • Bruce, Christopher, (2004) “The Reliability of Statistical Evidence Concerning the Impact of Disability;” Expert Witness, 9(4), http://www.economica.ca/ew09_4p1.htm.
  • Correctional Service of Canada, (1993) “Recidivists tend to be…;” Forum on Corrections Research, 5(3).
  • Gentreau, P. et. al. (1979) “Norms and recidivism for first incarcerates: Implications for programming;” Canadian Journal of Criminology, 1-26.
  • Grogger, J. (1995) “The effect of arrests on the employment and earnings of young men;” Quarterly Journal of Economics, 51-71.
  • Jones, D. (2005) “Offender employment: A research summary;” Forum on Corrections Research, 17(1), 13-20.
  • Kling, J. (1999) “The effect of prison sentence length on the subsequent employment and earnings of criminal defendants;” Woodrow Wilson School Discussion Papers in Economics.
  • Kling, J (2006) “Incarceration length, employment, and earnings;” American Economic Review, 863-876.
  • Lott, J (1992) “Do we punish high income criminals too heavily?;” Economic Inquiry, 583-608.
  • Motiuk, L, and B. Vuong (2005), “Offender employment: What the research tells us;” Forum on Corrections Research, 17(1), 21-24.
  • Ouimet, M., and M. LeBlanc (1996) “Life events in the course of the adult criminal career;” Criminal Behavior and Mental Health, 6(1), 75-97.
  • Richey, J. (2015) “Shackled labor markets: Bounding the causal effects of criminal convictions in the U.S.;” International Review of Law and Economics, 41, 17-24.
  • Visher, C., and J. Travis (2003) “Transitions from prison to community: Understanding individual pathways;” Annual Review of Sociology, 29, 89-113.
  • Western, B. (2002) “The impact of incarceration on wage mobility and inequality;” American Sociological Association, 4, 526-546.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary.

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Are Data from the 2011 Census Reliable?

by Christopher J. Bruce

When estimating future earnings in personal injury and fatal accident cases, financial experts often rely on information provided by the Canadian Census. Of particular importance are data concerning incomes by age, sex, occupation, and education. For example, if a 24 year-old male plaintiff would have been a journeyman carpenter, his potential earnings might be based on average incomes for Canadians with that certification, in the age groups 25-29, 30-34, 35-44, etc.

In the past, these data would have been drawn from a section of the Census known as the “long form.” This portion of the Census survey, which contained much more detailed information than on was on the rest of the Census, was given to only one household out of five. (The remainder of the Census survey asks only basic questions about such demographic factors as age, sex, language, and area of residence.)

For the 2011 Census, however, the government decided to replace the long-form questions with a “National Household Survey (NHS).” Although the 2011 NHS asked the same questions as had the 2006 Census long form, whereas the long form had been mandatory, the NHS was voluntary. The result, as had been expected, was that the percentage of households answering this portion of the survey fell significantly, from 93.8% in 2006 to 77.2% in 2011.This created three statistical problems concerning the reliability of the data (variability in small community data, sample error, and non-response bias). As Statistics Canada had anticipated these problems, however, it took steps to mitigate them, steps that have maintained the reliability of the data that are of value to the courts. Wayne R. Smith, Chief Statistician of Canada, recently wrote an article in which he discussed these steps. [“The 2011 National Household Survey – the complete statistical story,” http://www.statcan.gc.ca/eng/blog-blogue/cs-sc/2011NHSstory. June 4, 2015.] In this article, I summarise Dr. Smith’s discussion.

Variability in small community data

As the sample size of any survey becomes smaller, the data become less and less reliable, due to an increase in variance. In response, Statistics Canada routinely withholds data concerning the smallest communities. In 2011, they withheld the results from 1,100 such communities, up from 160 in the 2006 Census. That is, all of the data reported in 2011 meet the normal statistical requirements for reliability.

Sample error

As the overall size of a sample decreases, there is an increase in what is known as the “sampling error;” that is, from the problem that the average characteristics of the sample differ from the average of the total population. Because Statistics Canada expected a smaller percentage of households to answer the voluntary NHS than had answered the mandatory long form, they anticipated that the total size of the “sample” (the households answering the survey) would be lower in 2011 than in 2006.

To deal with this problem, Statistics Canada increased the number of households who were asked to answer the long portion of the 2011 Census. Whereas one household in five were asked to answer the 2006 long form, one household in three were asked to answer the NHS. The result was that, even though a smaller percentage of households responded to the NHS than had responded to the 2006 long form, the number of households answering the NHS was higher than in 2006, (2,657,461 versus 2,443,507, representing 6,719,688 versus 2006’s 6,136,517).

Although this approach does not correct for all errors, those errors become less and less important as the data are aggregated. Thus, for example, the data for the average income of all carpenters in Alberta are more reliable than for the average income of carpenters in Calgary.

Non-response bias

The most worrisome problem that arises when a survey is made voluntary is that the households who choose to respond to that survey may differ significantly from those who refuse to do so. For example, if those carpenters with relatively high incomes are more likely to respond to the NHS than are those with low incomes, the average incomes reported by the NHS will be biased upwards.

Statistics Canada could not control, ex ante, for the possibility that this would happen. However, they were able, ex post, to investigate whether the respondents to the NHS were representative of the overall groups from which they were drawn – that is, they were able to determine whether the respondents “looked” different from the average.

To make this determination, Statistics Canada was assisted by the fact that they had a considerable amount of information about the respondents to the NHS before those individuals answered the NHS survey. Most importantly, they also had their responses to the short questions on the Census that are mandatory for all Canadians. In addition, they were also able to link the NHS respondents to those individuals’ tax files, immigrant landing data, and the Indian Register.

Using sophisticated statistical techniques they were able to determine that the average respondent to the NHS had very similar characteristics to the average Canadian with respect to age, sex, language, area of residence, income tax, immigration status, and aboriginal status. This finding leads Statistics Canada to conclude that the NHS respondents were, in most cases, representative of the larger population from which they were drawn. And when Statistics Canada was unable to conclude that the individuals who replied to a specific sub-class of questions were representative of the population, the resulting data were not released, or they were released with an accompanying cautionary note.

Summary

To summarise: Although the long-form portion of the 2011 Census was made voluntary, there is sound reason to believe that the data that are of greatest relevance to the calculation of lost earnings can be relied upon.

  1. The information in this article is drawn from a blog written by Wayne R. Smith, Chief Statistician of Canada, entitled “The 2011 National Household Survey – the complete statistical story,” June 4, 2015. This blog can be found at: http://www.statcan.gc.ca/eng/blog-blogue/cs-sc/2011NHSstory.

 

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Cross versus Sole Dependency in Fatal Accident Actions

by Christopher J. Bruce

When a spouse has been killed through the negligence of a third party, the surviving spouse is entitled to damages that would allow him/her to maintain the standard of living that he/she had previously enjoyed.

The determination of this value requires that three steps be taken. First, the potential earning capacity of each spouse must be estimated. Second, a calculation must be made of each spouse’s dependency rate – that is, the percentage of family income that benefitted that spouse. Third, it must be determined whether any monies that had been spent on the deceased by the survivor (and which now do not have to be spent due to the death of the former) should be deducted from the survivor’s loss of dependency. In what is known as the sole dependency approach, that “saving” is not deducted. In the cross dependency approach, the saving is deducted.

In this article, I will use a concept that is fundamental to economic analysis – the rational person assumption – to suggest that basic economic principles favour the use of sole dependency.

I begin by making some simple assumptions about a couples’ earning capacity and dependency rates and use those assumptions to define sole and cross dependency. I then introduce the rational person assumption and provide examples of the use of that assumption in non-fatal accident cases. Finally, I extend the analysis to fatal accident cases and argue the rational person assumption provides support for use of the sole dependency approach.

Assumptions concerning earning capacity and dependency

Statistical analyses suggest that, in a household consisting of a husband and wife, approximately 30 percent of the family’s after-tax income is spent on items such as food, clothing, and transportation that benefit the husband alone; approximately 30 percent is spent on items that benefit the wife alone; and 40 percent is spent on items, such as housing, furniture, and insurance, that benefit both spouses collectively. Each spouse benefits, in total, from 70 percent of family income – 30 percent that benefits that spouse personally – usually referred to as “personal expenses” – and 40 percent that benefits both spouses equally – “common expenses.” The 70 percent figure in this example is known as the individual spouse’s “dependency rate.” [Note that, as both spouses have the same dependency rate, 70 percent, there is a net benefit from marriage.]

Assume that in a childless couple, the husband earns $100,000 per year after taxes and the wife earns $40,000. Based on my assumptions concerning dependency rates, out of the husband’s income, 30 percent, or $30,000, is devoted to his personal expenses, 30 percent, or $30,000, is devoted to his wife’s personal expenses, and 40 percent, or $40,000, to common expenses. From the wife’s income, the comparable figures are 30 percent ($12,000), 30 percent ($12,000), and 40 percent ($16,000), respectively.

Cross and sole dependency defined

Now, assume that the wife has been killed. The sole dependency approach asks: how much of the wife’s future income would have been devoted to expenses that benefitted the husband? The answer in this case is that it is the 30 percent of her income that she spent on items specific to her husband (food, clothing, etc.) plus the 40 percent of her income that she spent on common expenses (housing, furniture, etc.), or $28,000 – which equals the husband’s dependency rate, 70 percent, multiplied by the wife’s (after-tax) income, $40,000. The tortfeasor would be required to pay $28,000 per year until the projected date of the wife’s retirement, discounted to the present.

Proponents of the cross dependency would also calculate the husband’s dependency on the wife’s income, here $28,000. But they would then argue that there is an offset against that loss: the “savings” obtained by the husband because he no longer devotes 30 percent of his income to his wife’s personal expenses. In the example here, as the husband was spending 30 percent of his income on his wife, it is argued that he now benefits from a $30,000 saving as a result of her death. The difference between this $30,000 saving and the $28,000 he has lost, $2,000 per year in total, represents a net benefit to him. He has no claim (for dependency loss) against the tortfeasor.

The “Rational Person” assumption

Which of these approaches is more consistent with the legal principal that plaintiffs are to be returned to the position they would have been in had the negligent action not occurred, restitutio in integrum?

When answering this question, economists rely on an assumption that is fundamental to economic analysis: that individuals act rationally to improve their own welfare. This rational person assumption implies that informed individuals will voluntarily undertake actions only if those actions make them better off (or, at least, no worse off). [Note the similarity to the “reasonable person” doctrine of tort law and to the rationale, in contract law, for maintaining the sanctity of contracts.]

As a simple example of the rational person assumption, assume that individual B is observed to be saving towards the purchase of a lap-top computer. One day, B sees an ad for the computer he likes, at a price of $1,000 (inclusive of all taxes). He checks his bank balance and discovers that he has $1,500. Assume we also observe him use his debit card to buy the desired computer; and, when he gets home, to check his bank balance again, to find that he now has $500.

Can we, as an external observer (with no ability to read B’s mind) conclude that B is “better off?” Economists, employing the “rational person” assumption, argue that B must be better off than if the purchase had not been made: a rational individual will only pay $1,000 for an item if he or she values that item at more than (or equal to) $1,000.

Although it might be argued that B is “worse off” in the sense that he now has $1,000 less than he would have had, that reduction in his finances is at least offset by the fact that he now has a computer that he valued at $1,000 or more.

To put it another way, if an individual was observed to go shopping with the intention of paying $1,000 for a computer, but was prevented from doing so because the store had run out of stock, no professional economist would argue that that individual was now “better off” — because he now has $1,000 that he would otherwise not have had. He is not better off. His preference was observed to be to trade the $1,000 for a computer – that would have made him better off. [Indeed, the rational person assumption suggests that when he is prevented from spending his money the way that he prefers, he is made worse off.]

The Rational Person argument applied to personal injury cases

Before examining how this view of rational behaviour applies to fatal accident cases involving spouses, I first turn to two other classes of tort actions.

In the first of these actions, assume that an individual has been seriously injured in a motor vehicle accident. As a result of this accident, her earning capacity has been impaired to the extent that she will lose $100,000 between now and the time she would have retired. The defendant accepts responsibility for this loss, but counters that offset against this loss is a “gain” that the plaintiff has obtained because of the accident. Imagine that before the plaintiff was injured, she was an active golfer, spending $5,000 a year on green fees, lessons, and equipment. The injuries suffered in the accident, however, are such that she can no longer play golf, thereby “saving” $5,000 per year. Assume also that evidence has been led to suggest that she would have played golf for another 25 years, had she not been injured. Hence, because of her injuries, she will save approximately $125,000 over her lifetime that would otherwise have been spent on golf. The defendant argues that when this saving is deducted from the plaintiff’s lost earnings, the plaintiff is actually $25,000 better off as a result of the accident. The defendant owes nothing to the plaintiff.

Using the assumption of the rational individual, however, it is easily seen why the defendant’s argument in this case is fallacious. Although it is true that the plaintiff will now have $125,000 available to her that she would not have had in the absence of the accident, she now has been denied $125,000 worth of pleasure that golf would have given her. Ignoring the effect of the accident on her earnings, in order for the plaintiff to be left in the same position she would have been in the absence of the accident, she will have to spend sufficient money to replace the value she would have obtained from golf. But this must be at least $125,000: because she would have chosen to spend $5,000 per year on golf in preference to spending it on anything else, $5,000 spent on “anything else” must be of lesser value than that expenditure on golf. That the plaintiff now has $125,000 that she would not have had if she had been allowed to spend it on golf does not make her $125,000 better off. At best, it leaves her in approximately the same position as she would have been in had she been allowed to spend that money. Hence, it is incorrect to suggest that the $125,000 that has been “saved” should be set off against the plaintiff’s loss of earnings.

In the second example of a tort action, assume again that the injuries suffered by the plaintiff in an automobile accident have reduced his lifetime earnings by $100,000. Again, the defendant has accepted responsibility for the accident; but in this case, she argues that as the plaintiff’s daughter was killed in that accident, the plaintiff has been “saved” the costs of raising that child. If those costs have been calculated to be $150,000 over the life expectancy of the child, the defendant argues that the net effect of the accident has been to leave the plaintiff no worse off than he had been in the absence of the accident. There is no loss.

Again, the fallacy of this argument arises because the defendant has implicitly argued that the plaintiff would not have received any benefit from the $150,000 he would have spent on his daughter. But, according to the “rational consumer” assumption, if the plaintiff had chosen to have the daughter and to spend $150,000 on her, in preference to spending that money in any other way, the plaintiff is worse off having $150,000 than he would have been spending that money on his daughter.

The Rational Person argument applied to fatal accident cases

With these cases in mind, consider again the case discussed at the beginning of this article, concerning the death of a wife. It is now seen that when the defendant argues that the cross dependency approach should be applied, what he is actually arguing is that the $30,000 the plaintiff had been spending on his wife had provided him with no benefit at all. Now that those expenditures have been “freed up”, he can spend the money on himself, at a net gain of $30,000. Therefore, the defendant argues that that gain can be set against other losses from the accident – as was argued by the defendants in the cases of the plaintiffs who were asked to set their savings of expenditures on golf or on their child against their losses of income.

But, as in those cases, the rational person assumption suggests that surviving spouses are not better off when they do not “have to” make expenditures on their deceased partners. If they were making those expenditures voluntarily (i.e. rationally), they must have obtained some benefit from that expenditure – indeed, a benefit that exceeded the value from any other purchases that could have been made with the same amount of money. Now that the husband in the example does not “have to” spend $30,000 per year on his wife, he can spend it on himself – clothes, travel, cars, etc. But does that expenditure give him as much pleasure as spending it on his wife? The better argument, I suggest, is that preventing plaintiffs from spending money in the way that they would have chosen cannot make them better off. Hence, it would be inappropriate to deduct any such purported “gains” from plaintiffs ‘other losses.

It is the sole dependency approach that is more consistent with both restitutio in integrum and with the rational person assumption.

Summary

A fundamental assumption in economics is that individuals are rational; and, therefore, that when an individual is observed to make a voluntary choice, it can be concluded that the individual must have expected that choice to make him/her better off (or, at least, no worse off). With respect to fatal accident actions, this implies that if spouses are rational, they must have expected that the decisions they made about spending on one another would make them better off. In this article, I have argued that if this proposition is accepted, the sole dependency approach is preferred to cross dependency.

 

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Cost of Household Services, Alberta 2014: A Survey

by Christopher J. Bruce and Russette S. Pack

The cost of hiring individuals to perform household services such as housecleaning, snow removal, and handyman repairs can amount to a significant percentage of the damages in a personal injury or fatal accident claim. Yet, despite the importance of these costs, reliable estimates of the components of a household services claim are very difficult to obtain. In order to assist the court in this respect, Economica has conducted a number of surveys of household services costs since 1997.

In those surveys, for example, we found that the hourly cost of housecleaners in Edmonton and Calgary rose from approximately $13.50 in 1997, to $25.00 in 2006, and to $30.00 in 2010; and for handymen the rates rose from $24.00 in 1997 to $32.00 in 2006, and then fell to $30.00 in 2010.

As four years have passed since our last survey, and as our experience suggests that rates tend to increase appreciably over time, we have undertaken a survey of providers for 2014. This article summarises our main findings.

I. Housecleaning

Using the internet, we identified five professional agencies (for example, The Clean Team) in Calgary and four in Edmonton that provide house cleaning; and we identified fourteen ads from individuals (usually on Kijiji) in Calgary and seventeen in Edmonton.

In Calgary, the average rate among professional agencies was $34.40 per hour, with a range from $25.00 to $45.00.

The comparable average for Edmonton was $47.75, with a range from $34.00 to $57.00. Among those individuals who advertised on websites such as Kijiji, the average hourly rate in Calgary was $23.85 and in Edmonton was $24.32, (with almost half of the rates at exactly $25.00).

In the smaller cities, almost all of our data came from Kijiji ads. In those cities, the average hourly rates (with numbers of ads in brackets) were: Lethbridge (6), $24.16; Red Deer (7), $22.14; Medicine Hat (5), $24.50; and Grande Prairie (7), $25.00.

II. Handyman (maintenance) services

We obtained the names of handyman services in Calgary and Edmonton primarily from Kijiji. In each case, we attempted to obtain quotes to: “replace several fence boards, clean and repair the gutters, and paint the step rails and trim.” If those rates were not available in the ads, we phoned to obtain them.

The average hourly rate among nine services in Calgary was $31.77; whereas the average in Edmonton, among eight services, was $26.06. In both cities, more than half of the responses fell between $20.00 and $30.00, with the difference in the cities’ averages resulting primarily because a larger number of individuals quoted more than $30.00 per hour in Calgary (four out of nine) than in Edmonton (one out of eight).

III. Lawn care and snow removal

Again, lawn care and snow removal firms were identified from Kijiji ads in Calgary and Edmonton. With respect to lawn care, we asked for a quote on a suburban city lot (4,200 square-foot lot with an 1,800 square-foot, two-story home) with lawn in front and back.

With respect to snow removal, we obtained quotes for a house with a two car driveway, stairs, entry, and a city sidewalk. In all cases, firms quoted either per attendance at the home or per month (i.e. not per hour).

The fifteen lawn care firms in Calgary charged an average of $37.80 per attendance (with seven between $35 and $40) and the ten firms in Edmonton averaged $34.25 (with six at $30).

With respect to snow removal, the six Calgary firms that charged per visit averaged $38.75, whereas the eight that charged a flat rate per month averaged $160.00.

In Edmonton, we identified five firms, all of which charged a flat monthly rate, averaging $142 per month.

IV. Childcare

We identified five methods of providing (commercial) child care: day care, day home, live-in nanny, live-out nanny, and before- and after-school care. We obtained all of our information from various internet sites.

The numbers of day cares and day homes that were contacted in Calgary and Edmonton, and their average monthly fees, are reported in Table 1.

There it is seen that day homes charge approximately $700 to $800 per month for all ages of children; and that day cares charge approximately $1,200 to $1,300 per month for infants and from $900 to $1,200 for other age groups.

The average monthly rate for the twelve live-in nannies we identified in Calgary was $2,300; and for thirteen live-out nannies (also in Calgary) it was $2,518. (These individuals reported hourly rates of $13.08 and $16.55, respectively.) In Edmonton, many nannies only reported hourly rates. Assuming that those rates applied to forty-four hour weeks, the twelve live-in nannies charged an average of $2,053 per month ($11.66 per hour) and the eleven live-out nannies charged $2,464 ($14.00 per hour).

The average monthly rate for before- and after-school care was found to be $430 in Calgary (nine agencies) and $480 in Edmonton (YMCA).

V. Homecare and meal preparation

We were able to identify four agencies in Calgary that provide generalized home care services, such as meal preparation, light housekeeping, grocery and clothes shopping, grooming and dressing, bed-making, and bathing. In each case, we sought a quote for “a relative that had been injured in an accident and was recuperating at home.” The average hourly rate among these agencies was $21.50. In Edmonton, we found four individuals who charged an average of $19.50 per hour.

In addition, CBI Health quoted $29.00 per hour for assisting a relative “who had been injured in an accident and was recuperating at home;” and Alberta Health Service (AHS) indicated that they would provide: in home meal preparation for $25.00-$30.00 per hour; personal care (including bathing and dressing) for $23.00-$30.00 per hour; and twenty-four hour live-in care for $23.00-$27.00 per hour. (Skilled nursing would cost $38.00-$75.00 per hour from AHS).

VI. Hourly rate proposal

Statistics Canada provides data concerning the amounts of time spent on six types of “household work and related activities.” These are: cooking/washing up, house cleaning and laundry, maintenance and repair, other household work, shopping for goods and services, and primary child care.

For the purposes of calculating the costs of household services, in our reports we will combine “cooking/washing up” with “shopping” and evaluate that category at the approximate average rate for home care and meal preparation, $25.00 per hour (up from $20.00 per hour in our 2005 survey, but the same as the rate we obtained from our 2010 survey).

We will combine “maintenance and repair” with “other household work” (a large portion of which consists of “gardening and ground work”) and evaluate the resulting services at the landscaping, snow removal, and handyman services rate of approximately $35.00 per hour (up from $30.00 in 2010).

We will evaluate “house cleaning and laundry” at the rate for housecleaning services. For the purposes of our reports, we propose to use the conservative rate of $30.00 per hour in Calgary and Edmonton, and $25.00 per hour elsewhere (compared to $30.00 and $20.00, respectively, in 2010).

For each of the preceding services, however, we will assume that professionals will be 25 percent more efficient than the plaintiff would have been. Hence, our assumption is that the cost of those services is 25 percent less than the rate that has been quoted per hour.

Finally, we will assume that it costs $1,000 per month to care for each baby (the approximate mid-point of day care and home care costs), $900 to care for each toddler/pre-school child, and $450 per month to provide before- and after-school care for each school-aged child (up from $850, $800, and $400, respectively, in 2010).

For the purposes of quantifying child care costs on an hourly basis, we propose to employ $10.00 per hour.

VII. Discussion

The data discussed in this article raise an important question: if individuals listed on Kijiji charge approximately $25 per hour, why do consumers hire professional agencies at $10 to $15 per hour more than that? We suspect that the answer to this question derives from three factors.

First, agencies may be able to offer a higher quality of service than can private individuals. For example, they might provide training to their employees, use screening interviews to select the most skilled workers, or offer to replace workers who proved to be unacceptable to the client.

Second, it is possible that agencies might be able to complete their tasks more quickly than would private contractors, thereby lowering the effective hourly rate of the former.

Finally, commercial firms may be better able than individual cleaners to develop reputations for reliable service. If a cleaner is sick or otherwise unable to work, a firm can often replace that individual with another employee; whereas if self-employed individuals are unable to meet their commitments, their jobs go undone. Customers may be willing to pay a premium for the more reliable service.

Regardless of the answer to this question, however, the fact is that it would be very difficult to hire, say, a reliable housecleaner in Calgary or Edmonton for less than $25 per hour – and that cost would rise to more than $35 per hour if the client wished to hire a bonded cleaning service.

It should be noted, however, that even if it costs, say, $25 per hour to hire a housecleaner, it does not follow that it will cost $25 to replace one hour of a plaintiff’s time. The reason for this is that professional cleaners may be able to complete more work in an hour than could non-professionals. The best information we have available, for example, suggests that this differential is approximately 25 percent; that is, to replace one of the plaintiff’s hours will require only 0.75 hours of a professional’s time. In this case, the cost of replacing an hour will be $18.75 (= 0.75 × $25). [Note: this argument with respect to the greater efficiency of professional providers applies to all of the other services identified in this report, except child care.]

A further puzzle raised by our findings is that, according to the Alberta Wage and Salary Survey, “light duty cleaners” earned an average of $14.76 per hour in 2013, with a range of $13.76-$16.43, almost $10.00 per hour less than the rates charged by individuals advertising on Kijiji. What is the source of this differential?

One possibility is that the individuals identified by the Survey are working as employees for large cleaning companies and, therefore, have security of employment; whereas those advertising on Kijiji are self-employed, with the attendant uncertainties.

Another possibility is that it is the more productive, reliable individuals who choose self-employment.

Regardless of the answer, our evidence suggests that individual consumers will not be able to hire housecleaners at the wage found in the Alberta Wage and Salary Survey. It is the rates found on Kijiji and on the websites of professional agencies that best reflect the cost to a plaintiff of hiring a housecleaner for an hour.

VIII. Summary

In this article, we have reported the results of a survey of household services providers in Alberta. Two outcomes are very clear. First, it is inappropriate to use a single, hourly rate to evaluate all such services. Whereas child care services cost approximately $10.00-$15.00 per hour, housecleaning services cost more than $25 per hour, and lawn care and snow removal can cost over $35 per visit.

Second, the convention of using $12 to $16 per hour for household services is unsupportable. All of the services that were identified in our survey cost significantly more than that, even after allowing for the greater efficiency of professionals.

Our findings also suggest that it may be inappropriate to rely on the wage rates reported by the Alberta Wage and Salary Survey (or other sources of average wage rates) to estimate the costs of services such as housecleaning. Whereas the wages for that occupation average approximately $15 per hour, the individual housecleaners we identified through Kijiji charged more than $25.00 per hour on average; and housecleaning agencies charged $25.00-$50.00 per hour (more than twice the wage that Statistics Canada reports).

Finally, we are of the opinion that hourly rates for housekeeping services should not be obtained by averaging the figures that have been adopted in previous cases.

We are pleased to note that Madame Justice D. C. Read agreed with our conclusion on this point in her decision in Palmquist v. Ziegler, 2010 ABQB 337, at para [271] (emphasis added):

By using an average of numbers accepted in other cases in order to establish a number used to make an assumption in this case, all of the possible errors, either of the trial judge or of the economists who gave evidence in those cases, are incorporated into the number to be used in this case. Courts rely upon economists to determine what assumptions are reasonable to make and their decisions are only as reasonable as are the assumptions used. I have no means of evaluating the expert evidence that was before those other courts to determine whether or not I accept the assumptions made. It is circular to accept that an average of numbers accepted by another courts has any validity in respect to the issue of what economic assumptions are reasonable for me to make in this case.

To view our previous articles related to the costs of household services (or other articles of interest to personal injury law), please visit our website, www.economica.ca, or call our office at 403-297-0012.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Russette Pack is Economica’s administrative assistant.

The Dependency Rate as a Percentage of After-tax Income: Canada 2008

by Christopher J. Bruce and Kelly A. Rathje

In fatal accident litigation, the plaintiffs are entitled to claim an amount that is sufficient to allow them to maintain the same standard of living as they had enjoyed when the deceased had been alive. In practice, this requires that the court calculate the percentage of the deceased’s  after tax income that would have benefited the survivors directly. In Canada, this percentage is called the dependency rate.

Although most experts conclude that the dependency rate of one member of a couple is approximately 70 percent of the deceased spouse’s (after tax) income; there has recently been some confusion over whether the dependency rate might increase or decrease as family income increases. In particular, some experts have argued that the survivor’s dependency decreases as the deceased’s income increases. For example, whereas the widow of a man with low income might need, say, 80 percent of his income in order to be left in the same financial state as she would have had he lived, the widow of a wealthy man might need only 50 percent.

The purpose of this article is to employ a reliable source concerning  after tax income, expenditure patterns, and savings – the Canadian Survey of Household Spending (SHS) – to investigate this claim. Based on the SHS, we show that the survivor’s dependency rate, in a husband/wife family, does not deviate significantly from 72 percent, regardless of the family’s level of income.

The article is divided into three sections. In the first, we argue that the Canadian data are reliable. Second, we calculate the dependency rate for a surviving wife at each of the five income quintiles. There we will show that that rate does not differ significantly from 72 percent at any of these quintiles. Finally, we comment on the treatment of savings in the calculation of the dependency rate.

We also include an Appendix in which we calculate a dependency rate by category for each of the 17 categories of expenditure in the SHS. [Note: in this article, we do not comment on the question of whether some portion of the survivor’s incomes – the portion they now “save” because they do not “have to” spend it on the deceased – should be set off against the survivor’s loss. The arguments we make here apply equally to both the set-off, or cross-dependency, and sole-dependency approaches.]

I. Survey of Household Spending

The most reliable source of family expenditure data in Canada is Statistics Canada’s Survey of Household Spending (SHS), in which approximately 15,000 families are interviewed. The most recent such survey (for which appropriate data are available) was conducted in 2008. The primary source of information concerning this survey is Statistics Canada’s Spending Patterns in Canada, 2008 (Catalogue No. 62-202-XWE).

The 2008 SHS breaks down gross family income into 18 components: 15 major categories on current expenditures, two categories that reflect future expenditure – “insurance and pension contributions” and “money flows” (where the latter is a measure of net savings) – and one for income taxes. Summary information is provided concerning: number of families in the sample, average family size, number of adults, children, and age of head.

Table 1 provides an example of the type of information that can be drawn from the 2008 SHS. The first column in this table reports the average annual expenditures on each of 17 categories (other than taxes). The second column reports the percentages of total (after tax) income that were devoted to each of these categories.

There are a number of reasons for believing that the SHS data are reliable. First, Statistics Canada makes an effort to collect information from the family head. Second, the data for recurring expenses, such as food and personal care, are collected using a detailed daily diary. Third, all other data are collected through personal interviews taking two to three hours. Finally, Statistics Canada has confirmed that the average incomes reported by respondents to the SHS are consistent with those collected from other sources (such as income tax data) 1.

II. Dependency Rates by Income Quintile

The Appendix to this paper calculates the dependency rate for each of the 17 categories reported in Table 1. This rate is the percentage of the pre-accident expenditures on that category that the surviving spouse will need in order to maintain his or her pre-accident standard of living.

These dependency rates are reported in the second column of Table 2. The rate for each category has been multiplied by the percentage of current consumption devoted to that category, taken from the first column of Table 1, in order to obtain the figures reported in the third column. The latter represent the percentages of pre-accident,  after tax income that the surviving wife will need in order to maintain her pre-accident standard of living.

For example, the first row of Table 2 reports that the average Canadian family spent 12.06 percent of its after tax income on food, and that a widow will need 51 percent of this figure to maintain her pre-accident standard of living. Hence, she now needs 6.15 percent (= 0.51 × 12.06) of the family’s pre-accident income in order to purchase the food that she would have purchased had her husband not been killed.

When similar calculations are made for each of the 17 categories reported in Table 2, and the resulting figures are summed, it is found that the wife will require 72.83 percent of after tax income to maintain her pre-accident standard of living.

Using the same methodology employed to obtain the dependency rate for the average family, we also calculate dependency rates for families in each of the five income quintiles. In Table 3 (shown on the next two pages due to size constraints), we report the findings for each of these calculations, plus data concerning: the incomes of each of these groups and the distribution of their expenses among the 17 expenditure categories.

It is seen there that, before taxes, household incomes vary from a low of $19,179 for the first quintile to a high of $171,237 for the fifth; that income taxes range from 3.44 percent to 24.89 percent of total income; and that savings (as measured by the “money flow” category) range from minus 15.57 percent to plus 17.61 percent of  after tax income.

The most compelling finding in Table 3 is that dependency rates do not vary significantly with gross income, with figures ranging from a low of 72.52 percent for the fourth quintile to a high of 74.18 percent for the first quintile 2. Although this finding may, at first, seem counterintuitive, three factors help to explain it.

First, it is seen in Table 3 that the distribution of expenditures among categories does not vary appreciably among income groups. For example, even in the category with the greatest difference among income groups, shelter, families in the fifth quintile spend only nine percentage points more than do families in the second quintile (28.11 percent versus 18.93 percent). In no other category does percentage expenditure decrease or increase by as much as seven points between the second and fifth quintiles.

Second, because the percentages of expenditures on the 17 categories have to add to 100 percent, every increase in the fraction of income spent on one category must be offset by a decrease in the fraction spent on another. Thus, as long as the dependency rates of the categories that increase are similar to those of the categories that decrease, the average dependency rate across categories will not change.

Finally, our finding that dependency rates do not vary significantly with income depends in part on the assumption that the survivor’s dependency on savings will be the same as her dependency on current consumption – that is, on the assumption that, to maintain her standard of living, the survivor will need the same percentage of the family’s retirement income as she needed of its current income.

If, however, the survivor could only be “made whole” if she was allocated a higher (or lower) percentage of retirement income than current income, then dependency rates would increase (or decrease) as income rose – because high income families devote a higher percentage of their incomes to savings. We discuss this issue in greater detail in Section III.

III. Dependency on Savings

Assume that a husband and wife have family income of $80,000 per year, after taxes, of which they devote $70,000 to current expenditures (that is, to expenditures on food, clothing, shelter, etc.) and $10,000 to savings. Assume also that the wife’s dependency on current expenditures is 70 percent – that is, that she benefits from $49,000 (= 0.70 × $70,000) worth of goods and services each year (during the years in which her husband is working). If her husband is killed, she will require replacement of that $49,000 if her standard of living is to be maintained.

In addition, her husband’s death will deprive her of the benefit she would have received from the (ultimate) expenditure of the $10,000 per year that the couple was saving. In Section II, we assumed that the couple would have spent that money in a manner that was similar to the way in which they were spending their income on current expenditures. Therefore, we would have applied a dependency rate of 70 percent to the $10,000 to determine the loss to the wife.

It appears to us that there are two arguments against use of the latter assumption. First, it may be that, as retired couples have lower incomes than working-age couples, their expenditure patterns will also differ, resulting in different dependency rates. However, as we have found that dependency rates do not vary significantly across income levels (see Section II), this argument is not likely to have a significant effect on the results in Table 3.

Second, it is possible that couples may intend to leave a large portion of their savings either to charity or to their children.

To the extent that charitable donations and bequests are a “public good,” the surviving spouse may need as much as 100 percent of planned donations if she is to maintain her standard of living. For example, if the couple had planned to give $100,000 to their daughter, the surviving wife will not be left “equally well off” if the death of her husband leaves her able to give some amount less than $100,0003.

Assume, for example, that within the highest quintile, couples plan to spend 60 percent of their savings on the purchase of goods and services (when retired), and 40 percent on donations and bequests. If it is assumed that the wife’s dependency on current expenditures is 70 percent and her “dependency” on donations and bequests is 100 percent, her total dependency on savings will be 82 percent (= 0.60 × 70% + 0.40 × 100%), instead of the 73.91 percent we applied to savings in Table 3. In that case, however, her total dependency on after-tax income would increase by less than 1.5 percentage points.

Furthermore, this argument has almost no effect on the dependency rates for couples in the first four quintiles as their savings rates are either very low or negative (implying very small donations and bequests). Thus, once again, adjustment of the assumption concerning dependency on savings has no significant effect on the general conclusion that dependency rates do not vary appreciably with income.

APPENDIX: Dependency Rate by Expenditure Category

The purpose of this Appendix is to calculate the dependency rates for each of the seventeen expenditure categories identified in the Survey of Household Spending.

a) Food: Two steps must be taken in order to determine the dependency with respect to expenditures on food. First, it is necessary to identify the relative consumption levels among family members of different ages and sex. Second, allowance must be made for the fact that economies of scale from bulk buying are lost when one member is removed from the family.

With respect to the first of these calculations, our research indicates that the relative consumption of food, among family members of different ages, can be approximated by the figures in our Table A.1.

For example, if a family is composed of a husband and wife, for every 1.0 “units” of food consumed by the husband, the wife consumes 0.8 units. In this case, the couple consumed 1.8 units of food, of which 44.4 percent (0.8 ÷ 1.8) was devoted to the wife. It is this figure that has been used in the construction of Table 2.

Based on the above, and on the general finding that food costs approximately 10 percent more for a single person than for each member of a married couple due to loss of economies of scale, we conclude that in a family of two adults the dependency would be 51 percent when it is the husband who has died and 61 percent when it is the wife. In a family of four, the dependency would be approximately 76 percent if the husband should die and 83 percent if the wife should die.

b) Shelter: The shelter category consists primarily of payments for rent, mortgage, repairs and maintenance, and utilities, none of which could be expected to be reduced appreciably following the death of a spouse. For this reason, we recommend that the dependency be set at 96 percent. This is the figure that has been entered the second row of Table 2.

c) Household operation: This category consists, principally, of expenses for telephone, child care, domestic services, pet care, household cleaning supplies, paper supplies (e.g., toilet paper and garbage bags), and gardening supplies. Of these, only expenses on telephone and paper products can be expected to vary appreciably with family size. Accordingly, we set the dependency rate at 90 percent for the childless family.

d) Household furnishings: As there is no element of this category on which expenditures would be reduced by the death of a spouse, the dependency is 100 percent.

e) Clothing: The most reliable source of data concerning the division of clothing expenditures among family members is Statistics Canada’s Family Expenditure Survey, 1986. Relying upon that source, we have calculated that a family of two adults and two children (aged five to nine) would require approximately 0.6 adult male units for the boy’s clothing, 0.8 for the girl’s clothing, 1.65 for the wife’s clothing, and 1.00 for the husband’s. Thus, the dependency would be approximately (3.03 ÷ 4.05 =) 75 percent if the husband should die and (2.40 ÷ 4.05 =) 59 percent if the wife should die. In a family of two adults, the equivalent dependencies would be 62 and 38 percent, respectively.

f) Transportation: Approximately 90 percent of transportation is devoted to the purchase, maintenance, and operation of cars and trucks. Thus, the most important determinant of the dependency in this respect will be the number of vehicles owned by the family. If both adults drive but own only one car, the death of one of them can be expected to have little effect on vehicle costs; that is, the dependency would be relatively high.  However, if the family owned more than one vehicle, including one that was used primarily by the deceased, the dependency may be as low as 50 or 60 percent.

For the purposes of illustration, we have assumed in the construction of Table 2 that the family had two cars, giving it a dependency with respect to vehicles of approximately 60 percent. The remaining 10 percent of the transportation budget is devoted to public transportation (including air fares).

Assuming that these expenditures are divided evenly among family members, the total dependency with respect to transportation is 62 percent (= [0.9 × 0.6] + [0.1 × 0.75]) for a four-person family and 59 percent (= [0.9 × 0.6] + [0.1 × 0.50]) for a two person family.

g) Health care: Approximately 30 percent of this expenditure is devoted to health insurance. As premiums generally do not double when family size is increased from one to two, we assume for purposes of illustration that the dependency with respect to health insurance premiums is 60 percent for a two-person family. The remaining 70 percent of the average family’s medical budget is devoted primarily to eye care, dental care, and drug purchases. Lacking any firm data on the distribution of these expenses within the family we shall, for purposes of illustration, assume that they are divided equally. Thus dependency for a two-person family is 53 percent (= [0.30 × 0.6] + [0.70 × 0.5]).

h) Personal care: Personal care includes expenditures on such items as haircuts, hair and makeup preparations, soaps, deodorants, and shaving preparations. The recommended budget developed by the Social Planning Council of Toronto shows that adult females spend approximately 63 percent more than adult males on these expenditures. Hence, if it is the husband who has died, the wife’s dependency is approximately 61 percent.

i) Recreation: Approximately 50 percent of the average family’s recreation budget is devoted to expenditures that may not vary with the size of the family, such as purchases of recreational vehicles and home entertainment equipment. The remaining 50 percent is devoted to admissions to events, purchases of home recreational equipment (such as games and crafts), and purchases of sport and athletic equipment. Assuming that the latter expenses are shared equally among family members, the dependency with respect to recreation proves to be 75 percent (= [0.5 × 1.0] + [0.5 × 0.5]) for a two-person family.

j) Reading: The approximate division of reading is: 35 percent on newspapers, 20 percent on magazines, and 45 percent on books. Assuming that newspaper expenses do not vary by size of family and that one-third of book and magazine purchases are specific to one of the adult members of the family, the dependency with respect to reading proves to be approximately 80 percent (= [0.35 × 1.0] + [0.65 × 0.67]).

k) Education: In the absence of any information concerning the plaintiff family, and recognizing that less than 20 percent of the education expenses listed by Statistics Canada are devoted specifically to young children, the only assumption that can be made with respect to this category is that expenses are divided equally between the two adults if there are no older children in the family. That is, for purposes of Table 2, the dependency is 50 percent.

l) Tobacco and alcohol: As with education, in the absence of specific information about the family and assuming that there are no older children in the family, the dependency for tobacco and alcohol must be set at 50 percent.

m) Games of chance: In the absence of other information, we assume that the couple divides these expenditures equally. That is, the dependency rate with respect to this category is 50 percent.

n) Miscellaneous: Of the expenses listed under Miscellaneous, approximately 70 percent reflect items that would not vary significantly with family size, such as interest on personal loans, purchases of lottery tickets, bank charges, lawyers’ fees, and funeral expenses. Assuming that the dependency with respect to these items is 90 percent and with respect to the remaining items is 50 percent, the total dependency with respect to the miscellaneous category is 78 percent (= [0.7 × 0.9] + [0.3 × 0.5]).

o) Personal insurance payments and pension contributions: Approximately 70 percent of the expenditures in this category are for pension fund payments (primarily the mandatory, government-operated Canada Pension Plan), 15 percent for life insurance premiums, and 15 percent for employment insurance premiums. Thus, the value of the dependency will be determined primarily by the labour force attachments of the adult members of the family and by the number and ages of children.

Consider, first, the life insurance premiums. In a two-adult family, life insurance is normally taken out on the life of the main income earner, with the second family member being the beneficiary.  If either family member dies, the need for such insurance is reduced significantly. That is, the dependency is (approximately) zero.

In a family with children, however, it may be the children who are made the beneficiaries.  Therefore, regardless of which parent has died, the remaining parent can be expected to continue his or her payments to a life insurance scheme.  Indeed, that parent may even increase life insurance coverage to take account of the fact that a further death would leave the children with no parents. In such a case, a 100 percent dependency would appear reasonable.

The value of the dependency with respect to employment insurance contributions will be determined by the employment status of the adult members of the family.  If the deceased was employed and the survivor is not, no contributions will now have to be made to employment insurance.  Therefore, the dependency is zero.  On the other hand, if the deceased was not employed and the survivor is, contributions will be unaffected.  That is, the dependency is 100 percent. And if both adults were fully employed, the dependency will be 50 percent.

Finally, when the family loses the deceased’s contributions to a pension plan, it loses the future consumption it would have enjoyed from that pension. As it is only the spouse, and not the children, who would have benefited from this pension, it is the surviving spouse’s dependency on the couple’s retirement level income that will be relevant.

Applying the technique described in Section II, above, we find that if both members of a couple are over 65, the surviving spouse will have a dependency rate of approximately 73 percent (whether it is the wife or the husband that has died). Hence, if both spouses had been fully employed, the total dependency on the personal insurance and pension contributions category becomes 73.6 percent (= [0.15 × 1.0] + [0.15 × 0.5] + [0.70 × 0.73]) when there are children and 58.6 percent (= [0.15 × 0] + [0.15 × 0.5] + [0.70 × 0.73]) when there are not.

p) Gifts of money and contributions: This category consists of gifts to individuals outside of the family-spending unit – for example to parents and children living in separate households – and of charitable donations. We believe it can be argued that if the wellbeing of the survivors is to be maintained at the pre-accident level, these contributions must also be maintained at the pre-accident level. That is, the dependency with respect to this category is 100 percent.

q) Money flows – assets, loans and other debts: The purpose of this category is to measure households’ net contributions to (or withdrawals from) savings. Its primary components are changes in bank balances, purchases of stocks and bonds, contributions to registered retirement savings plans, and changes in money owed by (or to) the household. To the extent that any money put in to savings will be spent later, the dependency on this category will be the same as the dependency on expenditures that were made while the family members were working, or approximately 74 percent, (see Section II). However, if a significant portion of the household’s financial assets are passed to the couple’s children, through their estate, the dependency on savings approaches 100 percent (as for “gifts and contributions”). For the purposes of the sample calculations reported in Section II, we have assumed that the couple spends all of their savings during their lifetimes. Accordingly, we employ a dependency rate equal to the dependency on current consumption, or approximately 74 percent.

Footnotes:

  1. Personal interview with Danielle Zietsma, Senior Economist, Survey of Household Spending, Statistics Canada, May 31, 2013. [back to text of article]
  1. We repeated the exercise in Table 3 using data for the situation in which it is the wife that had died. The dependency rates for the five quintiles did not change appreciably. They became 74.07%, 72.63%, 71.95%, 71.57%, and 71.56%, from lowest to highest quintile.[back to text of article]
  1. In Ratansi v. Abery (1994), 97 B.C.L.R. (2d) 74 (S.C.) the deceased parents had contributed a substantial portion of their income to their mosque. The court found that it was not “….appropriate or accurate to describe the monies contributed to that institution as ‘income not available for family expenditure’.” Accordingly, the dependency of the surviving children on this portion of their parents’ income was found to be 100 percent.[back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

Implied Rates of Return on Structured Settlements

by Derek Aldridge & Christopher Bruce

The purpose of a lump sum award in a personal injury or fatal accident case is to provide a fund that, when invested, will generate a stream of benefits equal to the plaintiff’s future stream of losses. One method of generating such a stream would be to purchase a life annuity. This, for example, is what is anticipated by Section 19.1 of the Judicature Act (RSA 2000) when it provides that:

(2)  On application by any party to a proceeding, the Court may order that damages awarded be paid in whole or in part by periodic payments…

This type of periodic payment has come to be known as a structured settlement annuity. Such annuities are sold by insurance companies. When calculating the price it is going to charge for an annuity, the insurer determines how much it would have to invest, at current interest rates, in order to generate a stream of income at least equal to the required periodic payments. For example, if it had promised to pay $10,000 per year indefinitely , and the rate of interest that it thought it could earn was 10 percent, it would charge at least $100,000 – as $100,000, invested at 10 percent per year, would generate a stream of income of $10,000 per year.

Conversely, therefore, if we observe the lump sum that an insurance company charges for an annuity that promises a specified stream of payments, we can calculate the rate of interest that the insurance company expects to obtain on the investment of that sum. For example, if it was observed that the company had charged $100,000 for a periodic payment of $10,000 per year (indefinitely)¹, we would be able to calculate that the rate of return it expected to obtain on investment of that $100,000 was at least 10 percent.

We have used this principle to calculate the rate of return that insurers expect to obtain on a series of standard structured settlements. By contrasting these rates of return with the rates that Economica has been using, we can check whether Economica’s rates are consistent with those that sophisticated investors – insurance companies – expect to earn on low-risk investments.

With the assistance of Heber Smith, of Smith Structured Settlements (www.structuredsettlements.ca), in August 2011 we obtained quotes on an annuity that provided payments of $1,000 per month to a male plaintiff. These quotes were for

  • three different ages of plaintiffs: 20, 35, and 50;
  • two different termination dates: the plaintiff’s age 60 and his age of death; and
  • two different assumptions concerning inflation indexation: one in which the insurer increased the annual payment each year by the rate of consumer price inflation and one in which the payment was increased each year by a fixed 2 percent.

We report the quotes that we obtained for twelve different scenarios in columns 6 and 8 of the table below. As an example of how to read this table, the $127,064 figure in column 6 of the first row in the table, indicates that we were quoted a price of $127,064 to purchase an annuity that paid $1,000 per month, increasing at the rate of consumer price inflation, from the plaintiff’s age 50 to his age 60. Similarly, it is seen from column 8 of the first row that that annuity would have cost $121,255 if the payments had been adjusted by 2 percent per year instead of by the prevailing rate of inflation. (If we assume that insurers believe that inflation will be 2 percent on average, the difference be $5,809 difference between columns 6 and 8 in the first row is a “premium” the insurer charges to compensate it for taking the risk that inflation might prove to be higher than 2 percent.)

The comparable figures in columns 6 and 8 of the third row of the table report the cost of an annuity that extends to the end of the plaintiff’s life, instead of to age 60 (as in the first row). The figures in the third row would be relevant if an annuity was being purchased to pay for costs of care, instead of for loss of earnings (first row). The remaining rows in the table report the costs of annuities paying $12,000 per year to a 20-year old and a 35-year old.

Given the quotes reported in columns 6 and 8, we were able to calculate the real rate of interest (interest rate net of a two percent expected rate of inflation) the insurance company was expecting to receive from investment of each annuity. These rates are reported in columns 7 and 9, with the figures in column 7 referring to the quotes in column 6 and the figures in column 9 referring to the quotes in column 8. As an example, the figure of -0.95% in column 9 of the first row indicates that the insurance company anticipated that it would receive a nominal interest rate of approximately 1.05% (i.e. 1.05% nominal interest – 2.00% inflation = -0.95% real rate of interest, or discount rate).

Of the twelve discount rates reported in the table, only one – the 2.10 percent rate of return in column 9 of the second row – exceeds the lowest rate used by Economica, as reported in Table 2 of the first article in this newsletter – 1.80 percent on investments of less than four years; and most of the remaining discount rates are significantly lower than the rates that we recommend.

The result is that the present discounted values quoted by insurance companies for the purchase of structured settlements are considerably higher than the comparable values that would have been calculated by Economica. The latter values are reported in column 4 of the table. It is seen in column 4 of row four, for example, that whereas Economica would have calculated that a plaintiff would need $277,538 to replace $12,000 per year from age 20 to age 60; the quote we received for a structured settlement was $506,890 – 82.6 percent more.

The differentials are even greater if we use the discount rate that some other expert economists have recommended – 3.50 percent. In the fourth row of column 5, for example, we report that the present value of $12,000 from age 20 to age 60 would be $252,895 if 3.50 percent is used – less than half of the $506,890 that we were quoted for a structured settlement.

To conclude: in every case, the present values that we would estimate using our discount rate assumptions are considerably lower than the actual cost that a plaintiff would incur if he were to buy an annuity to fund his future losses. This is very strong evidence in support of the claims that we have made over the last several years that our discount rate approach is a conservative one. Based on the costs to purchase structured settlement annuities, and the plaintiff’s ability to demand that his/her loss be funded using this “periodic payment” approach (given Section 19.1 of the Judicature Act), it follows that any reasonable change to our discount rate approach would be to use lower rates, not higher (as some other experts have argued).

Acknowledgment

As noted above, Heber Smith, of Smith Structured Settlements generously provided us with quotes on various annuities which we used in the creation of this article. On previous cases, we have worked together with Mr. Smith when the plaintiff’s lawyer chose to argue that damages should be satisfied by periodic payments (in accordance with Section 19.1 of the Judicature Amendments Act), rather than a conventional present value. An advantage of having future losses assessed in this manner is that it removes the subjective nature of opinions concerning the discount rate. Instead of relying on opinion concerning the rate of return that a plaintiff will earn on his or her investments, we can determine precisely how much it will cost the plaintiff to purchase annuities to fund the future losses.

Smith Structured Settlements serves the personal injury community as an annuity brokerage specializing in the preparation of fee-based Section 19.1 damages reports. Should you wish to investigate such an option they may be reached at www.structuredsettlements.ca.

 

 

Footnote:

  1. Of course, structured settlements never continue indefinitely. We use this example because of its mathematical simplicity. [back to text of article]

The Discount Rate Simplified

by Christopher Bruce, Laura Weir, Derek Aldridge, and Kelly Rathje

In every personal injury or fatal accident case in which the plaintiff’s loss continues into the future, it is necessary to calculate the rate of interest at which the damages will be invested. This interest rate is commonly called the discount rate, and it is calculated as the nominal (or observed) rate of interest net of the expected rate of price inflation.

As Alberta has no mandated discount rate, the determination of that rate is left to the courts. In this article, we propose to offer a simple technique for identifying this rate.

We proceed in two steps. First, we discuss the criteria that we believe must be met when selecting the discount rate. Second, we apply these criteria to the relevant data, to make that selection. In a separate article following this one, Derek Aldridge and Christopher Bruce contrast the rates that we propose with those that are available on structured settlements.

1. Criteria

The first step in selecting a discount rate is to recognise that the plaintiff is expected to invest his or her award in such a way that the stream of income generated from that award will exactly reflect the stream of losses that the plaintiff has suffered. If the plaintiff has lost $50,000 per year for twenty years, investment of the lump-sum award should produce $50,000 per year, with the principal being exhausted by the end of the twentieth year.

As this stream of investment income is intended to replace a significant portion of the plaintiff’s lifetime earnings, the courts have ruled that the lump-sum should be invested in low-risk financial instruments. Hence:

The discount rate must be based on an investment portfolio that is of low risk.

Although this requirement does not mean that the plaintiff must put all of his or her award into government bonds or guaranteed investment certificates (the lowest-risk investments available), we argue that the interest rate available on those investments provides the most reliable indicator of the rate of return required by the courts.

The plaintiff may well include in his/her portfolio non-government or non-guaranteed investments, such as corporate bonds, mutual funds, and blue chip stocks; but, that the returns on such investments are higher than those obtained from government bonds results primarily from the higher level of risk associated with them – as was seen with devastating results in the post-2008 stock market crash.

The difference between the rate of interest on a government bond or a GIC and, say, a corporate bond is a measure of the compensation that investors demand for accepting a higher degree of risk on the latter investment than on the former. Once that level of “compensation” is deducted, the net, risk-free, interest rate is approximately the same on both. Hence:

The rates of return on Government of Canada bonds and GICs represent reliable indicators of the rate of interest sought by the courts.

Once it has been decided that it is government bond and GIC rates that are to be used, it is necessary to select from among the various options that are available to the plaintiff. Financial advisors recommend that, in order to reduce risk, investors should purchase a mix of bond durations. In that way, if interest rates should rise, investors can sell their short-term bonds and purchase newly-issued bonds at the higher rates; and if interest rates should fall, although investors will have to accept reduced interest rates on any new investments, they will still experience relatively high rates on their long-term (locked-in) investments. Hence:

Plaintiffs should purchase a mix of short-, medium-, and long-term investments.

If the duration of the plaintiff’s loss is less than ten years, the plaintiff will minimize risk by purchasing investments that have durations that mature on the dates on which the losses are incurred. For example, a one-year bond might be purchased to replace the loss one year in the future, a two-year bond to replace the loss two years from now, etc. Hence:

For losses that will occur in the next ten years, the relevant interest rate for any year is the rate of interest on a Government of Canada bond (or GIC) that has a term equal to that number of years.

But if the plaintiff’s loss extends for more than ten years, it will be wise to adopt an investment strategy in which bonds are purchased for shorter terms than the duration of the loss, and then re-invested periodically. To replace a loss twenty years from now, for example, the plaintiff might purchase five-year bonds today and re-invest the returns every five years until the funds were needed. If a similar practice is followed for every duration of loss, the risk that interest rates will rise or fall, relative to what is expected at the time of the initial investment, will be minimised.

Such a strategy, of rolling over short-term investments in order to generate a long-term return, means that the effective discount rate over the term of the investment will be determined not only by the rates that are available today but also by rates that will become available in the future. Thus, the court must predict what those future rates will be.

Contrary to what many experts argue, this prediction can be made simply and with confidence: the most reliable prediction of the rate of interest that will prevail in the long-run is that it will equal the rate of return currently available on long-run bonds. For example, if the current rate on 15-year government bonds is 3.0 percent, the best prediction of the rate of return that will prevail over the next fifteen years is 3.0 percent.

The argument for basing the prediction on this rate can most easily be understood by showing that the contrary cannot be true. For example, it might be argued that “as interest rates are unusually low today, it can be expected that they will eventually rise above current rates.” If this argument is correct, then individuals who wished to invest their funds for long periods of time (for example, individuals who are saving for their retirement) would not purchase long-term bonds today – they would purchase short-term bonds while waiting for interest rates to rise, and then purchase bonds at the new, higher rates once the interest rate had risen.

But if investors behaved this way, the demand for long-term bonds would decrease; and when demand for a bond decreases, its interest rate rises. (Issuers have to raise the rate of return in order to attract investors.) That is, if investors predict that the long-term interest rate will exceed the rate currently available on long-term bonds, they will act in such a way as to drive up the interest rate on long-term bonds. A bond rate that is less than the expected rate cannot be maintained.

Similarly, if investors believed that interest rates were about to fall, they would sell their short-term bonds and purchase long-term. But this would decrease the demand for short-term funds, driving up short-term interest rates, and increase the demand for long-term funds, driving down long-term interest rates.

In short, if the rate of interest that is currently available on long-term bonds is different from the rate that investors expect will prevail in the future, the long-term bond rate will change “towards” the rate that investors predict. As a result, the interest rate available on long-term bonds will always adjust until it equals the rate that investors predict will prevail in the long run. And, as investors have a strong incentive to make correct predictions about the bond market, it is likely that their predictions are the best that are available. Hence, we conclude that:

The best predictor of the rate of interest that will prevail in the long-run is the rate of interest that is currently offered on long-term bonds.

Finally, as we noted in the introduction to this article, the discount rate is found by netting out the forecasted rate of price inflation from the observed nominal rate of interest. Hence, before the discount rate can be determined:

The long-run rate of price inflation must be forecast.

Fortunately, there is a clear consensus that the long-run rate of inflation in Canada will be two percent. This consensus has developed because, since the early 1990s, the Bank of Canada has not only set two percent as its long-run target, it has both met that target and expressed satisfaction with the results of its policy.

That participants in the “money markets” have come to accept that the Bank will achieve this goal over the long-run is seen in two surveys of business leaders that have been conducted annually since 1994. Consistently, respondents have reported that they expect the long-run rate to be 2.0 percent. Indeed, not only has the average, expected rate been 2.0 percent in most years that the surveys were conducted, the variation of responses “around” 2.0 percent has decreased continuously. Hence:

There is a strong consensus that, in the long run, the rate of inflation will average 2.0 percent in Canada. Hence, the discount rate can be found by reducing the forecasted nominal rate by 2.0 percent.

2. Data

In Figure 1 and Table 1 we report the annual rates of return that have been available since 1995 on five Government of Canada bonds: 2-, 5-, and 10-year bonds, long-term bonds (an average of bonds with a maturity date longer than 10 years), and “real rate of return” bonds (bonds whose rates of return are stated net of inflation). It is seen there that both nominal and real interest rates on Government of Canada bonds have decreased almost continuously since the Bank of Canada introduced its policy of targeting a two percent rate of inflation. Whereas real interest rates were between 4.5 and 7.5 percent in 1995, they have fallen below one percent on most bonds, and even below zero percent on some, in recent years.

 

 

What these figures indicate is that investments in government bonds are unlikely to provide real rates of return above zero percent over the next five years; that bonds of five to ten year durations are unlikely to produce rates in excess of 1.0 percent; and that the market expects long-term real interest rates on government bonds to be less than two percent.

Nevertheless, in recognition of the fact that current rates are at a historical low, we have left our assumed rates at the same values we have employed for the past five years. Those rates, which we report in Table 2, are: 1.8 percent per year on funds invested for three years or less; rising in equal increments to 3.0 percent per year on funds invested for more than fifteen years.

 

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

Laura Weir is a consultant with Economica and has a Bachelor of Arts in economics (with a minor in actuarial science) and a Master of Arts degree from the University of Calgary.

The Cost of Household Services, Alberta, 2010: A Survey

by Amelia Lamb and Christopher Bruce

In 2005, Economica conducted a survey of the cost of obtaining household services (see The Expert Witness, Vol. 11, No. 2, Summer 2006). At that time, we found that housecleaners in Calgary and Edmonton charged approximately $25.00 per hour; and that handymen charged approximately $33.00 per hour.

Since that time, we have estimated the current costs of household services by increasing the 2005 estimates by the intervening rate of inflation in Alberta. This implies, for example, that our estimate of the cost of housecleaners was approximately $27.50 per hour in 2010.

Increasingly, however, we have become aware that our estimates differ from the rates that prevail in Alberta, particularly in Calgary and Edmonton. The informal evidence available to us suggests, for example, that many housecleaners now charge more than $30 per hour.

For this reason, in late 2009 and early 2010 we conducted a new survey of household costs. In this survey, we obtained housecleaning, handyman, landscaping and snow removal, child care, and home care/meal preparation rates from a large sample of agencies and individuals in both Calgary and Edmonton, and housecleaning rates for smaller samples in Lethbridge, Grande Prairie, Red Deer, and Medicine Hat. We report the results of that survey in this article.

1. Housecleaning

Using the internet, we identified five professional agencies (for example, Molly Maid) in Calgary and four in Edmonton that provide house cleaning; and we identified nineteen Kijiji or Craigslist ads (usually from individuals) in Calgary and twenty-five in Edmonton. In each case, we attempted to obtain an hourly rate to clean a 1600 square foot, two story house, assuming there were no pets and that the cleaner would not be responsible for the basement.

In Calgary, the average rate among professional agencies was $36.63 per hour, with a range from $24.00 to $45.00. The comparable average for Edmonton was $34.50, with a range from $20.00 to $41.25. Among those who advertised on Kijiji or Craigslist, the average hourly rate was $23.76 in Calgary and $23.44 in Edmonton, (with over seventy percent of the rates falling between $20.00 and $25.00).

In the smaller cities, all of our data came from Kijiji or Craigslist ads. In those cities, the average hourly rates (with numbers of ads in brackets) were: Lethbridge (16), $20.81; Red Deer (7), $20.00; Medicine Hat (4), $23.75; and Grande Prairie (7), $18.71.

An important question is raised by the deviation between the rates charged by professional services and those by individuals: if individuals charge, say, $20 to $25 per hour, and agencies charge $30 to $40 per hour, why do clients hire the professional firms?

We suspect that the answer to this question derives from three factors: First, agencies may be able to offer a higher quality of service than can private individuals. For example, they might provide training to their employees, use screening interviews to select the most skilled workers, or offer to replace workers who proved to be unacceptable to the client.

Second, it is possible that agencies might be able to complete their tasks more quickly than will private contractors, thereby lowering the effective hourly rate of the former.

Finally, commercial firms may be better able than individual cleaners to develop reputations for reliable service. If a cleaner is sick or otherwise unable to work, a firm can often replace that individual with another employee; whereas if self-employed individuals are unable to meet their commitments, their jobs go undone. Customers may be willing to pay a premium for the more reliable service.

Regardless of the answer to this question, however, the fact is that it would be very difficult to hire a reliable housecleaner in Calgary or Edmonton for less than $20 per hour – and that cost would rise to more than $30 per hour if the client wished to hire a bonded cleaning service.

2. Handyman

We obtained the names of handyman services in Calgary and Edmonton from Kijiji and Craigslist. In each case, we attempted to obtain quotes to: “replace several fence boards, clean and repair the gutters, and paint the step rails and trim.” If those rates were not available in the ads, we phoned to obtain them. The average hourly rate among twenty-six services in Calgary was $24.88; whereas the average in Edmonton, among twenty-one services, was $29.24. In both cities, approximately half of the responses fell between $20.00 and $30.00, with the difference in the cities’ averages resulting primarily because a larger number of individuals quoted less than $20.00 per hour in Calgary (nine out of twenty-six) than in Edmonton (two out of twenty-one).

3. Lawn care and snow removal

Again, lawn care and snow removal firms were identified from Kijiji and Craigslist ads in Calgary and Edmonton. With respect to lawn care, we asked for a quote on a suburban city lot (4200 sq ft lot with an 1800 sq ft two story home) with lawn in front and back. With respect to snow removal, we obtained quotes for a house with a two car driveway, stairs, entry and a city sidewalk. In all cases, firms quoted either per attendance at the home or per month (i.e. not per hour).

The twenty-six lawn care firms in Calgary charged an average of $29.71 per attendance (with the majority between $25 and $35) and the thirteen firms in Edmonton averaged $36.15 (with the majority between $30 and $40). With respect to snow removal, the six Calgary firms that charged per attendance averaged $26.67, whereas the five Edmonton firms averaged $33.80. One Calgary firm charged a flat rate of $100 per month and one charged $140 per month.

4. Child care

We identify five methods of providing (commercial) child care: day care, day home, live-in nanny, live-out nanny, and before- and after-school care. We obtained all of our information from various internet sites.

The numbers of day cares and day homes that were contacted in Calgary and Edmonton, and their average monthly fees, are reported in Table 1. There it is seen that day homes charge approximately $650 to $700 per month for all ages of children; and that day cares charge approximately $1,000 per month for infants and from $750 to $900 for other age groups.

 

The average monthly rate for the thirteen live-in nannies we identified in Calgary was $1,763; and for thirteen live-out nannies (also in Calgary) the rate was $1,683. In Edmonton, many nannies reported hourly rates. Assuming that those rates applied to forty-hour weeks, the ten live-in nannies charged an average of $1,770 per month and the eleven live-out nannies charged $1,912.

The average monthly rate for before- and after-school care was found to be $401 in Calgary and $415 in Edmonton.

5. Home care & meal preparation

We were able to identify four agencies in Calgary that provide generalized home care services, such as meal preparation, light housekeeping, grocery and clothes shopping, grooming and dressing, bed-making, and bathing. In each case, we sought a quote for “a relative that had been injured in an accident and was recuperating at home.” The average hourly rate among these agencies was $24.81.

In Edmonton, we found only one agency (We Care), which charged $27.75 per hour. However, we also identified two individuals on Kijiji, who charged $14.00 per hour and $15.00 per hour, respectively.

 

6. Summary

In this article, we have reported the results of a survey of household services providers in Alberta. Two outcomes are very clear. First, it is inappropriate to use a single, hourly rate to evaluate all such services. Whereas child care services cost approximately $5.00 per hour per child (assuming that nannies care for two children on average), housecleaning services cost more than $25 per hour, and lawn care and snow removal can cost over $30 per visit.

Second, the convention of using $12 to $16 per hour for household services is insupportable. All of the services that were identified in our survey either cost significantly less that that – for example, childcare – or significantly more – for example, housecleaning, lawn care, and handyman services.

These findings strongly support the view that hourly rates for housekeeping services should not be obtained by averaging the figures that have been adopted in previous cases. We are pleased to note that by Madame Justice D. C. Read agreed with our conclusion on this point in her decision in Palmquist v. Ziegler, 2010 ABQB 337, at para [271] (emphasis added):

By using an average of numbers accepted in other cases in order to establish a number used to make an assumption in this case, all of the possible errors, either of the trial judge or of the economists who gave evidence in those cases, are incorporated into the number to be used in this case. Courts rely upon economists to determine what assumptions are reasonable to make and their decisions are only as reasonable as are the assumptions used. I have no means of evaluating the expert evidence that was before those other courts to determine whether or not I accept the assumptions made. It is circular to accept that an average of numbers accepted by another courts has any validity in respect to the issue of what economic assumptions are reasonable for me to make in this case.

Our findings also suggest that it may be inappropriate to rely on the wage rates reported by Statistics Canada to estimate the costs of services such as housecleaning. Whereas the wages for that occupation average approximately $15 per hour, the individual housecleaners we identified through Kijiji and Craigslist charged more than $22.00 per hour on average; and housecleaning agencies charged more than $30 per hour (more than twice the wage that Statistics Canada reports).

7. Proposal

Statistics Canada provides data concerning the amounts of time spent on six types of “household work and related activities.” These are: cooking/washing up, house cleaning and laundry, maintenance and repair, other household work, shopping for goods and services, and primary child care. For the purposes of calculating the costs of household services, we propose to combine “cooking/washing up” with “shopping” and evaluate that category at the approximate average rate for home care and meal preparation, $25.00 per hour (up from $20.00 per hour in our 2005 survey).

We will combine “maintenance and repair” with “other household work” (a large portion of which consists of “gardening and ground work”) and evaluate the resulting services at the landscaping, snow removal, and handyman services rate of approximately $30.00 per hour (down from $32.00 in 2005).

We will evaluate “house cleaning and laundry” at the rate for housecleaning services. For the purposes of our reports, we propose to use the conservative rate of $30.00 per hour in Calgary and Edmonton, and $20.00 per hour elsewhere (compared to $25.00 and $20.00, respectively, in 2005).

Finally, we will assume that it costs $850 per month to care for each baby (the approximate mid-point of day care and home care costs), $800 to care for each toddler/pre-school child, and $400 per month to provide after-school care for each school-aged child (up from $700, $600, and $275, respectively, in 2005).

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Alternatives to the Minor Injury Regulation

by Christopher Bruce

This article first appeared in the summer 2009 issue of the Expert Witness.

Introduction

Between 2001 and 2003, average automobile insurance premiums for “all coverages” increased in Alberta by 33.2 percent, from $563 to $750. (See Bruce and Strauss, 2008.) In response to the public outcry that followed this increase, the Government of Alberta sought a method for constraining the growth of premiums. Accordingly, in October, 2004, it introduced the Minor Injury Regulation (MIR), which set a $4,000 limit on non-pecuniary damages for “minor” injuries.

As the MIR has been the subject of legal challenges, however, it is possible that the government may wish to consider alternative methods for reducing automobile insurance premiums. The purpose of this article is to canvass a number of techniques that have been suggested to achieve this by reducing the number and severity of accidents.

Specifically, I will survey the academic literature concerning the effects that the following policies can be expected to have on average claims costs: (i) mandatory fines for “driving under the influence” (DUI) offences; (ii) insurance surcharges following either DUI or “chargeable accident” events; (iii) increases in the minimum drinking age; (iv) a ban on driver use of cell phones; (v) mandatory use of alcolocks; and (vi) introduction of in-vehicle data recorders.

1. Mandatory DUI fines

A number of U.S. states have introduced mandatory jail terms and/or mandatory license revocation for first DUI offences. Both Sloan et. al. (1994) and Wagenaar et. al. (2007) found that these rules were associated with statistically significant reductions in numbers of fatal accidents. Nevertheless, both studies found that the absolute numbers of accidents avoided were small. The Wagenaar study, for example, found that the introduction of these mandatory measures implied that the number of individuals killed by drivers with blood alcohol content over 0.08 was approximately 13 per year per state ? a number that was worth achieving, but which would not reduce accident premiums by a significant amount.

2. Insurance surcharges for DUI and “chargeable accident” offences

Sloan et. al. (1994) also found that, among drivers over age 21, the imposition of a “substantial” premium surcharge for DUI or chargeable accidents led to fewer fatalities. The size of the surcharge, however, had to be in excess of 50 percent before it had a significant impact.

3. Raising the minimum drinking age

In 1984, the federal government in the United States began to use offers of highway funding to induce states to raise their minimum legal drinking ages (MLDA) to 21. A large number of statistical studies have been conducted to determine the effects that this policy has had on alcohol consumption among drivers in the 18 to 22 year-old age group; and on alcohol-related traffic accidents caused by drivers in these groups.

In a survey of 241 empirical analyses of MLDA that had been conducted prior to 2001, Alexander Wagenaar and Traci Toomey (2002) found that the “? preponderance of evidence?” suggested that an increase in the minimum legal drinking age was associated with a reduction in both the level of alcohol consumption among young people and the number of traffic crashes attributed to them.

Recently, Carpenter and Dobkin (2009) confirmed that MLDA laws had had a significant effect on the consumption of alcohol. 19 and 20 year-olds, for example, consumed between 11 and 21 percent less than comparable 21 year-olds. Furthermore, this reduction in consumption was associated with a 15 percent reduction in the vehicle-related mortality rate.

Similarly, Fell et. al. (2008) found that the introduction of the MLDA had resulted in an 11 percentage reduction in the ratio of drinking to non-drinking drivers aged 20 or younger who were involved in fatal car crashes. (That is, among those who were involved in fatal accidents, a smaller percentage had been drinking.) Furthermore, they also found that the most important deterrent to underage drinking was enforcement of strict rules against the use of false ID.

4. Restricting driver use of cell phones

Although it appears that most members of the public are convinced that driver use of cell phones increases the risk of accidents, it is difficult for researchers to obtain objective evidence concerning this issue.

The earliest studies, which investigated driver behaviour under laboratory conditions, found that driver reaction time was slowed when using cell phones. (McCartt, et. al. (2006).) But, as researchers were concerned that laboratory behaviour might not translate into driving behaviour under actual traffic conditions, innovative techniques were devised to draw connections between cell phone use and accident rates.

One technique, employed by Kolko (2009), was to correlate state-level data on mobile phone ownership with “hands-free” laws and traffic fatalities. He found that increased mobile phone ownership was associated with an increase in the number of traffic fatalities, “but only in bad weather or wet road conditions” (p. 21). He also found some evidence that hands-free laws reduced fatalities, but concluded that the effect was only minor.

A study conducted in Toronto (Redelmeier and Tibshirani, 1997) used a technique called case-crossover design to extract the effect of cell phone use on accident probabilities in real world applications. They obtained the cell phone records of approximately 700 drivers who had been involved in accidents that had caused “substantial” property damage, but that had not caused personal injury. Using these records, they were able to compare the degree of cell phone use of those drivers in the 10 minutes prior to the accidents with the use rates in comparable 10 minute periods on previous days.

If cell phone usage had no effect on accident activity, the researchers would have found that the same percentage of drivers were using their cell phones on the (previous) days when they did not have accidents as were using their phones on the days that they reported accidents. What Redelmeier and Tibshirani found, however, was that when drivers used a cell phone, the risk they would have an accident was approximately four times as high as when they did not use a phone. Significantly, they concluded that this risk was “?similar to the hazard associated with driving with a blood alcohol level at the legal limit.” (p. 456) They did not find, however, that the risk of an accident was lowered if drivers used a hands-free phone.

A similar, case-crossover design was subsequently used in Western Australia (McEvoy, et. al., 2005) to investigate approximately five hundred drivers who had been involved in automobile crashes that necessitated attendance at hospital. Using cell phone logs, that study confirmed the Toronto study’s finding, that drivers who had used a cell phone within ten minutes before a crash were four times more likely than non-users to have been involved in a serious crash.

In a Vancouver study (Wilson, et. al., 2003), observers stationed at street corners determined whether drivers were using cell phones. If they were, their license plate numbers were recorded, thus allowing researchers to compare cell phone use with Insurance Corporation of British Columbia records concerning automobile insurance claims. It was found that those drivers who had been observed to be using cell phones were significantly more likely than the average driver to have made at least one “at-fault” crash claim in a previous four year period. This finding was much stronger for female drivers than for male.

All of these studies shared the problem that there had been no direct observation of the drivers at the time that the accident occurred. To resolve this issue, the U.S. National Highway Traffic Safety Administration (NHTSA) fitted approximately one hundred cars with both video cameras ? to record both the driver’s actions and the events on the road immediately around the vehicle ? and electronic sensors ? to measure such aspects of the automobile’s actions as speed, acceleration, deceleration, and sudden turns.

The in-car video recorders were able to monitor the drivers’ cell phone use and the degree of their attentiveness to the road. The remaining video recorders could record traffic conditions; while the electronic recorders could measure the driver’s responses to external events.

After observing each car for more than a year, researchers were able to conclude that the actions of (i) dialing a hand-held device and (ii) talking/listening to a hand-held device each contributed to 3.6 percent of all crashes and near-crashes. (NHTSA, 2006: p. 32) The sum of these two figures, 7.2 percent, is approximately equal to one third of the effect of driving while moderately or severely drowsy.

5. Alcolocks

The Swedish government has been experimenting with the use of “alcolocks” to reduce driving while intoxicated (DWI). These are instruments that lock a car’s ignition until the driver has blown into an alcohol-measuring device, (and recorded an alcohol level below the maximum permissible). In one experiment, Swedish drivers who had been convicted of DWI were enrolled in an alcohol ignition interlock programme (AIIP) for two years. Bjerre and Thorsson (2008) found that participants in the AIIP were more likely than non-participants to qualify for full reinstatement of their drivers’ licenses at the end of the two-year period; and that they were less likely to be in traffic accidents or to be charged with DWI offences after that period.

Alcolocks could be used to reduce traffic accidents in Alberta in two ways. First, they could be employed in a manner similar to that in Sweden, to assist in the rehabilitation of drivers who had been charged with DWI. Second, they could be employed by drivers who had been charged with DWI offences and who wished to obtain reduced insurance rates by providing evidence to their insurers that they were not driving while intoxicated.

6. In-vehicle data recorders

Computer systems in automobiles have advanced to the point that it is now a relatively simple matter to monitor and record not only engine performance but also driver performance. At a low cost, for example, in-vehicle data recorders (IVDRs, sometimes called event data recorders, EDRs), can keep records of actions associated with increased probabilities of accidents, such as rapid changes in acceleration or deceleration, sudden changes in direction, average speed, distance travelled, and time of day travelled. (See Bordoff and Noel, 2008, at p. 13, for a discussion of current IVDR technology.)

With the addition of a GPS system, information can also be obtained concerning the speed limits, road conditions (for example, ice or snow), weather, and traffic congestion in the areas travelled by the driver; and with the addition of an alcolock, information can also be provided about the driver’s blood alcohol content.

A number of insurance companies ? particularly Progressive and GMAC Insurance in the United States (McQueen, 2008) and, to a lesser extent, Aviva in Canada (Bordoff and Noel, 2008) ? have recognized that even IVDRs that lack GPS systems can be used to reduce automobile insurance premiums in two ways.

First, it will be possible to identify, and reward (with reduced premiums), those individuals who: are less likely than average to be involved in accidents because they drive relatively few kilometers, are unlikely to engage in risky behaviour (as measured by acceleration, deceleration, and sudden turns), drive at speeds at which few serious accidents occur, and drive at times of day that are associated with low accident frequency.

Second, and more importantly, the data from IVDRs could be used to induce drivers to reduce the probability they would become involved in accidents, either by reducing the distance they drove or by increasing the level of precautions they took. Drivers could either volunteer to reduce their risk exposure ? for example, by reducing the number of kilometers driven or decreasing the number of incidents of sudden acceleration or deceleration, as measured by the IVDR ? in return for reduced insurance premiums; or they could agree to pay increments in premiums based on increased risk, again as measured by the IVDR.

One variation on this possibility would be to disband the “Facility Association,” (the program that allows high risk drivers to obtain insurance at actuarially unfair rates), and to replace it with a program based on the use of IVDRs. That is, high risk drivers could be offered the opportunity to moderate their premiums if they would agree to reduce their accident-causing behaviour, as measured by IVDRs installed in their vehicles. (Note: drivers would not be “forced” to install IVDRs: they would be given the choice between paying actuarially fair premiums or providing evidence that their behaviour had changed in such a way as to justify lower premiums.)

Even when a GPS is not attached to the IVDR, research shows that the information that can be extracted from an IVDR is sufficient to induce changes in driver behaviour. In a thorough review of the evidence, for example, Jason Bordoff and Pascal Noel (2008), of the Brookings Institution, argued that the introduction of a system in which individual drivers’ automobile insurance premiums were directly correlated with numbers of miles driven (pay-as-you-drive insurance) would reduce the number of automobile accidents by eight percent.

Toledo et. al. (2008) found that the risk data collected by the IVDRs in their experiment were strongly correlated with the probability that drivers had been involved in at-fault accidents. Interestingly, they also found that even when drivers were told that the information from IVDRs would not be used to reward or punish them, crash rates declined by approximately 19 percent. The presence of the IVDR alone was sufficient to alter driver behaviour.

The primary concern with IVDRs that has been expressed in the literature (see, especially, Askland, 2006), is that they represent an invasion of the driver’s privacy. Two responses have been made to this criticism. First, if a GPS system is not attached to the IVDR, the data that can be collected ? average speed, distance driven, number of occasions of sudden acceleration or deceleration, etc. ? provide no more information about the individual than do the data already collected by the car’s odometer and engine monitoring system.

Second, as long as the individual is free to choose whether to install an IVDR and whether to provide the information stored in any such system to a third party, that information is no more invasive of the individual’s privacy than are questions that consumers already voluntarily respond to when seeking health or life insurance or consumer credit.

7. Conclusion

In the early 2000s, automobile insurance premiums rose dramatically in Alberta, Ontario, New Brunswick, Nova Scotia, and Prince Edward Island. In each of these provinces, the government responded by reducing the benefits that were available to drivers ? that is, by introducing a limit on the non-pecuniary damages that were available to plaintiffs who had suffered “minor” injuries.

In this article, I have argued that numerous alternative policies exist that could reduce premiums, not by reducing benefits, but by reducing the incidence and severity of automobile accidents. Some of these policies ? such as IVDRs and alcolocks ? are still under development, and others ? such as raising the minimum drinking age or banning cell phone use ? may be politically unacceptable. Nevertheless, a strong argument can be made, I believe, for presenting the evidence concerning these policies to the citizens of Alberta, to determine whether they consider the potential savings to outweigh the costs.

References

Askland, A. (2006) “The Double Edged Sword that is the Event Data Recorder,” 25 (1) Temple Journal of Science Technology, and Environmental Law, 1-14

Bjerre, B., and J. Kostela (2008) “Primary Prevention of Drink Driving by the Large-Scale Use of Alcolocks in Commercial Vehicles,” 40 Accident Analysis and Prevention, 1294-1299.

Bjerre, B., and U. Thorsson (2008) “Is an Alcohol Ignition Interlock Programme a Useful Tool for Changing the Alcohol and Driving Habits of Drink-Drivers?” 40 Accident Analysis and Prevention, 267-273.

Bordoff, J., and P. Noel (2008) Pay-As-You-Drive Auto Insurance: A Simple Way to Reduce Driving-Related Harms and Increase Equity, The Hamilton Project: Brookings Institution, (July).

Bruce, C., and J. Strauss (2008) “Premiums, Profits, and Costs of Business in Alberta’s Automobile Insurance Industry, 1996-2006,” 13(2) Expert Witness, 2-7.

Carpenter, C., and C. Dobkin (2009) “The Effect of Alcohol Consumption on Mortality: Regression Discontinuity Evidence from the Minimum Drinking Age,” 1(1) American Economic Journal of Applied Economics, 164-182.

Fell, et. al. (2008) “The Relationship of Underage Drinking Laws to Reductions in Drinking Drivers in Fatal Crashes in the United States,” 40 (4) Accident Analysis and Prevention, 1430-1440.

Kolko, J. (2009) “The Effects of Mobile Phones and Hands-Free Laws on Traffic Fatalities,” 9 (1) B.E. Journal of Economic Analysis and Policy.

McCartt, A., et. al. (2006) “Cell Phones and Driving: Review of Research,” 7 Traffic Injury Prevention, 89-106.

McEvoy, S., et. al. (2005) “Role of Mobile Phones in Motor Vehicle Accidents Resulting in Hospital Attendance: A Case-Crossover Study,” British Medical Journal.

McQueen, M. (2008) “How Technology Can Help Trim Auto Insurance,” Wall Street Journal, June 26; accessed on May 8, 2009 at http://online.wsj.com/article/SB121443810954605365.html.

NHTSA (2006) The Impact of Driver Inattention on Near-Crash Risk, DOT HS 810 594.

Redelmeier, D., and R. Tibshirani (1997) “Association Between Cellular-Telephone Calls and Motor Vehicle Collisions,” 336 (7) New England Journal of Medicine, 453-458.

Sloan, F., B. Reilly, and C. Schenzler (1994) “Tort Liability versus Other Approaches for Deterring Careless Driving,” 14 (1) International Review of Law and Economics, 53-72.

Toledo, T., O. Musicant, and T. Lotan (2008) “In-Vehicle Data Recorders for Monitoring and Feedback on Drivers’ Behavior,” 16 Transportation Research, Part C, 320-331.

Wagenaar, A., and T. Toomey (2002) “Effects of Minimum Drinking Age Laws: Review and Analyses of the Literature from 1960 to 2000,” Journal of Studies on Alcohol, Supplement No. 14, 206-225.

Wagenaar, A., et. al. (2007) “General Deterrence Effects of U. S. Statutory DUI Fine and Jail Penalties: Long-term Follow-Up in 32 States,” 39 (5) Accident Analysis and Prevention, 982-994.

Wilson, J., M. Fang, and S. Wiggins (2003) “Collision and Violation Involvement of Drivers Who Use Cellular Phones,” 4 Traffic Injury Prevention, 45-52.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary.

Premiums, Profits, and Costs of Business in Alberta’s Automobile Insurance Industry, 1996-2006

by Christopher Bruce and Jason Strauss

This article first appeared in the winter 2008 issue of the Expert Witness.

Introduction

In February, 2008, Economica Ltd. was retained by the Canadian Bar Association to prepare a series of reports on automobile insurance premiums in five provinces: Alberta, Ontario, New Brunswick, Prince Edward Island, and Nova Scotia. We have now completed this work, having prepared two reports on Alberta and one on each of the other four provinces.

In this article, we summarise the main findings of the first of these reports, Alberta’s Minor Injury Regulation: Automobile Insurance Profits, Premium Rates, and Costs, prepared by Christopher Bruce, of Economica, and Jason Strauss, a Ph.D. student in the department of Risk Management and Insurance at Georgia State University. (The full text of this report can be found at: www.cba-alberta.org)

Our Report had three purposes:

  • to provide a measure of the profitability of automobile insurance in Alberta in the period 1996-2006, (that is, immediately preceding and immediately following the introduction of Alberta’s Minor Injury Regulation, the MIR, in the Fall of 2004);
  • to determine whether the observed changes in profits and premiums in the years prior to the introduction of the MIR had been caused by changes in costs; and
  • to identify what the effects on profits and premiums would be if the MIR was removed.

We summarise the results of our analyses in the three following sections of this article.

1. Profitability of Basic Coverage

As the MIR applied primarily to Basic Coverage, we focus in this section on that line of insurance. The methodology we use to estimate profits is based on the approach developed by the Insurance Bureau’s actuary, Mr. Joe Cheng, for his testimony in the case of Morrow v. Zhang (2008). (It was in Morrow that the constitutionality of Alberta’s Minor Injury Regulation was challenged.)

The most common measure of industry profitability (and the measure used in the Cheng Report), is after-tax “return on equity” (ROE) – that is, the industry’s after-tax profits divided by the value of the investments made in the industry. In Table 1 and Figure 1 (taken from our Report), we show that, prior to 2003, Basic Coverage was not profitable in Alberta, with an ROE ranging from -5.6 to +2.1 percent. In 2003, however, the return on Basic Coverage increased dramatically, to 19.1 percent, and rose above 20 percent in each of 2004, 2005, and 2006.

Table 1

Figure 1

1.1 Claims costs relative to total costs

It is possible that the sudden increase in ROE in 2003 could have arisen from a dramatic change in the costs of claims. The data in Table 2, however, indicate that these costs remained a relatively constant portion of insurance companies’ total costs throughout the entire period 1996 to 2006. That is, the rate at which the costs of claims were rising was not appreciably different from the rate at which insurance companies’ other costs – primarily the costs of administration – were increasing.

Table 2

1.2 Claims costs relative to premiums

Alternatively, profits may have risen in the 2003/2004 period because claims costs fell relative to premiums. We investigate this possibility in Table 3, which reports changes in claims costs per motorist, relative to average premiums. What this table indicates is that, until 2002, premiums tracked claims costs fairly closely. That is, each increase in claims costs per motorist was matched by a similar increase in insurance premiums, resulting in a ratio of costs to premiums that varied only slightly. For example, while the average claim for Basic Coverage was 99.0 percent of the average premium in 1996, that ratio was 92.9 percent in 2002 – because premiums rose by 39.1 percent over that period, while average claims rose by a similar amount, 30.3 percent.

Table 3

In 2003 and 2004, however, premiums rose much more quickly than did claims costs, driving down the claims ratio. Between 2002 and 2004, for example, the average premium rose by 19.3 percent, while average claims actually fell by 21.9 percent. Thus, it appears that the dramatic increase in profit rates over the 2003-2004 period was driven, in large part, by a sudden change in the relationship between the costs of Basic Coverage and the premiums that were charged for that coverage. In the following section, we investigate a number of factors that might have led to this change.

2. Changes in Costs per Vehicle

The price of automobile insurance – the premium – is affected by four components. First, there are the average costs of claims (including adjustment expenses) per vehicle that were discussed in the preceding section. Second, allowance must be made for administration expenses (broker’s commissions, overhead, etc.). Third, insurers earn income from the investment of equity and reserves (premium revenue that will eventually be used to pay claims). Finally, a reasonable rate of profit must be added to net costs.

The question we address in this section is whether the increases in premiums between 1996 and 2004 can be attributed to changes in any of these components.

2.1 Average claims per vehicle

In Table 3, we showed that the cost of claims rose at approximately the same rate as the price of premiums over the period 1996 to 2002. Thus, if there was a need for increased premiums in 2003 and 2004, it was not because the ratio of claims costs to premiums had changed over the preceding six years.

Nevertheless, Basic Coverage is composed of a number of sub-categories, including Third-Party-Liability and Accident Benefits. In turn, Third-Party-Liability (TPL) is composed of TPL-Property Damage and TPL-Bodily Injury, of which only the latter was affected by the Minor Injury Regulation (MIR). Thus, it is possible that even though claims costs for Basic Coverage as a whole did not increase in 2003 and 2004, there may yet have been an increase in the component that was affected by the MIR. To investigate this possibility, we report the data in Table 4.

Table 4

In this Table, it is seen that the claims for TPL-Bodily Injury increased at roughly the same rate as the other components of Basic Coverage prior to the MIR. For example, whereas claims for Bodily Injury increased by 32.5 percent between 1996 and 2002, claims for Property Damage increased by a similar percentage, 27.8.

We are led to ask, therefore, whether a change in some other element of the cost of insurance can explain the sudden increase in premiums that was observed in 2003 and 2004. In sections 2.2, 2.3, and 2.4 we analyze administrative expenses, investment income, and return on equity.

2.2 Administrative expenses

Table 5 reports that the ratio of administrative expenses to premiums (the expense ratio) decreased from 25.5 percent in 1996 to 23.8 percent in 2001. As average premiums increased only slightly over this period, the dollar value of expenses must have been decreasing or relatively stable. Furthermore, in the time period immediately prior to the introduction of the Minor Injury Regulation, 2002 and 2003, expense ratios fell further while premiums increased dramatically. It can be concluded, therefore, that changes in administrative expenses were not the source of the premium increases that occurred in 2002 and 2003.

Table 5

2.3 Return on investment

Insurance premiums are placed in a reserve until claims have to be paid. Those reserves are invested and the investment income generated thereby is credited against the cost of premiums. Hence, an increase (reduction) in the rate of return on investment, ROI, may lead to a decrease (increase) in premiums.

It is seen in Table 6 that the ROI insurers earned on their equity and reserves declined almost continuously over the period 1996 to 2001. Nevertheless, this decrease placed only limited upward pressure on premium rates. Specifically, we estimate that to compensate for the decrease in ROI from 9.0 percent in 2000 to 6.2 percent in 2003, insurers would have needed a $44 increase in the 2003 premiums on Basic Coverage. In fact, those premiums increased by $213, from $537 to $750. (See Table 3.) This confirms that decreasing ROI was not the primary impetus for the premium increases in 2002 and 2003.

Table 6

2.4 Return on equity

Once the net costs of insurance have been calculated, the premium is determined by adding a profit margin, or return on equity, ROE, to those costs. Thus, as the necessary ROE increases, premiums will also increase. We surveyed seven sources of expert opinion concerning the appropriate ROE target for the automobile insurance industry. We found:

  • Dr. Norma Nielson and Dr. Mary Kelly, in a presentation to the Alberta AIRB October 20, 2006, recommended an ROE in the range of 14.31 to 18.26 percent
  • NERA Consulting Economists, in a report for the Newfoundland & Labrador Board of Public Utilities, October 13, 2004, recommended an ROE in the range of 11 to 14 percent.
  • Based on NERA’s report, Dr. Ronald R. Miller of Exactor Insurance Services Inc. recommended an ROE of 12.5 percent.
  • Dr. Basil A. Kalymon, on behalf of the consumer advocate, recommended to the Newfoundland & Labrador Board of Public Utilities that the target return on equity for the setting of automobile insurance rates should be 9 to 10 percent.
  • The consumer representative to the Alberta AIRB, Ms. Merle Taylor, CMA, recommended that the ROE be higher than the allowable rate for utilities (at that time, 8.9 percent). She also stated that a 19.6 percent ROE would be “excessive.”
  • In his testimony in Morrow v. Zhang (2008), actuary Joe S. Cheng, F.C.I.A. stated that a 12.5% ROE was considered by many insurers to be in the low end of a reasonable range; and that the high end of a reasonable range might be 20%.

The Alberta Automobile Insurance Rate Board (AIRB) currently employs a formula that implies that an after-tax ROE of 9.5 percent would be appropriate.

Excluding the report by Merle Taylor, which did not give an exact range or recommendation, the average of the six remaining experts’ opinions concerning a reasonable ROE for automobile insurance is 12.76 percent. This figure is well above the rates earned on Basic Coverage in Alberta between 1996 and 2002, (see Table 1), but is well below the rates earned since then. Most importantly, Alberta insurance companies earned an ROE of 19.1 percent in 2003, the year before the introduction of the MIR.

2.5 Summary and conclusions

  • As indicated in the preceding sections, claims did not dramatically increase in the time period leading up to the Minor Injury Regulation.
  • As also shown above, administrative expenses did not increase but, rather, decreased in the time leading up to the Minor Injury Regulation.
  • Although investment returns decreased in the time leading up to the Minor Injury Regulation, their effect on the increase in premiums was minor.
  • ROE for Basic Coverage averaged -1 percent per year in the period 1996 to 2002 (7.4 percent for All Coverages). During this same period, average premiums for Basic Coverage only increased by 6 percent per year on average (4.5 percent per year on average for All Coverages). This premium deficiency (the difference between premium charged and premium required to reach a reasonable rate of return) appears to have been the primary impetus for the sharp increase in premiums that occurred in 2002/2003, as the “soft” market ended and a “hard” market began.
  • We estimate that without the premium increases in 2002 and 2003, ROE on Basic Coverage would have been -3.8 percent (in 2003).

 

3. Projected Effect of Removing the Minor Injury Regulation

Using the AIRB’s methodology, and controlling for other reforms beside the Minor Injury Regulation (i.e. controlling for the gross to net income reform and the collateral income reform), we estimate that the required average premium increase for Basic Coverage, if the Minor Injury Regulation had been removed, would have been $111.76/year if industry profits were to be maintained at their 2006 level, of 21.8 percent.

Alternatively, using the AIRB’s methodology, we estimate that insurer ROE for Basic Coverage would have been 12.2 percent in 2006 if the Minor Injury Regulation had been removed and premiums held constant. (Furthermore, in this case, the ROE would have been 16 percent for All Coverages.)

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary.

Jason Strauss is a Ph.D. student in the department of Risk Management and Insurance at Georgia State University.

Examination of Expert Witnesses

by Christopher Bruce and Derek Aldridge

This article first appeared in the winter 2008 issue of the Expert Witness.

On October 28 in Edmonton and October 29 in Calgary, Chris Bruce and Derek Aldridge were participants in a Legal Education Society of Alberta panel on examination of expert witnesses. In this note, we offer some recommendations regarding the examination of expert economists. These recommendations are based on our comments during the panel, and the feedback we received.

We divide our advice into pre-testimony and during-testimony periods.

Pre-Testimony

An effective examination is not created days, weeks, or even months before trial, but years. That is because an effective examination begins with a well-constructed expert’s report. In our experience, at least half of the judge’s impression of your expert’s opinion is going to be based on his or her reading of that expert’s report. Our advice, therefore, is that as soon as you receive the first report from your expert, you should try to read it from the perspective of the judge. If you cannot follow the report easily, despite having been immersed in the case, it is not likely that the judge will be able to follow it either.

This is not to say that you should attempt to influence what your expert is going to say. You do, however, have the right to ask your expert to improve how that opinion has been expressed. At this stage, you should particularly be looking for a clear, logical, methodical development of the expert’s argument. Are the facts and assumptions, upon which the opinion has been based, stated clearly? Is there a clear progression from the facts and assumptions to the conclusions? Does the expert employ clear, simple terminology and arguments? Does he or she “tell the reader what he/she is going to say, say it, then tell the reader what has been said?” Too often, we are sent opposing experts’ reports with a request that we please explain what that expert has said. If the lawyer we are working for cannot understand the opposing expert’s report, it is unlikely that the lawyer for whom the report was prepared could understand it either ? and it is also highly unlikely that the judge will understand it.

Be cautious when asking your economist to present scenarios that may not be supportable. For example, suppose your plaintiff had a well-established career and earned a steady income averaging $75,000 per year. Your economist will likely include a scenario in which it is assumed that the $75,000 annual income would have continued, but for the accident. However, your plaintiff might have advised you that earnings of $100,000 would have been available, due to a likely promotion, and you may decide to ask your economist to include such a scenario, with the understanding that supporting evidence (say, from the employer) will be forthcoming. If it turns out that no evidence will be offered in court to support the more-optimistic scenario, it will reflect badly on your expert (and your case) if the judge is unimpressed with scenarios that are presented as “illustrative only” or “at the request of counsel.”

We strongly recommend that you have a meeting with your expert some time in the two or three weeks preceding a trial: to clarify what the expert’s opinion is in detail and to prepare the most effective method of presenting that opinion in court. We feel that there are at least four major advantages to this pre-trial meeting. (i) As most experts are involved in hundreds of actions and may have written the report in this case months, if not years, ago, a pre-trial meeting can ensure that the expert is fully familiar with his/her own report. (ii) As it is common that new information becomes available in the last month or two before the trial, it is important that the expert is made aware of this information. (iii) You and the expert should discuss the most effective techniques for presenting his/her evidence. Are you, for example, going to follow the expert’s report page-by-page? At this stage, it is often useful to try some practice questions on the expert as experts can sometimes find the wording of questions to be confusing. If there are certain points that you especially want your expert to make during his/her testimony, make sure that your expert knows this, and knows what type of question you will ask in order to obtain the desired response. (iv) A review of the file with your expert may provide you with a clearer assessment of the strengths and weaknesses of both your expert’s report and that of the opposing experts, thereby creating a firmer basis on which to negotiate a settlement.

It is often also important to meet with your expert during the trial, a day or two before his/her testimony. As the lay witnesses appear before the experts, it is important that your expert be informed about any new information that has been presented during the lay testimony. Also, since the economist typically follows most (if not all) of the other experts, your economist can be advised of what evidence was ultimately offered by some of the other experts who prepared reports that were used as a foundation for the economist’s evidence. For example, if the vocational expert’s evidence has changed slightly from that offered in his 218 report (based on new information offered by lay witnesses during trial perhaps), it is important for your economist to know about this. Finally, the expert can be informed concerning the general approach that has been taken by both the opposing counsel and by the judge.

In the weeks or days before testimony, it is important to discuss with your expert the counter-arguments that you and he/she expect will be raised by the other side. While rebuttal reports may been prepared already, it is useful to try to identify what will be the most contentious economic issues, and what your expert’s response will be. Discuss any weaknesses in your expert’s report, and how they might be dealt with in court.

During-Testimony

Unless you have a particularly poorly-qualified expert, you should always begin the expert’s testimony by reviewing his/her qualifications, to impress the judge with the expertise of your witness. If you have a particularly well-qualified expert, opposing counsel may attempt to preclude you from introducing these qualifications by announcing that he/she will accept the expert’s qualifications without a review of the c.v. It is not advisable, of course, to succumb to this tactic.

Before beginning a review of the expert’s qualifications, it is advisable to inform the judge what that individual’s area of expertise is, so the judge can contrast the expert’s qualifications with the expertise that you are claiming.

Do not simply ask the expert to describe his/her c.v. Some experts will be too modest to provide a full description ? and some will be too boastful. Rather, ask them a series of questions about specific aspects of their expertise ? for example, about their most important educational attainments, their professional experience, their most important publications, and their experience testifying.

Enter the expert’s report and base your examination on the report. As the judge will not have expertise in the expert’s area, it will be useful for the judge to have the report before him/her as an aid to understanding the testimony. Also, as the judge will need to read the report later, when preparing a decision, it will be useful to be able to relate the recorded testimony to the report.

Follow the report page-by-page, if not paragraph-by-paragraph or line-by-line in your questioning of the expert. Our experience is that judges find it useful to follow the report during the testimony. If you start jumping around from page to page, the judge will become frustrated.

Ask questions that require only short answers. The court’s attention is held better that way than by allowing the expert to ramble on, perhaps becoming embroiled in the language of his/her discipline.

If you are representing the plaintiff and you think opposing counsel is going to introduce his/her own expert to counter yours, it may be advisable to ask your expert to comment on the opposing expert’s arguments. Your expert may be in a better position to expose the weaknesses of those arguments than you will be in cross-examination.

Similarly, you should also attempt to anticipate the tack that opposing counsel will use in cross-examination of your witness and ask your expert to comment on the anticipated arguments. Your expert will be much more comfortable “arguing” with you than with your opponent, both because cross-examiners will often severely curtail any attempt by experts to raise counter-arguments and because most experts will be reluctant to appear argumentative (with cross-examiners) as it makes them appear biased.

Sometimes during cross-examination, your expert may concede a weakness or error in his/her report. If the other lawyer does not allow your expert ample opportunity to discuss the significance of this weakness/error, then it may be helpful for you to raise the issue during redirect. This will provide your expert with additional time to think about the issue, and to provide a more in-depth response, if one is required.

Conclusion

In summary, a successful examination of your expert economist begins with a well-written report, containing scenarios and assumptions that match the evidence that will ultimately be offered in court. Regardless of your expert’s prior trial experience, it is always useful to meet with him or her before trial to discuss the economic evidence that will be offered, prepare for the other side’s arguments, and advise him/her of relevant testimony by other witnesses. With a suitable foundation and preparation before trial, your expert will have the best opportunity to perform well during trial.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary.

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

The Discount Rate Revisited (Spring 2008)

by Laura Weir, Derek Aldridge, Kelly Rathje, and Christopher Bruce

This article first appeared in the spring 2008 issue of the Expert Witness.

Our readers will recall that every year or two we review our standard discount rate assumptions and publish our findings. It is time to repeat this exercise.

In the Summer 2006 issue of the Expert Witness, we reported that real rates of interest (that is, the rates of return net of inflation) had increased slightly from those outlined in our Summer 2005 article. We responded by increasing our forecast of the short-term (one to six years) real rates of interest. Our forecasted interest rates for the medium to long-term (seven to 15 years or more) remained unchanged – although these rates were slightly higher than the observed real rates of return on Government of Canada bonds, long-term real rate of return bonds, and the long-term rate mandated in Ontario. (Higher rates lead to lower present values, so our estimates can be considered conservative.)

In our 2006 article we specified our assumptions for real interest rates for periods ranging from one-year to 15 years or more. Our assumptions were based on the observed rates of interest on Government of Canada bonds of various terms. We now have more rates to observe and we see that these rates have continued their long-term downward trend. Real rates of interest for five bond series over the last 14 years are depicted in the figure below (with the rates for 2008 estimated using an average of the January through June interest rates).

Figure 1

From the figure we see that real rates have decreased slightly from their 2006 and 2007 levels. However, the decrease in real interest rates is not sufficient to warrant a change in our discount rate assumptions. In particular, we note that the average real rates for the past 12 and 24 months are very similar to the corresponding averages at the time we wrote the previous article. One exception is the long-term rate, whose 24-month average (2.23 percent) is a third of a percent less than the corresponding 24-month average at the time of our previous article.

Although we do not show the comparable interest rates on guaranteed investment certificates (GICs), we have examined them and they are consistently lower than the rates of return on bonds. For example, the rate currently offered for 5-year GICs is approximately three percent, corresponding to a real rate of only one percent.

Our discount rate assumptions, unchanged from our 2006 article, are shown in the table below.

Table 1

Over the years, our approach to forecasting an appropriate discount rate has been criticized by other economists who prefer to rely on historical interest rates in making their forecasts. Below, we address some of these critiques and provide support for our approach.

Our approach, often called the “conservative investment” approach (which assumes a plaintiff will use his damage award to purchase a financial instrument with an appropriate term to maturity and hold that instrument to maturity), has been criticized by other economists who argue for a “market-based” approach (that assumes a plaintiff will buy and sell bonds as interest rates vary instead of holding the bond to maturity). One of us (Bruce) addressed this issue in an article written for the Spring 2007 issue of the Expert Witness entitled “Forecasting the long-term interest rate on Government of Canada bonds: “market-based” versus “conservative” investment“. We summarize his conclusions here as this issue continues to arise.

Some economists suggest that our approach ignores the price changes resulting from changes in the interest rate within the bond market, arguing for the market-based approach that assumes the plaintiff can earn a higher rate of return by actively buying and selling bonds as interest rates change. As a simple example, suppose a plaintiff will incur a loss of income of $100,000, 20 years from now. The conservative approach assumes that he will purchase a 20-year bond, paying five percent in interest per year, for $37,689 and redeem it at maturity for $100,000 to fund his loss in that year.

Assume, however, that the interest rate decreases to four percent one year after purchase. The market-based approach suggests that at four percent, the plaintiff could sell his bond (that has 19 years left to maturity) for $47,464 (= $100,000/1.0419) and earn $9,775 (= $47,464 – $37,689) in profit, for an effective rate of return of 25.94 percent in one year. However, this is actually not a profit because the plaintiff still has to purchase a 19-year bond (at a cost of $47,464) to fund his $100,000 loss of income 19 years from now. Thus, there is no real benefit to actively trading bonds as the interest rate changes.

In addition to the fact that the effective rates of return under the market-based approach are illusory, effective rates of interest are extremely variable. For example, a publication by the Canadian Institute of Actuaries entitled Report on Canadian Economic Statistics 1924-2005 indicates that the 10-year average (1996-2005) effective real rate of return on long-term Government of Canada bonds was 7.36 percent. However, the standard deviation was 9.01 percent, suggesting an average effective real rate of return that could fluctuate between -1.65 percent and 16.37 percent. This suggests that the plaintiff will almost certainly earn a rate of return different from the average long-term rate. Further, while a “profit” can be made by selling a bond when the interest rate decreases, a “loss” would occur if the interest rate increased (say) to six percent, where the 19-year bond would now only cost $33,051, for a net loss of $4,638 (or an effective rate of return of -12.31 percent).

Finally, if we were to rely on an average of past effective rates of interest then what period should we rely on? For example, the Canadian Institute of Actuaries report noted above indicates that the real effective rate of return on Government of Canada long-term bonds averaged -1.31 percent for the period 1956-1980, +8.74 percent for the period 1981-2005, and +6.79 percent for the period 2001-2005. There would be no justification for relying on any one of the above periods over the others, or for averaging these periods together, in attempting to obtain a forecast of the rate of return in the future.

We use the observed rates on government bonds as an indicator of the rates that are anticipated by large institutional investors, with billions of dollars at stake. While one might find that a forecaster is suggesting that (say) 3½ percent is the appropriate real long-term rate, this prediction is contradicted by the fact that the Government of Canada is presently able to sell its long-term bonds which offer a real return of less than three percent. (If expert institutional investors anticipated that real rates on secure investments will average, say 3½ percent over the next ten years, then they would not buy bonds that pay only 2½ percent, and the Government of Canada would be forced to adjust its bond rates.)

Other economists suggest that it would be simpler to assume that a plaintiff will hold a long-term security and then liquidate portions of this security to fund his/her losses in each year. This is simply another version of the market-based approach and, as discussed, there is a great amount of risk inherent in this strategy. Under our approach, if a plaintiff purchases a 5-year government bond with a value at maturity of $10,000, then in five years he is virtually guaranteed to receive $10,000 after redeeming his bond. However, if he were to buy a 20-year bond with the idea that he would liquidate portions of it to fund losses in each year, then he would be at the mercy of the bond prices available in each year. That is, he would be selling portions of his bond (as opposed to redeeming bonds for the guaranteed maturity value) and so, would be relying on the price of bonds attainable at the date he needed to fund his losses. As our discussion regarding the “conservative” versus “market-based” approaches illustrates, a plaintiff trying to fund his losses during periods of high interest rates would likely be selling portions of his bond at prices lower than his original purchase price and so, may not be able to fund his losses in each future year. If there is pressure on interest rates to increase in the next few years, as many economists feel is the case, then it is likely that plaintiffs investing awards from trials occurring in the next year or two would find themselves in this situation. We do not believe it is reasonable to impose this level of risk on a plaintiff.

Over the last ten years our prediction concerning the long-term interest rate has gradually declined from 4¼ percent to three percent. This decline has been in step with the observed rates, which can be seen in the above chart. Other economists have commented on our changes, with the implication that these changes demonstrate a weakness in our methodology. Our response is that the long-term rate has been changing over the past ten years, and it is important to reflect these changes in our calculations. To do otherwise would result in us using interest rates that are inconsistent with the rates that are actually available to plaintiffs.

Even if one finds that over the past few decades, long-term real interest rates have averaged 3½ percent, that rate is not now available to plaintiffs. Today’s plaintiff seeking secure investments simply cannot obtain a guaranteed long-term rate as high as the rates that were available 10 or 20 years ago. Even if the long-term rate rises to 3½ percent in five years, it does not follow that today’s plaintiff will be able to earn a long-term rate of 3½ percent, since he will be limited to the lower rates for the first five years.

Finally, many economists argue that plaintiffs should invest in equities, as well as bonds, and argue that this would result in a portfolio that is less volatile than investing in bonds alone. We find it difficult to justify the assertion that a portfolio that includes equities would be less volatile, given that the value at maturity of Government of Canada bonds is virtually guaranteed. Remember, the purpose behind the plaintiff’s investment of an award is to fund his losses in each future year and this is much different from investing for (say) retirement. The plaintiff must be able to fund his future losses in each year, whereas retirement can be delayed (or retirement plans changed) if there are insufficient funds. A plaintiff who invests in a series of bonds that provide the amount needed to fund his loss in each year, will receive the necessary amount with little to no risk of default. The same can not be said of equities, which carry a very real risk of default. The inclusion of equities can only increase the risk that a plaintiff will not be able to fund their future losses in each year.

We will re-examine our assumptions next year, and expect that some minor adjustments in our shorter-term rates may be warranted, depending on the movement of rates between now and then. As noted, minor changes in our assumptions regarding short-term interest rates will typically lead to negligible changes to our present value estimates. The assumed longer-term rates have a greater influence on our calculations, and if the rate on long-term bonds remains significantly below three percent (as it has since 2004), it may be appropriate to adjust our long-term rates as well.

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Laura Weir, Derek Aldridge, Kelly Rathje, and Christopher Bruce are consultants with Economica.

The Impact of Poor Health on Retirement Age

by Christopher Bruce

This article first appeared in the autumn 2007 issue of the Expert Witness.

In personal injury cases, plaintiffs often argue that their disabilities will induce them to retire early and, therefore, cause a reduction in lifetime earnings. As such claims are largely based on the plaintiff’s own testimony, it is often difficult for the courts to determine whether the claim is credible and, if so, to identify the number of years by which retirement will be accelerated.

The purpose of this article is to assist the court in these determinations by providing a survey of the academic literature on the effects that health limitations have on the age of retirement. As the first edition of my textbook, Assessment of Personal Injury Damages (Butterworths, 1985) contains a survey of the early literature on this topic, I concentrate in this paper on articles published since 1990.

This yields a set of eight studies. Of these, two (Disney, for Britain, and Campolieti, for Canada) reported only that a negative change in health or disability status among individuals over 50 had a “significant” negative effect on the age at which those individuals retired.

Of the remaining studies, two provided data concerning the impact of alternative levels of health status on the probability that 50-65 year-olds would be working. Au, Crossley, and Schellhorn, using Canadian data from 2000-2001, reported that even a minor change in health status, from “very good” to “good,” would reduce the probability of employment by 10 percent. (See Table 1.) And a change from “excellent” to “poor/fair” could reduce employment by as much as 40 percent (among males).

Table 1

Similarly, Cai and Kalb, using Australian data from 2001, found that a change in health status from “excellent” to “poor” would reduce the probability that individuals would be in the labour force by approximately 16-18 percent. (See Table 2.)

Table 2

At age 55, these reductions in probabilities imply that individuals in poor health will retire between one and two years earlier than those in very good health. This is consistent with Gustman and Steinmeier’s finding, for the United States, that individuals who were “limited in the kind or amount of work” in which they could engage could be expected to retire two years earlier than those not so-limited.

Berger and Pelkowski, for the United States, and Jimenez-Martin, Labeaga, and Prieto, for Spain, also found impacts that were similar to those found by Campolieti and Au, et. al., but using somewhat different measures of health status.

Jimenez-Martin et. al. reported that 55-65 year-old individuals with “severe disability” were 14.6 percent less likely to be employed than were the non-disabled, and that those with “very severe disability” were 28.5 percent less likely to be employed than were the non-disabled.

Berger and Pelkowski found that among 51-61 year-old couples in which both the husband and wife had (at the beginning of the study period) been healthy and employed, the effect of a health problem was to reduce the probability that the wife would be working by 19 percent and that the husband would be working by 35 percent.

Finally, McGarry found that a change in health status from “good” to “fair” would reduce the probability that a 62 year-old would be working from approximately 45 percent to 40 percent.

To summarise, regardless of the country that is investigated, the evidence is clear: a reduction in health, from “good” to “fair or poor” will have a significant, negative impact on the probability that 50-65 year-old individuals will be working. Although the precise effect of such a reduction varies from study to study, there appears to be fairly consistent evidence that the average effect is to reduce the age of retirement by approximately two years (for example, from age 61 to age 59).

References

Au, D. W., T. Crossley, and M. Schellhorn (2005) “The effect of long-term health on the work activity of older Canadians.” 14 Health Economics, 999-1018.

Berger, M., and J. Pelkowski (2004) “Health and family labor force transitions.” 43 Quarterly Journal of Business and Economics, 113-138.

Cai, L., and G. Kalb (2006) “Health status and labour force participation: Evidence from Australia.” 15 Health Economics, 241-261.

Campolieti, M. (2002) “Disability and the labor force participation of older men in Canada.” 9 Labor Economics, 405-432.

Disney, R., C. Emmerson, and M. Wakefield (2006) “Ill health and retirement in Britain: A panel data-based analysis.” 25 Journal of Health Economics, 621-649.

Gustman, A., and T. Steinmeier (2000) “Retirement in dual-career families: A structural model.” 18 Journal of Labor Economics, 503-545.

Jimenez-Martin, S., J. Labeaga, and C. Prieto (2006) “A sequential model of older workers’ labor force transitions after a health shock.” 15 Health Economics, 1033-1054.

McGarry, K. (2004) “Health and retirement: Do changes in health affect retirement expectations?” 39 Journal of Human Resources, 624-648.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Impact of Childhood Sexual Abuse on the Educational Attainment and Adult Earnings of Canadian Women

The Impact of Childhood Sexual Abuse on the by Christopher J. Bruce, Ph.D. & Daniel V. Gordon, Ph.D.

This article first appeared in the autumn 2007 issue of the Expert Witness.

Introduction

One of the most complex issues facing the courts in any sexual abuse case is the determination of the impact that the harm has had on the plaintiff’s earning capacity. Not only is very little statistical evidence available on this issue, but the data that do exist have often proved to be unreliable.

Recently, this lack of a reputable source has been resolved with the publication of a Statistics Canada survey in which a representative sample of Canadians was asked about their experiences of victimization. From this survey, we were able to obtain information about a large set of (adult) women who had suffered sexual abuse as children.

The purpose of this paper is to report our findings concerning the consequences of that abuse on the educational attainment and earnings of the victims. Our surprising result is that, among most such victims, abuse does not have a statistically significant effect on adult education and earnings. Furthermore, in the only group for which abuse
was found to have a significant effect – women who were first abused between the ages of seven and thirteen
– education and income were higher than among women who had not been abused.

The remainder of the paper is divided into three sections: a review of the existing literature; the development of an economic model concerning the effect of abuse; and a summary of our statistical findings.

Existing Literature

The academic literature concerning the effects of childhood sexual abuse is composed of two streams. In the first, researchers have attempted to develop theories of childhood social-psychological development that can be used to understand the pathways by which abuse affects its victims. In the second, researchers have used statistical tests to identify correlations between abuse and its predicted outcomes, such as depression, alcoholism, and school completion rates.

Theoretical

Many theories concerning the impact of sexual abuse are founded on the ‘core-symptom’ model, in which a
core problem or event is presumed to have led to one or more symptoms. The most common of these models characterize sexual abuse as a trauma, leading researchers to predict that abuse will result in post traumatic stress disorder.

An alternative interpretation suggests that, rather than
having a single effect, sexual abuse might produce multifaceted effects. Finkelhor and Browne (1985), for example, argued that sexual abuse had four primary effects: traumatic sexualization, stigmatization (i.e. low esteem and self-destructive behaviour), betrayal, and powerlessness.

A third approach, ‘developmental models,’ proposes that sexual abuse may affect victims by interfering with development in areas such as social- and self-functioning. In this view, therefore, the age at which the child is abused may be a critical determinant of the long-term effects of that abuse. For example, Celano (1992) suggested that the impact of sexual abuse may differ among Piaget’s three stages of childhood moral development (Piaget, 1965): preschool (ages 0-6), latency (7-13), and adolescence (14-19). She hypothesised that whereas preschoolers may not recognise that abuse is morally reprehensible, and adolescents may consider their moral culpability to be ameliorated by failure to provide informed consent, children in the latency period may consider themselves (at least in part) to be responsible for many of the types of abuse. Accordingly, she predicts that abuse will be most harmful if it occurs in the latency period.

Statistical

Statistical studies can roughly be divided among those that investigate the effect of sexual abuse on: psychological factors, (such as depression, self-esteem, and sexuality); social outcomes, (such as alcoholism and delinquency); and economic outcomes, (specifically, schooling and adult income).

This literature is virtually unanimous in its finding that childhood sexual abuse has statistically significant effects on the victim’s psychological well-being. The outcomes that are most commonly found include: low self-esteem, post-traumatic stress disorder, depression, affective and personality disorders, and anti-social behaviour.

The sociological literature has provided evidence concerning the effect that abuse has on criminal activity. Studies that aggregate across a number of different types of childhood abuse
– neglect, physical abuse, and sexual abuse, for example
– commonly find that criminal activity is correlated with
this aggregate; although some find no statistically significant correlation. Importantly, however, when ‘abuse’ is separated into its components, it is only ‘neglect’ that is found to be correlated with criminal activity. Neither physical nor sexual abuse appears to be a significant determinant in this formulation.

Very mixed results have been obtained when researchers investigate the impact of abuse on schooling and income. Slade and Wissow, (2006) found that individuals who had been maltreated as children had lower high school GPAs than the control group, but no greater problems with teachers, with completion of homework, or with school absences. And some studies have found evidence that victims of childhood sexual abuse performed better in school than those who had not been abused (e.g. Eckenrode, et al. 1993 and Buckle, et al. 2005).

Economic Model

In our model, we assume that individuals divide their time among three activities: solitary leisure activities, such as reading, watching television, and playing video games; social leisure activities, such as team sports, club memberships, and interacting with friends; and “market” activities, such as investing in education and working in the labour market. The value of each activity increases as additional time and effort is devoted to it. And the “cost” of time spent in any one activity is the value that is foregone from the other activities (the “opportunity cost” concept so familiar to economics students).

We hypothesize that the effect of sexual abuse is to reduce the benefits that individuals obtain from each of the three activities. Normally, one would expect that this would lead to a reduction in each of them. However, assume that the negative effect on the time and effort devoted to two of the activities was greater than it was on the remaining one. In that case, it is possible that the victim might “substitute” away from the more seriously-affected activities towards the less-seriously affected one. As a result, the latter might even increase.

For example, if abuse had a much more significant (negative) impact on the individual’s ability to socialize than on
her ability to undertake schoolwork or to compete in the labour market, abuse might lead to a lesser reduction in the latter activities than expected, and could even lead to an increase in those activities. In common parlance, the individual might be said to have compensated for the harm to her socialization skills by ‘throwing herself’ into academic and work-related activities. In such a case, abused individuals might be observed to complete more years of education than the non-abused, and might earn higher incomes; but this would come at the expense of a significant withdrawal from normal social activities. We propose to test for this effect in the analysis reported in the next section.

Statistical Estimates

We obtained information concerning 6,528 adult Canadian
women, (drawn from the 1999 General Social Survey), of whom 607 reported that they had been sexually abused as children. Using the data from this survey, we conducted two statistical tests.

In the first of these, we estimated the effect of a series
of variables on educational achievement. The variables that are usually found to be important – such as parents’ education, individual’s place of birth, and whether the individual belonged to a “visible minority” – all proved
to be significant in our data. In addition, we found that if the individual had first been sexually abused between the ages of seven and thirteen, she obtained more education than did individuals who had not been abused or who had first been abused before seven or after thirteen.

In our second test, we estimated the effect of a number of background variables on adult earnings. As expected, we found that variables such as the individual’s education and whether she belonged to a visible minority had significant effects on income. And, again, we found that individuals who had been abused between the ages of seven and thirteen had statistically higher levels of income than did those who had not been abused or who had first been abused before seven or after thirteen. Importantly, this effect is in addition to the increase in income that would have arisen from the effect of abuse on education.

To summarise, we found: first, that abuse before the age of seven or after the age of thirteen had no statistically discernable effect on either the victim’s education or her adult income. Second, abuse between the ages of seven and thirteen increased average educational levels and increased average incomes, both directly and indirectly (through the effect on education).

Conclusion

We have found that, on average, sexual abuse is not associated with lower educational levels or lower adult incomes among victims. This does not mean that all victims have higher income levels than those who have not been victimised: some victims will be above-average and some below. When the court is dealing with a particular plaintiff, it should always rely on factors that are specific to that individual. Nevertheless, our results suggest that it cannot be concluded, without such specific information, that the individual’s adult income will be adversely affected by sexual abuse.

References

Buckle, S., S. Lancaster, M. Powell, and D. Higgins (2005) “The Relationship Between Child Sexual Abuse and Academic Achievement in a Sample of Adolescent Psychiatric Inpatients,” 29 Child Abuse and Neglect, 1031-1047.

Celano, M. (1992) “A Developmental Model of Victims’ Internal Attributions of Responsibility for Sexual Abuse,” 7 Journal of Interpersonal Violence, 57-69.

Eckenrode, J., M. Laird, and J. Doris (1993) “School Performance and Disciplinary Problems Among Abused and Neglected Children,” 29 Developmental Psychology,
53-62.

Finkelhor, D., and A. Browne (1985) “The Traumatic Impact of Child Sexual Abuse: A Conceptualization,” 55 American Journal of Orthopsychiatry, 530-541.

Piaget, J. (1965) The Moral Judgement of the Child, (New York: Free Press).

Slade, E., and L. Wissow (2006) “The Influence of Childhood Maltreatment on Adolescents’ Academic Performance,”
Economics of Education Review, (in press).

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Daniel V. Gordon, Ph.D., is a professor of economics at the University of Calgary, where he specialises in the use of statistics for economic analysis.

Forecasting the long-term interest rate on Government of Canada bonds: “market-based” versus “conservative” investment

by Christopher Bruce

This article first appeared in the spring 2007 issue of the Expert Witness.

Introduction

In order to calculate the lump-sum, or discounted, value of a future stream of earnings, the financial expert must forecast the rate of interest (or discount rate) at which the plaintiff’s damages will be invested. Although most experts now base this forecast, to a large extent, on the rates of interest available on Government of Canada bonds, disputes have arisen concerning the manner in which the data concerning these bonds should be interpreted.

Fundamentally, the question comes down to one of whether the plaintiff can be assumed to take a “conservative” approach, in which she invests her damages in long-term bonds and holds those bonds to maturity; or whether she can be assumed to follow a “market-based” (or “speculative”) approach in which she buys and sells bonds as market conditions change.

Whereas Economica favours what I have called the conservative approach, some other economists employ the market-based approach. In this article, I first describe how interest rates are determined under each of these approaches and then I explain why I believe that the market-based approach is inappropriate.

Definitions

Imagine the following scenario: the court has ruled (i) that one component of the plaintiff’s damages is a loss of $50,000 twenty years from now; and (ii) that the interest rate to be used to discount this loss is five percent. In this case, the lump sum value of the loss can be determined to be $18,844 (= $50,000/1.0520).

It is possible that the court could have obtained its interest rate assumption simply by observing the rates offered on twenty-year bonds – what I will call the “posted” rates. Implicitly, in that case, it would have been assuming that the plaintiff will use his damages to purchase a twenty-year bond (or similar, long-term financial instrument) that pays five percent per annum; and that he will hold that bond until maturity. I call this the “conservative” approach.

Alternatively, however, the court might have assumed that the plaintiff will not hold his bond until maturity, but will buy and sell bonds as interest rates vary. In this approach, the effective interest rate will be the average of the rates that the plaintiff can expect to earn over the twenty year period. I call this approach the “market-based investment” approach.

Market-based investment in bonds operates in the following way: Imagine that, at a time when posted interest rates are five percent, the plaintiff has paid $18,844 to purchase a twenty-year bond worth $50,000 on maturity. Assume also that, one year later, interest rates have fallen to four percent. At that rate, it would cost $23,732 (= $50,000/1.0419) to purchase a bond that paid $50,000 nineteen years in the future. The plaintiff could now sell his twenty-year bond, (which, after a year, has nineteen years left on it), for this amount – making a profit of $4,888 (= $23,732 – $18,844), or an effective rate of return of 25.94 percent, in one year.

Rates such as this can be earned on long-term bonds as long as the interest rates on those bonds are falling. For example, a bond that pays $10,000 ten years from now will cost $5,584 when interest rates are six percent; and a bond that pays $10,000 nine years from now will cost $6,446 when interest rates are five percent. Thus, the investor who purchases a ten-year bond at six percent will be able to sell it one year from now for a profit of $862 (= $6,446 – $5,584), or an effective return of 15.44 percent (= $862/$5,584), if interest rates fall to five percent.

Whenever interest rates are falling, the investor who actively trades long-term bonds will make effective rates of return that exceed the rates that would be obtained if those bonds were held to maturity.

Conversely, however, if interest rates are rising, the market-based trader will earn effective rates that are lower than the posted rates. For example, if the interest rate is seven percent, a bond that pays $10,000 nine years from now will cost $5,439 (= $10,000/1.079). It was seen above, however, that a bond that pays $10,000 ten years in the future will cost $5,584 when interest rates are six percent. Thus, an investor who purchases a ten-year bond at six percent will lose $145 (= $5,439 – $5,584), for an effective “return” of -2.6 percent, if interest rates fall to seven percent and he sells it one year later.

What is less clear from these examples is that, if the effective interest rates are averaged over a long period of time, they will equal the rates that investors would have obtained had they held their bonds to maturity. Over the long-run, the investor who sells multi-year bonds after one year, and replaces them each time with other multi-year bonds, will average the same rate of return as an investor who buys and holds bonds to maturity.

Data

Table 1 reports both the posted and the effective rates of interest on Government of Canada bonds of 10+ years to maturity, for the last 25 years. It is seen in the first column of this table that posted interest rates have fallen almost continuously over the entire period: from 15.22 percent in 1981 to 4.39 percent in 2005.

Table 1

Given the discussion above, therefore, we expect to see that effective interest rates over most of this period would exceed the posted rates. It is seen in the second column of Table 1 that this is what happened. Particularly noticeable is the effective rate in 2005: 15.05 percent at a time when posted rates were in the four to five percent range.

As those who argue for the use of effective rates anticipate that the average of those rates will equal the average of the posted rates over the long run, Table 2 reports average posted and effective rates, both in nominal and “real” terms, for various sub-periods in the last 50 years.

Table 2

It is seen there that, whether nominal or real (i.e. net of inflation) rates are used, effective rates have exceeded posted rates in every sub-period in the last 25 years. For example, whereas the average effective nominal rate was 12.49 percent between 1981 and 2005, the average posted rate was 8.64 percent. The comparable real rates were 8.74 and 5.00 percent, respectively, a difference of over three percentage points in each case.

Only if a fifty year period is used do the effective and posted rates begin to approach one another – primarily because the 25 year period from 1956 to 1980 experienced extremely low effective rates of return (hence balancing the high rates from 1981-2005 in the calculation of the fifty-year average).

Drawbacks to Use of the Effective Rate

A review of the information contained in Tables 1 and 2 makes it clear that there are many disadvantages to the use of the effective rate as an indicator of the rate of return that plaintiffs will be able to obtain in the future.

1. The most serious difficulty with this rate is that it has been extremely variable. As a result, one can obtain almost any estimate of the real effective rate that one wishes, simply by choosing the appropriate time period.

Those who wish to argue for a very high rate might choose the fifteen-year period 1991-2005, with an average rate of 9.39 percent, for example. Whereas those who wish to argue for a much lower rate could choose the fifty-year period 1956-2005, with an average rate of 3.71 percent – or even the 60-year period 1946-2005, with an average of 2.44 percent.

There is no sound reason for choosing any one of these periods over the other. For example, it would be difficult to justify averaging together the 1956-1980 average, of -1.31 percent, with the 1981-2005 average, of 8.74 percent, to obtain a forecast of the rate of return obtainable over the next ten years.

2. A related problem is that the extreme variability of the effective rate virtually guarantees that the rate of return the investor will actually earn will differ significantly from the average rate obtainable over the long run. Hence, it would never be prudent to advise plaintiffs to adopt the market-based investment approach on which the effective rate is based.

3. Because long-term interest rates have been falling for 25 years, they have reached levels so low that most analysts believe they will not fall further – they certainly cannot fall by more than ten percentage points, as they did between 1981 (15.22 percent) and 2005 (4.39 percent). This means that the very high effective rates that have been observed in the last 25 years will not be observed again. Indeed, it is highly likely that nominal rates will rise over the near future, causing effective rates to fall, perhaps even into negative figures. As a result, plaintiffs would not be well-advised to engage in market-based investment in bonds.

4. Even if effective rates are positive, and above posted rates, the effective rate is not an appropriate rate for determining long-term rates of return on investments.

Return to the example developed in the first section of this article: The court has found that the plaintiff will lose $50,000 twenty years from now. Hence, if the interest rate is five percent, the lump-sum value of the plaintiff’s damages amount to $18,844. If, between now and one year from now, the interest rate falls to four percent, the plaintiff will be able to sell his bond for $23,732, earning a one-year rate of return of 25.94 percent.

But the plaintiff still needs to set aside enough money to replace his future $50,000 loss. At the new four percent interest rate, this will cost him $23,732. The money he has “earned” by selling his bond now has to be spent to replace it. Thus, the high effective rate of interest is illusory.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Cost of Household Services, Alberta, 2006: A Survey

by Christopher Bruce and Amelia Lamb

This article first appeared in the summer 2006 issue of the Expert Witness.

In 1997 and 1999, Economica conducted surveys of the cost of obtaining household services. At that time, we found that housecleaners in Calgary and Edmonton charged approximately $13.50 per hour; and that handymen charged approximately $24.00 per hour.

Since that time, we have estimated the current costs of household services by increasing the 1999 estimates by the intervening rate of wage inflation in Alberta. This implies, for example, that our estimate of the cost of housecleaners was approximately $16.00 per hour in 2005.

Increasingly, however, we have become aware that our estimates differ from the rates that prevail in Alberta, particularly in Calgary and Edmonton. The informal evidence available to us suggests, for example, that most housecleaners charge significantly more than $20 per hour.

For this reason, in late 2005 and early 2006 we conducted a new survey of household costs. In this survey, we obtained housecleaning, handyman, landscaping and snow removal, child care, and home care/meal preparation rates from a large sample of agencies and individuals in both Calgary and Edmonton, and housecleaning rates for smaller samples in Lethbridge, Grande Prairie, and Red Deer. We report the results of that survey in this article.

Housecleaning

Using newspapers and the Yellow Pages, we identified thirteen individuals or agencies in Calgary and ten in Edmonton that provide housecleaning services. We asked each of them to provide their hourly rate to clean a 1,600 square foot, two-story house (assuming there were not pets and that the cleaner would not be responsible for the basement). In Calgary, the average rate was $28.00 per hour ($26.22 if the top two rates are excluded), with a range from $21.25 to $38.00. As can be seen in Table 1, the most common rates (from seven agencies) were in the range of $24.00 to $27.50 per hour. Two of the thirteen rates were from individuals, who quoted $22.50 and $24.00 per hour, respectively.

In Edmonton, the average rate was slightly lower, at $26.10 per hour ($24.77 without the top rate); and the most common rates (from six agencies) ranged from $22.00 to $25.00 per hour. (See Table 1.)

Table 1

We were less successful at obtaining quotes in the other regions, obtaining only three in Lethbridge, two in Red Deer, and one in Grande Prairie. In those cities, the average hourly rates were: Lethbridge, $17.00; Red Deer, $21.00; and Grande Prairie, $22.50.

With the sole exception of the $17.00 figure for Lethbridge, it is seen that all of these figures significantly exceed the $16.00 rate that we estimated by increasing the 1999 rate by the average rate of wage inflation in Alberta.

We suspect that there are two reasons for the deviation of our predicted estimates from the actual figures, as indicated by the survey. First, it may be that the wages of individual housecleaners have been rising more quickly than the average. Second, anecdotal evidence suggests that the housecleaning sector has increasingly become dominated by professional agencies, whose hourly rates exceed the wages they pay to their employees, (in many cases by a significant margin).

This raises an important question: if employees are being paid, say, $14 to $17 per hour, and agencies are charging $25 to $35 per hour, why don’t individual cleaners leave their current positions and set up in competition with their former employers? Why doesn’t a worker who has been earning $15 per hour advertise his or her services at $20 to $30 per hour?

We suspect that the answer to this question derives from three factors. First, many cleaner-employees may lack the business skills to allow them to establish their own companies. These individuals may prefer to work for a company that offers them guaranteed hours and wages, as low as those wages may be, rather than take the risks of setting up their own firms.

Second, commercial firms often incur costs – for example, for cleaning supplies, advertising, insurance, transportation, administration, and employee bonding – in excess of the wages they pay to their employees. Individuals who established their own businesses would have to bear these costs themselves.

Finally, commercial firms may be better able than individual cleaners to develop reputations for reliable service. If a cleaner is sick or otherwise unable to work, a firm can often replace that individual with another employee; whereas if self-employed individuals are unable to meet their commitments, their jobs go undone. Customers may be willing to pay a premium for the more reliable service.

Regardless of the answer to this question, however, the fact is that it would be very difficult to hire a reliable housecleaner in Calgary or Edmonton for less than $20 per hour – and the expected cost is closer to $26 to $28 per hour.

Handyman

We obtained the names of handyman services in Calgary and Edmonton from newspapers and the internet. In each case, we asked agencies to quote for the hourly rate to either paint an interior room or repair a deck. The results are reported in Table 2. With the exception of one “outlier,” a $15.00 per hour rate quoted by a non-bonded, uninsured, non-professional student company, the rates in both cities fell consistently in the $30.00 to $40.00 per hour range, with an average of approximately $33.00 per hour in both cities.

Table 2

Landscaping and snow removal

Landscaping and snow removal firms were identified online or from the Yellow Pages. In the case of landscaping, firms were asked for their hourly rates to mow lawns and conduct yard clean-up. The four firms we identified in Edmonton had slightly higher hourly rates, approximately $38.00 per hour, than did the seven firms surveyed in Calgary, where the average was approximately $33.00 per hour. (See Table 3.) It is possible that the difference between the two cities arose simply from the small sample size in Edmonton.

Table 3

Child care

There are two primary methods of providing (commercial) child care: nannies, who come in to the home, and day care. We obtained information about nanny services online and from the newspapers; information about daycare services was obtained from the Yellow Pages.

In Table 4, we provide information about “live-in” and “live-out” nannies in Calgary. Unlike Tables 1-3, we do not present information about individual rates, as we collected 30 observations. Rather, we report the number of observations in each of a number of ranges.

Table 4

The first column in Table 4 represents monthly rates that were offered in advertisements in the Calgary Herald by families who were seeking to hire nannies. The second column represents rates that private nanny agencies charge for placements.

We also obtained some information concerning the cost of nannies in Edmonton. (These data are not reported in tables as we had insufficient responses.) As in Calgary, the one nanny placement service we were able to identify charged $1,510.82 per month; and the hourly rate for (private) live-out nannies were from $8.00 to $16.00 per hour, with an average of approximately $11.75.

With respect to live-in nannies, the private and commercial rates were in agreement, at approximately $1,500 per month, or approximately $8.00 per hour. (Employers are required to pay at least the minimum wage for 44 hours per week, or $1,510.82 per month.) With respect to live-out nannies, however, private rates in Calgary, at $1,360 per month, were significantly less than commercial rates, at $2,220 per month, (or $11.50 per hour).

We suspect that the commercial rates in Calgary are more reliable estimates of the actual costs than are the private. First, the private rates in Edmonton are virtually identical to the commercial rates in Calgary. And, second, although we would anticipate that live-in nannies, who receive room and (some) board, would be paid less than live-out nannies, who have to pay their own room and board, the live-in rates offered in the Calgary newspapers were more than live-out rates.

With respect to day care services, (Table 5), we found that, for the youngest children, there was a significant concentration of fees around $700 per month and another concentration around $800, with an overall average of $720 (pre-toddlers) to $740 (babies) per month in Calgary, (or approximately $4.00 per hour per child), and $630 to $855 per month in Edmonton. As we found only three day care centres that would look after babies in Edmonton, we prefer the Calgary figure. The pre-toddler figure appears to be lower in Edmonton than in Calgary because of the presence of a number of centres associated with the YMCA that provide low-cost care for this group.

Table 5

With respect to older pre-school children, we found that almost half of the agencies charged between $600 and $630 per month, with an overall average of $590 to $625 (approximately $3.00 per hour).

In Table 6, we report day care charges for pre- and after-school care for school-age children in Calgary. It is seen there that the most common rate is $300 per month, with an average across 23 agencies of $280. The two agencies we identified in Edmonton charged $335 and $320, respectively.

Table 6

Home care and meal preparation

Through the Yellow Pages and the internet, we were able to identify six agencies in Calgary that provide generalized home care services, such as meal preparation, light housekeeping, grocery and clothes shopping, grooming and dressing, bed-making, and bathing. Five of these six agencies charged between $21.00 and $23.00 per hour, with the sixth charging $17.95. If the latter is excluded, the average hourly rate was $22.00. We were unable to obtain rates for similar services in Edmonton.

Calgary’s Kerby Center also provided us with a list of six agencies that would prepare meals at home. Five of those six charged between $15.00 and $20.00 per hour, with an average of $17.50. The sixth agency charged $30.00 per hour, but was operated by a nutritionist who would design healthy menus, in addition to preparing meals.

Summary

In this article, we have reported the results of a survey of household services providers in Alberta. Two outcomes are very clear. First, it is inappropriate to use a single, hourly rate to evaluate all such services. Whereas child care services cost approximately $3.00 to $4.00 per hour per child (assuming that nannies care for two children on average), housecleaning services cost more than $25 per hour, and handyman and gardener services cost approximately $33 per hour.

Second, the convention of using $12 to $16 per hour for household services is insupportable. All of the services that were identified in our survey either cost significantly more than that or significantly less.

Proposal

In its publication As Time Goes by . . . Time Use of Canadians (Catalogue 89-544-XPE) Statistics Canada provides data concerning the amounts of time spent on six types of “household work and related activities.” These are: cooking/washing up, house cleaning and laundry, maintenance and repair, other household work, shopping for goods and services, and primary child care. For the purposes of calculating the costs of household services, we propose to combine “cooking/washing up” with “shopping” and evaluate that category at the approximate average rate for home care and meal preparation, $20.00 per hour.

We will combine “maintenance and repair” with “other household work” (a large portion of which consists of “gardening and ground work”) and evaluate the resulting services at the landscaping, snow removal, and handyman services rate of approximately $32.00 per hour.

We will evaluate “house cleaning and laundry” at the rate for housecleaning services. For the purposes of our reports, we propose to use the conservative rate of $25.00 per hour in Calgary and Edmonton, and $20.00 per hour elsewhere.

We will assume that it costs $700 per month to care for each baby, $600 to care for each toddler/pre-school child, and $275 per month to provide after-school care for each primary school-aged child.

Finally, we will continue to assume that replacement workers for the non-childcare services will perform these tasks more efficiently than the plaintiff would have. Specifically, we will assume a 25 percent reduction in the hours requiring replacement to reflect increased productivity on behalf of hired replacements. We do not make this adjustment for the childcare services, since if a child needs (say) three hours of after-school care, there is no opportunity to somehow provide this care in only 2½ hours.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Amelia Lamb has been Economica’s office administrator since 2004.

Estimating non-discriminatory lifetime earnings for young females

by Christopher Bruce and Kelly Rathje

This article first appeared in the spring 2006 issue of the Expert Witness.

A number of judicial decisions have suggested that estimates of the lifetime earnings of young females should be based on data for males. Two arguments have been made in support of this view.

The first argument is that, as the differential between male and female earnings has been falling, incorporating the historical differential will understate the future earnings that young females will achieve once they become established in their careers. The second argument is that it is inappropriate for the courts to institutionalise current wage differentials that are based on discrimination.

The first of these arguments was alluded to in two BC judgments: ([B.I.Z.] v. Sams, [1997] B.C.J. No. 793; and Terracciano v. Etheridge and Fujii, [1997] B.C.S.C. B943125). The latter judgement involved a woman who was aged 16 when injuries from an automobile incident left her a paraplegic. In this judgement, Madam Justice Saunders indicated her preference for using earnings statistics of males to calculate Ms. Terracciano’s without-incident income:

[81] Indeed, it may be as inappropriately discriminatory to discount an award solely on statistics framed on gender as it would be to discount an award on considerations of race or ethnic origin. I am doubtful of the propriety, today, of this Court basing an award of damages on a class characteristic such as gender, instead of individual characteristics or considerations related to behaviour: Toneguzzo-Norvell (Guardian ad litem of) v. Burnaby Hospital, [1994] 1 S.C.R. 114.

The second argument was considered explicitly in the Alberta decision, MacCabe v. Westlock (RCSSD #110 et al [action: 9303 05787]). There, for example, the court accepted the use of income statistics for males to estimate the without-incident potential earnings of a young woman who had been paralysed while still a high school student. The court found that Ms. MacCabe had a without-accident income potential that was well above average. Importantly, the court argued:

[para468] Clearly the evidence establishes that the exceptional individual characteristics of the Plaintiff are such that her abilities would have commanded the equivalent salary of her male counterparts. She would have established a strong attachment to her career. The use of male wage tables is justified. In any event, I am of the view that any award which I grant to the Plaintiff should not and cannot be solely determined by her gender.

[para469] It is entirely inappropriate that any assessment I make continues to reflect historic wage inequities. I cannot agree more with Chief Justice McEachern . . . in Tucker, supra, that the courts must ensure as much as possible that the appropriate weight be given to societal trends in the labour market in order that the future loss of income properly reflects future circumstances. Where I differ is that I will not sanction the “reality” of pay inequity. The societal trend is and must embrace pay equity given our fundamental right to equality which is entrenched in the constitution. . . .

However, these decisions were silent about the possibility that women might earn less than men even after discriminatory practices had been removed. Importantly, for example, the Court of Appeal in MacCabe (9803-0617AC) rejected the trial court’s finding that male contingencies (such as for non-participation, unemployment, and so forth) should be used when estimating Ms. MacCabe’s losses.

[105] In general, tort law and in particular, the quantification of damages necessitates an individual approach. This is where I find the learned trial judge erred. In attempting to rectify potential inequities in the methods for quantifying damages, the learned trial judge neglected to focus on the evidence and the individual actually before her. While principles of equality should inform tort law, the learned trial judge’s application of equitable principles resulted in her ignoring some of the relevant material facts.

[106] In this case, based on the evidence, it was not reasonable to calculate MacCabe’s damages based on male contingencies. MacCabe stated she wanted to have children and would have preferred to stay at home with them for some period. This meant she would not have worked a pattern typical for male physiotherapists. There was no evidence to indicate it was more likely that MacCabe would not have had children and chosen not to take time off from full time paid employment as a physiotherapist. Thus, it would be inappropriate to apply male contingencies to her when there was no evidentiary basis that she would have worked a typical male pattern.

The appellate court in MacCabe recognised that, even in a world in which men and women experienced equality of opportunity, incomes might differ between the sexes if they made different choices. Most importantly, women might choose to take more time off to care for children; might choose to work fewer hours per week or weeks per year; and might retire earlier than men.

If this is true, one approach to predicting the earnings of young women might be to take current earnings data for men and adjust them downward for these differences in contingencies. In this article, we consider the impacts that each of four such contingencies might have on the male/female earnings differential.

Participation rates

The percentage of any group that is either working or available for work at any time is known as the “participation rate.” Primarily because of the impact of child-rearing, women have lower participation rates than do men at virtually every age. Hence, if everything else is equal, women’s earnings in an average year will be lower than men’s in proportion to the differences in participation rates.

Statistics indicate that the best predictor of whether a particular woman will be in the labour force in the future is whether she was in the labour force in the past. In particular, married women who had been working prior to the birth of their first child have a strong tendency to return to work within one to two years of the birth of that child. Nonetheless, there is a large number of women who delay re-entry until their youngest child is of school age. [1]

Also, many authors have detected a strong positive correlation between education level and female participation. That is, the most highly educated women tend to have the strongest attachment to the labour force. Table 1, for example, indicates that 86.4 percent of 25-54 year-old, university-educated women in Alberta participated in the labour force in 2002, compared with 80.7 percent of 25-54 year-olds who had high school education. (Participation rates drop significantly after age 54 due to retirement.)

Table 1

Note that the figures reported in Table 1 reflect the current labour force participation of women. It seems likely, however, that women who are currently in their 20s and 30s will maintain their high participation rates as they age. Therefore, the figures for the older age categories, in Table 1, might be adjusted upwards when projecting the future behaviour of plaintiffs who have not yet reached the age of majority.

Given the figures in Table 1, and recognising that male participation rates are approximately 95 percent for all age and education groups (between 24 and 54), the earnings for females might be estimated by reducing male earnings by the difference between 95 percent and the relevant female labour force participation rate. For example, given the information in Table 1, the earnings for females with post-secondary education could be estimated by reducing the earnings of comparable males by approximately 10 percent. Similarly, earnings for those with high school education might be obtained by reducing male earnings by approximately 15 percent.

Part-time employment

Even when they are in the labour force, women report lower annual incomes than men because they are more likely to work part-time. As Table 2 indicates, in the age group 25-54, approximately 20 to 25 percent of women work part-time, whereas only 2 to 5 percent of men do so. That is, on average, the number of women working part-time is approximately 20 percentage points higher than the number of men. If part-time is interpreted to mean “half time,” this implies that women in the labour force work 10 percent fewer hours than men. Everything else being equal, therefore, this difference suggests that male earnings should be reduced by a further 10 percent, in order to obtain an estimate of female earnings.

Table 2

Hours Worked

There is also evidence to suggest that, even among individuals who work “full-time,” women work fewer hours per week than do men. Table 3 indicates, for example, that women’s “usual hours per week” are about 80 percent of those of men. Furthermore, Sweetman [2] reports that this ratio varies only slightly by education level: in the age group 40-44, for example, the ratio of female to male hours worked is 81 percent for those with high school and 85 percent for those with a bachelor’s degree.

Table 3

It would be double-counting, however, to reduce male earnings by both 10 percent for part-time work and 15 to 20 percent for hours worked, as the latter differential includes the effect of the former. Rather, it appears that, among those individuals who work full time, women work 5 to 10 percent fewer hours than do men. It is this contingency that should be applied to male earnings.

Retirement

It is seen in Table 4 that women retire approximately two years earlier than men, on average. Hence, any estimate of female lifetime earnings will have to take this difference into account.

Table 4

Summary

Even if there was no discrimination in the labour market – that is, even if women received the same hourly wages as men – on average, women’s annual earnings would still be lower than men’s. Among those with high school education, the differential would be as much as 35 percentage points, due to differences in labour force participation rates (15%), propensity to work part-time (10%), and hours worked per week (10%). Among university graduates, the differential would be approximately 25 percentage points.

Accordingly, if it is concluded that women’s attachment to the labour market will not change in the future, women’s average annual earnings cannot be expected to rise above 65 percent (high school graduates) to 75 percent (bachelor’s degrees) of men’s earnings.

Only if women increase the percentage of their time that they devote to the labour market will that 25 to 35 percent differential begin to fall.

Application

How should these statistics be applied? We believe that two broad cases can be distinguished. In the first, the plaintiff was old enough at the time of her injury that it is possible to determine both the occupation she would have entered and the strength of her attachment to the labour market. (This was the situation in MacCabe, for example.) In those cases, information specific to the plaintiff should be used to predict her (non-injury) earning capacity.

In the second case, the plaintiff was young enough that neither her career nor her labour market attachment can be predicted. In such cases, we believe that information about the plaintiff’s family background is sufficient to allow the court to identify approximately what her educational attainment would have been. Census data concerning incomes by education can then be used to predict the plaintiff’s earning capacity.

But, is it census data for females, or for males, that should be used for this purpose? We have argued that, if the court believes either that labour force discrimination will largely disappear over the next few decades, or that the effects of discrimination should not be institutionalised in damage awards, it is male data that should form the basis of the award. However, the information we have presented in this paper suggest that, even in the absence of discrimination, women will earn less than men because of differences in attachment to the labour force. For that reason, we would propose that, for young females, the forecast of earnings capacity should be based on male data; but that those data should be adjusted downwards as we discussed above.

Footnotes

1. C.J. Bruce, Assessment of Personal Injury Damages (Butterworths: Toronto, Vancouver), fourth edition, 2004, page 167. [back to text of article]

2. Arthur Sweetman, 2002. “Working Smarter: Education and Productivity,” The Review of Economic Performance and Social Progress, in: Andrew Sharpe, Executive Director & France St-Hilaire, Vice-President, Research & Keith Banting, Di (ed.), The Review of Economic Performance and Social Progress 2002: Towards a Social Understanding of Productivity, volume 2 Centre for the Study of Living Standards. [back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

Death and Retirement: Allowing for Uncertainty

by Christopher Bruce

This article first appeared in the autumn 2005 issue of the Expert Witness.

Assume that a plaintiff has begun to recuperate following a serious accident. If her injuries stabilize at their current level, she will suffer a loss of earnings of $20,000 per year. If, however, she has a relapse, her losses will increase to $40,000 per year. Her doctors tell you that there is a 50 percent chance that there will be a relapse (and a 50 percent chance that there will be no relapse).

How should the annual value of her loss be calculated? If damages are set equal to $20,000 per year, there is a 50 percent chance that she will be under compensated; whereas if she is paid $40,000, there is a 50 percent chance that she will be over compensated. (And if she is paid some amount between $20,000 and $40,000, there is a 100 percent chance that she will be incorrectly compensated.)

This conundrum, in which there is uncertainty about the outcome of future events, is common in the assessment of personal injury (and fatal accident) damages. Not only is there uncertainty about the future course of the plaintiff’s injuries, as in the example above, we also face uncertainty concerning the age at which the plaintiff will retire, the plaintiff’s life expectancy, the probability that the plaintiff would have (and will be) unemployed, and a host of other factors.

The general approach that virtually all financial experts take in such cases is to calculate the average outcome that would arise from the uncertain event, if the event could be repeated a large number of times. For example, if the injury described above was to be repeated 100 times (for example, if there were 100 plaintiffs with that same injury), we would expect that the plaintiff’s injuries would remain stable in approximately 50 cases, leading to a loss of $20,000 per case. In the other 50 cases, the plaintiff would suffer a relapse and her loss would rise to $40,000. Thus, the total annual loss, across all 100 cases, would be ((50 × $20,000) + (50 × $40,000) =) $3,000,000. The average annual loss would be $30,000; which could also be calculated by multiplying 50% times $20,000 and adding 50 % times $40,000. That is, the average value of a loss can be calculated by multiplying each of the possible losses by its probability and then adding the resulting numbers together.

But, as was noted above, $30,000 is guaranteed to be the “wrong” amount in 100 percent of cases. How, then, can it be justified? One simple answer is this: if the event in question is truly uncertain, the plaintiff should be able to use the $30,000 to purchase insurance that will compensate her fully regardless of which value turns out to be her true loss – either $20,000 or $40,000. The reason for this is that if the insurer issues, say, 100 such policies, it can expect to pay out $20,000 in 50 cases and $40,000 in the other 50, for an average of $30,000. (It will have collected $3,000,000 [= 100 × $30,000] and will have paid out $3,000,000 [= 50 × $20,000 + 50 × $40,000].)

Risk of Mortality

This type of calculation is most commonly used when dealing with the uncertainties associated with mortality. Take the extreme case in which there is a ? probability that a plaintiff will live exactly one year (and then die), a ? probability that he will live exactly two years, and a ? probability that he will live exactly three years. If he would have earned $60,000 per year but has now been left unable to work, his loss can be calculated using the technique described above. That is, there is a ? chance that he has lost one year’s income ($60,000), a ? chance he has lost two years’ income ($120,000), and a ? chance he has lost three years’ income ($180,000); for an average of $120,000 (=? × $60,000 + ? × $120,000 + ? × $180,000).

Alternatively, in such cases, it is sometimes possible to use a “rule of thumb” to estimate the loss. Given the probabilities in the preceding example, it can be shown that, on average, the plaintiff will live two more years before dying. (2 = ? × 1 + ? × 2 + ? × 3) That is, his life expectancy is two years. His expected loss can then be calculated as the sum of his losses over that life expectancy, or $120,000 (= 2 × $60,000). Note, however, that this approximation works best if the losses are approximately the same in each year, as it was here. (If the annual loss is significantly different in the first year than, say, the third year, this approach yields a biased estimate.)

What is clear is that it would be inappropriate to mix together the two calculation techniques. It is not appropriate, for example, to estimate the loss by multiplying each of the first two years’ losses by their associated probabilities and assuming that the loss continues for only two years. That would produce an “estimated” loss of only $60,000 (=? × $60,000 + ? × $120,000), $60,000 less than the true loss.

Retirement Age

The techniques described here can also be used to estimate the effect of uncertainties about the plaintiff’s retirement age. Assume, for example, that there was a ? probability that a 63 year-old plaintiff would have worked for exactly one year (i.e. to his 64th birthday) and then retired, a ? probability he would have worked two years, to his 65th birthday, and a ? probability he would have worked three years, to his 66th birthday. If he would have earned $60,000 per year while working, his loss, again, can be found from the formula: ? × $60,000 + ? × $120,000 + ? × $180,000 = $120,000; or by multiplying the average number of years to retirement by his annual earnings, to produce $120,000 = 2 × $60,000.

As with the mortality example, it would clearly be incorrect to multiply each year’s earnings by the probability it would occur and assume the individual would have retired at the average age, of 65. That would produce an “estimate” of, (? × $60,000 + ? × $120,000 =) $60,000, again, only half of the correct estimate.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Discount Rate Revisited

by Christopher Bruce, Derek Aldridge, Kelly Rathje, and Hugh Finnigan

This article first appeared in the summer 2005 issue of the Expert Witness.

In the Autumn 2000 issue of this newsletter, we conducted an extensive review of the various methods of measuring the real rate of interest, or discount rate, and presented evidence concerning the movement of those measures over the period 1995-2000. (That article is available on our website, at economica.ca/ew53p1.htm.)

That survey was subsequently updated in our Winter 2001/02 and Spring 2003 issues. What we found in both of those updates was that interest rates had begun to fall relative to the historically high levels that had persisted over most of the 1990s.

At the time of our Spring 2003 article, we concluded that the best estimate of the long-run discount rate was 3¼ percent. But we also argued that, as interest rates on short-term bonds and GICs were lower than those on longer term investments, it would be appropriate to employ an interest rate of 2¼ percent on the first five years of any investment.

The primary purpose of this article is to examine nine additional quarters (27 months) of data to determine whether the trend we observed in our earlier articles has continued, or whether a revision in our recommended interest rate is appropriate. We also report on recent changes to Ontario’s mandated discount rate; and we revisit the question of whether forecasts of future interest rates should be based on information about past interest rates or on information about current, long-run interest rates.

Revised Data

Instead of providing tables of data comparable to those presented in our earlier articles, we now present a chart that shows the trend in interest rates since 1995. The complete data set can be found on our web site (see www.economica.ca/ew102p1.htm). Figure 1 shows the trend in real interest rates on government bonds of various term lengths, as well as the rate of return on real rate of return bonds.

Figure 1

Note: We deduct two percentage points from the “nominal” or observed interest rates to reflect inflation anticipated by investors. As the Bank of Canada has managed to keep the core rate of inflation within a small band around this target since the early 1990s, and as it has been the stated intention of not only the Bank of Canada but most other central banks (most notably that of the European Union) to keep the inflation rate at that level, there is now virtual unanimity among investors that two percent will be the long run rate of inflation in Canada. Accordingly, it can be concluded that investors have been acting as if the real rate of interest is the observed, nominal rate less two percent.

The data in Figure 1 indicate that real rates of interest have continued the downward trend that began in 1996/97. Whereas we concluded two years ago that long-term real interest rates were approximately 3¼ percent and short-term rates approximately 2¼ percent; it now appears that real rates have fallen substantially below those levels. In particular, note that the rate of return on 10-year Government of Canada bonds, net of the 2 percent expected rate of inflation, is now below 2 percent and has not exceeded 3¼ percent (our earlier prediction of the “long-term” rate) since early 2002. Even the real rate on long-term (30-year) Government of Canada bonds has fallen below 2½ percent in the most recent quarter. And the rate of return on real rate of return bonds is now below 2 percent and has not been above 3 percent since mid-2003.

Although we do not show the comparable interest rates on guaranteed investment certificates (GICs), we have examined them and they are consistently lower that the rates of return on bonds. For example, the real rates on 1-year GICs have been consistently negative since late-2001, meaning that investments in one-year GICs are not keeping pace with inflation. The real rate on 5-year GICs has been below one percent for all but two of the last eight quarters and has not exceeded two percent since early 2002.

Forecasting the Real Rate of Interest

For some time now, Economica has been arguing that current interest rates, net of the two percent expected rate of inflation, provide the most reliable basis on which to predict future interest rates. Some other economic experts in Western Canada disagree with us, and base their forecasts on information about historical interest rates. We consider their position to be unjustified. We explain why here:

The continued dramatic fall in interest rates.

First, as a glance at Figure 1 will indicate, the real rate of interest in the last decade has fallen continuously and dramatically: the long-term rate has fallen from about 7 percent to below 2½, while the short-term rate has fallen from about 6 percent to below 1 percent. Clearly, any prediction that was based on an average of the figures in this period (or any other period extending back to the early 1980s) would seriously overstate the rates that will be available to a plaintiff investing his or her award today.

It is important to note that although rates are low by historic standards, today’s investors who seek the security of investments comparable to government bonds and GICs cannot avoid these low rates. The fact that average interest rates over the last 30 years were much higher does not help today’s plaintiff-investor. Even if one believed that long-term real rates will rebound to (say) 3.5 percent in the next 5-10 years, the best that today’s investor will be able to do is place his funds in 5-10 year investments earning 1.5-2 percent and then hopefully reinvest at the higher 3.5 percent rate. This of course will not yield nearly the same result as if he had been able to invest at 3.5 percent right from the start.

Economic theory.

Second, the fall in real interest rates is consistent with macroeconomic theory. Specifically, many macroeconomists are arguing that the relatively high real interest rates that were observed in the 1980s resulted from the high volatility in expectations concerning the nominal rate of inflation. That is, when inflation is unpredictable, investors who place their funds in long-term bonds face a considerable amount of uncertainty. If inflation proves to be higher than expected, the real rate of return that they realise may be very low or even negative. To compensate for this uncertainty, investors demand a relatively high expected rate of return. Conversely, when inflation becomes predictable, as has happened in the last five to ten years, investors face much less uncertainty and are willing to accept lower real rates of return. Accordingly, there is sound reason to believe that, as long as the Bank of Canada maintains its current course[*] (which it is expected to do), both nominal inflation and real interest rates will remain at the low levels that have been observed recently.

Furthermore, most economists believe that real interest rates will be higher in a period in which governments run large deficits – and, therefore, have to borrow heavily – than in those in which revenues exceed expenditures. As is well known, although the Canadian government ran sizeable deficits in the late 1980s and 1990s, it has now adopted a goal of achieving a balanced (or, even, surplus) budget. Again, this leads us to believe that real interest rates will be lower in the future than they were in the 1980s and 1990s.

The actions of large, institutional investors.

Most of the bonds reported in Figure 1 are purchased by large, institutional investors, such as pension funds. That these investors are willing to purchase, say, ten-year bonds paying a real rate of approximately two percent, or real rate of return bonds that are paying below two percent (as of the second quarter of 2005) indicates that they do not anticipate that they can obtain better rates of return on other secure investments. That is, regardless of whether private investors actually purchase the government bonds identified in Figure 1, the returns on those bonds indicate that the institutions that base millions of dollars of investment on their predictions of the financial markets are forecasting that real rates of return will remain low in the foreseeable future. (If expert institutional investors anticipated that rates on secure investments will average, say 3½ percent over the next ten years, then they would not buy bonds that pay only two percent, and the Government of Canada would be forced to adjust its bond rates.)

A future increase in rates will have little effect on most plaintiffs.

Even if real interest rates were to increase substantially in the next ten years or so, (against expectations), that would have relatively little effect on the investments of many plaintiffs, for two reasons. First, it is the rates of return that are available today that will dictate the average rate that plaintiffs will be able to obtain over at least the first 5-10 years of the period of their loss. As noted above, if rates increase in the future, the best that today’s plaintiff can do is place his funds in 5-10 year investments at today’s low rates and then later reinvest at the (hopefully) higher future rates. Even if rates return to their historical average, this investment approach will still yield an average rate of return that is below the historical average. Second, since most plaintiffs will need to begin consuming their award immediately (to replace their lost income and fund their costs of care), the most substantial portion of the interest that they will earn on the investment of their awards will occur in the first half of their period of loss, before they have drawn down much of their capital (that is, during the period in which they are funding most of their annual losses from interest income). If the period of loss is 20 years or less (like most plaintiffs), then the interest they earn in the first ten years will have a much greater impact on their investments than the interest they earn in the next ten years. Thus a return to higher interest rates after 10 years or so will have only a small impact on these plaintiffs. For plaintiffs with a period of loss that is only ten years or less, future increases in interest rates will have almost no effect on their investments.

Note that one implication of relying heavily on current interest rates is that it requires that we change our discount rate assumption more frequently than if we simply relied on historical averages. However, making changes to our discount rate assumption does not imply a weakness in our methodology. To do otherwise would result in us using interest rates that we know are inconsistent with the rates that are actually available to plaintiffs. Even if one believed that over the long-term, real interest rates will average (say) 3 or 3½ percent, it does not necessarily follow that our discount rate assumptions should remain fixed. This is because (as we explained above), the rates of return over the next ten or so years will have a substantial impact on the investment results of most plaintiffs. Thus, it is important to account for the rates that are available to plaintiffs now, as well as the rates that will be available (on average) over the long-term.

Ontario’s mandated discount rate

Following a detailed review, Ontario (in year 2000) revised its regulations concerning its mandated discount rate. The new methodology that was chosen yields a discount rate of 1.5 percent for the first fifteen years of any award and 2.5 percent for all years beyond that point. Specifically, Ontario’s revised regulation 53.09 states:

53.09 (1) The discount rate to be used in determining the amount of an award in respect of future pecuniary damages, to the extent that it reflects the difference between estimated investment and price inflation rates, is,

(a) for the 15-year period that follows the start of the trial, the average of the value for the last Wednesday in each month of the real rate of interest on long-term Government of Canada real return bonds (Series V121808, formerly Series B113911), as published in the Bank of Canada Weekly Financial Statistics for the 12 months ending on August 31 in the year before the year in which the trial begins, less 1 per cent and rounded to the nearest ¼ per cent; and

(b) for any later period covered by the award, 2.5 per cent per year. O. Reg. 488/99, s. 2; O. Reg. 263/03, s. 4 (1).

The average month-end rate of return on real rate of interest bonds from September 2003 through August 2004 was 2.58 percent. Deducting one percentage point and rounding to the nearest quarter percent yields a mandated discount rate of 1.5 percent for trials that occur in 2005. Given the rates on real rate of interest bonds since September 2005, we can also be almost certain that Ontario’s mandated discount rate (for the first 15 years of loss) will fall to 1.0 percent for trials that occur in 2006.

As discussed in an earlier article (see “Ontario’s Mandated Discount Rate – Rule 53.09(1)” that appeared in the Autumn 2000 issue of the Expert Witness), we have a concern with Ontario’s policy of deducting one percentage point from the one-year average of the rate on real rate of return bonds. What is perhaps more interesting is their finding that 2.5 percent reflects the long-term real rate of interest. This rate is lower than the long-term rate we have been using, though it is consistent with the current rate on long-term Government of Canada bonds.

Conclusion

Our review of the empirical and theoretical sources suggests that it would be appropriate to adjust our discount rate assumption. We also propose to make a change in how we apply our discount rate assumptions in our calculations. Whereas we previously assumed that the real rate of return on all of a plaintiff’s investments would be 2.25 percent for the first five years and 3.25 percent thereafter, we now assume that for income required in the first few years, an investment will be made at short-term rates, while for income needed in the more distant future, investments will be made that will earn the predicted long-term rates. Below we will further explain the approach we will use for our calculations, and then we will outline the discount rate assumptions we will use.

To illustrate the effect of this approach, note that a child plaintiff who will not experience a loss of income for ten years will manage to earn a relatively high rate of return because he will be able to invest in “long-term” investments, and he will be more likely to benefit from possible future increases in interest rates. On the other hand, an older plaintiff who will experience a loss of income over the next five years only, will not be able to benefit from long-term investments or from possible increases in interest rates. She will face the low rates available on short-term investments.

Consider the following example of a plaintiff who will incur a loss of income of $10,000 seven years from now. If she is compensated for the future loss today, she could use her award to purchase a government bond with a seven-year term, and not touch the award until it is needed in seven years, when the bond matures. We will see in Table 1 (below) that such a bond has been paying about 2.2 percent, net of inflation over the last two years. This plaintiff will not need to invest at the lower rates offered by shorter-term assets, but she will also not benefit from the rates offered on longer-term bonds, nor will she benefit from a possible future increase in interest rates. To invest her award in secure assets she faces two options: she can make successive short-term investments in hopes that the rates will increase in the near future, or she can make a longer-term (seven-year) investment and accept the interest rate that is available to her. Given her investment-obligations as a plaintiff, we would expect that that latter option would be more appropriate. Even if she chose the former option we would not expect her overall return to improve, unless we knew that rates would increase in the near future. (And if it was known that rates will increase in the near future, then this increase would already be reflected in the current rate of return offered on seven-year bonds.)

For our calculations we will choose an average rate of return that will be earned on investments that are held until each future year of the period of loss. For example, we assume that the portion of the plaintiff’s award that is held for seven years to compensate her for her loss in year 7 will earn an average rate of return of 2.2 percent. Similarly, we assume that the portion of the plaintiff’s award that is held for 15 years to compensate her for her loss in year 15 will earn an average rate of return of 3.0 percent. And so forth.

To obtain the discount rates for use in our calculations, we propose to take an average of the most recent two years of quarterly interest rates (using two years of monthly rates would yield the same results), for the Government of Canada benchmark bond yields for 2-, 3-, 5-, 7-, 10-year, and long-term bonds. After deducting two percentage points for anticipated inflation and rounding to the nearest tenth of a percent, this will give us our assumed real interest rates for various future terms. We assume the one-year rate is the same as the reported two-year rate, and for the “in-between” years we simply extrapolate. We assume that the long-term rate applies to year 15 and beyond. The rates that result from this approach are shown in Table 1.

Table 1

Note that we believe that the rates proposed in Table 1 (above) remain conservative (that is, they may understate future losses) since they reflect interest rates that have been available over the past two years, instead of only the rates that are available now (even though only the rates available now can be assured to today’s investor).

Footnotes

* Since approximately December 1993, the Bank of Canada has successfully maintained a policy of keeping inflation at a two percent target (the midpoint of its 1-3 percent target range). [back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

From 2003 through 2005, Hugh Finnigan was a consulting economist at Economica, with a Master of Arts degree from the University of Calgary.

Estimating the Impact of Mid-Career Retraining

by Christopher Bruce and Derek Aldridge

This article first appeared in the summer 2005 issue of the Expert Witness.

Vocational psychologists commonly recommend that injured plaintiffs retrain for a new occupation. A problem that this creates for the financial expert is that it is not clear what the individual’s starting wage will be once the training period has been completed.

Specifically, all of our data concerning incomes by occupation suggest that individuals’ incomes increase as they age (usually until their mid-40s). If we assume that this increase occurs either because individuals gain valuable experience in their occupations or because they move up “career ladders” as they age, individuals who change careers will find themselves starting at lower wages than would be suggested by their ages.

For example, Table 1 reports incomes by age (for Alberta males) for two occupations that are commonly recommended as retraining possibilities: partsman (NOC-S B572) and drafting technologist/technician (NOC-S C153). It can be seen there that annual incomes rise continuously from the youngest age group, 20-25, to the second oldest group, 45-54, before declining slightly.

Table 1

If it has been recommended that, say, a 40 year-old male retrain to enter one of these occupations, the economic expert is faced with determining which of the income levels from Table 1 best represents the income at which the plaintiff will begin his new career. If experience in the occupation, or movement along a career ladder, are important determinants of income, then we would expect that the newly-trained worker would begin at one of the lower incomes suggested by the census data.

Perhaps with his greater maturity the 40 year-old would not start at the income level of a 20-25 year-old; but with no experience in this occupation, it seems unlikely that he would start at the income of a 40 year-old. Fortunately, statistical evidence has recently become available that can help us to determine the impact of a change in career.

Most importantly, Arthur Goldsmith and Jonathan Veum[*] have used a detailed survey that followed 1400 young workers from 1979 to 1996 to compare the effects of additional years of experience on wages when individuals: remained in the same occupation and industry, remained in the same occupation but moved between industries, remained in the same industry but changed occupations, and changed both occupations and industries.

What they found was that the value that was placed on previous experience was approximately the same for all individuals except those that had changed both occupation and industry. In their words:

…experience acquired while a real estate agent is
valued similarly as tenure at other occupations, such as
accounting, within the real estate industry. In addition, the
experience as a real estate agent is valued similarly to
tenure at other industries, such as the pharmaceutical
industry, if continuing in the occupation of sales. If the
real estate agent becomes an accountant in the pharmaceutical
industry, however, the experience as a real estate agent is
of less value than that within accounting or the
pharmaceutical industry. (p. 442)

Referring to the examples in Table 1, Goldsmith and Veum’s findings suggest that the 40 year-old who retrains as a partsman may be able to earn an income comparable to that of a 40 year-old partsman with 15 years experience, if the retrained individual remains within his previous industry. For example, if an individual who had previously worked on oil rigs becomes a partsman in a shop that provides equipment to oil rigs, he can be expected to obtain a starting salary much higher than he would have obtained if he had become a partsman in an automobile dealership.

We would suggest that Goldsmith and Veum’s findings be interpreted in the following way: First, if the plaintiff’s injuries require that he/she retrain for both a new occupation and a new industry, the starting salary should (normally) be selected from the 25-29 year-old census category. This allows for the finding that previous experience is of limited importance, while avoiding the confounding effect that the incomes of 20-24 year-olds will be biased downwards by issues of immaturity.

Second, if the plaintiff’s injuries require that he/she retrain for a new occupation in the same industry he/she worked in prior to the accident, it should be assumed that the experience gained in the previous occupation will be, in large part, transferable to the new occupation. This does not necessarily mean that a 40 year-old plaintiff should be assumed to start his/her new career at the income level of an experienced 40 year-old in that occupation. Most importantly, plaintiffs often experience residual mental and physical difficulties that will reduce their earning capacity below that of the individuals represented in the census data. Also, however, it must be recognised that Goldsmith and Veum’s results referred to individuals who had changed occupations voluntarily; that is, to individuals who had chosen new occupations that met both their interests and their aptitudes. Plaintiffs often are not provided with that opportunity. As the new occupations for which they are retraining are not those that they had chosen when they were healthy, it is possible that they will not perform as well as individuals who had chosen those occupations voluntarily.

Finally, it must be recognised that Goldsmith and Veum’s findings are only suggestive. They can only be interpreted to indicate that, on average, when uninjured individuals make mid-career changes within a given occupation or industry, they tend not to suffer appreciable losses of earnings. They provide less information about specific individuals, particularly those who make significant career changes because of injury. We strongly suggest, therefore, that counsel request an opinion from a vocational psychologist concerning the impact that the injuries suffered by the particular plaintiff in question will have on that individual’s earning capacity. Specifically, if the psychologist recommends that the plaintiff retrain for a different occupation or industry, does the psychologist believe that that individual will be able to begin the new career at a salary that is comparable to other individuals of his/her age? Or will the plaintiff be forced to enter the new career at a salary lower than that of otherwise comparable individuals?

Footnotes

* Goldsmith, A.H. and J.R. Veum (2002). Wages and the Composition of Experience. Southern Economic Journal, 69(2), 429-443. [back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

The Impact of Disability on Earnings: Reliable Data

by Christopher Bruce

This article first appeared in the spring 2005 issue of the Expert Witness, though it is based on a paper that Dr. Bruce presented at the Canadian Bar Association national conference, “Hot Topics in Litigation,” in Toronto on April 16, 2005.

In a previous article in this newsletter, “The Reliability of Statistical Evidence Concerning the Impact of Disability,” I argued that the courts should be very cautious when relying on evidence concerning the effects of disability on earnings. In this paper, I summarise some of the statistics on this factor that I consider to be reliable.

Criteria

Before a data set can be used with confidence, it must meet two criteria. First, the number of observations must be large enough that one can be certain that a representative sample has been drawn of all relevant populations. This means, first, that the sample must include individuals both with and without the disability in question; and, second, that the sample of the disabled population must be large enough that the results are not affected by accidental inclusion of unrepresentative individuals. For example, if one Canadian in a thousand has a particular disability, it might be necessary to survey one Canadian in three hundred in order to obtain a sample of sufficient size (in this case, one hundred) to ensure that a few “outliers” did not affect the statistical findings. Second, the observations must be drawn in a sufficiently random manner that the researcher can be confident that the individuals in the sample are representative of the population of interest. For example, it might not be appropriate to rely on a follow up survey of one hundred patients from a hospital that attracted an unrepresentative group of patients – unless the plaintiff was known to fall into that group.

My experience suggests that there are two sources of data that best meet these criteria: data sets constructed by national statistical agencies, such as Statistics Canada and the U.S. Bureau of Labor Statistics, and certain of the large, longitudinal studies – such as the National Longitudinal Survey or the Panel Study on Income Dynamics – that have been conducted by reputable research institutes in the United States. When employed by well-trained researchers, using appropriate statistical techniques, these data provide information on which the courts can rely. In the following sections, I summarise some of the studies that I believe meet the criteria set out above.

Spinal Cord Injuries

One of the most widely-studied groups of victims is those who have suffered from spinal cord injuries – paraplegia and quadriplegia. Fortunately, within the dozens of studies that have been conducted, there is a small set that employ large, reliably-drawn sets of data and appropriate statistical techniques. I particularly recommend three of these:

  • Bruce, Christopher (2004) Assessment of Personal Injury Damages, 4th Edition, (Butterworths: Toronto), Chapter 8 (with Hao Wang).
  • Krause, J. Stuart, et. al. (1999) “Employment After Spinal Cord Injury: An Analysis of Cases from the Model Spinal Cord Injury Systems” Archives of Physical Medicine and Rehabilitation 80, November, pp. 1492-1500.
  • Krueger, Alan, and Douglas Kruse (1995) Labor Market Effects of Spinal Cord Injuries in the Dawn of the Computer Age, (National Bureau of Economic Research: Cambridge, MA), Working Paper 5302.

The data in my book are the most representative of the total population (both disabled and non-disabled) as they are taken from the 1990 Canadian census. However, as the census identified individuals by impact of disability rather than cause, I was forced to use “unable to walk or carry light objects” as my disability category, rather than “spinal cord injured.” The Krause et. al. and Krueger and Kruse data were less representative than mine, as the U.S. census does not provide detailed information about disabled individuals. Instead, both studies relied on concerted efforts by research groups to gather data without government assistance. This meant that, although both were able to obtain large data sets that specifically concerned individuals with spinal cord injuries, they were unable to ensure that their data were truly randomly drawn.

Nevertheless, the three studies provide compelling evidence concerning the impact of spinal cord injuries on labour market outcomes. First, because of the size and breadth of my sample, I was able to divide my data between those who had been injured before they were 20 years old and those who were injured later. This allowed me to investigate the effect that “inability to walk” had on the educational attainment of young disabled individuals. I found that non-disabled individuals were approximately twice as likely to complete a university education as were disabled; and were correspondingly much less likely to drop out of high school. (See Table 1.)

Table 1

Conversely, by restricting a second sample to those who became disabled after they had completed their education, I was able to investigate the effect of “inability to walk/carry” on earnings, holding education constant. Here I found, first, that the disabled were much more likely than the non-disabled to be earning either no income or subsistence wages. Among those with high school education, for example, 26.3 percent of disabled males and 68.7 percent of disabled females earned less than $5,000 per year (in 1990), whereas the comparable figures for the non-disabled were only 4.4 percent and 20.1 percent, respectively. (See Table 2.)

Table 2

Second, there was a dramatic difference between the probabilities that the disabled and non-disabled would have earnings in the highest income category. Even after “correcting” for age, sex, educational level, province of residence and a number of other variables, I found that those who were unable to walk were less than half as likely to earn over $30,000 as were those who reported no disability.

Krause, et. al., lacking data concerning the non-disabled, could only comment on the factors that affected the probability that a spinal cord injured individual would be able to find employment. Most importantly, they found that if the individual had been employed at the time of the injury, he/she was almost four times as likely to be working after the injury as if he/she had not been so-employed; and that those spinal cord injured with a university education were three times as likely to be employed as were those with less than a high school education.

Krueger and Kruse were able to provide information concerning both employment and earnings. Perhaps their most important finding was that, even after allowing for age, sex, education, race, and marital status, victims of spinal cord injury were much less likely to be employed than were the non-disabled. Specifically, whereas approximately 75 percent of the non-disabled in their study were employed, the comparable probabilities for the sub-categories of spinal cord injury were: incomplete paraplegic, 42.2 percent, complete paraplegic, 29.5 percent, incomplete quadriplegic, 27.6 percent, and complete quadriplegic, 22.2 percent. That is, they found that the most common outcome of spinal cord injury was that the victim became competitively unemployable.

They were also able to confirm Krause’s finding that individuals with university education were three to four times more likely to be working after injury than were those with high school education or less. Whereas only 10 to 15 percent of those in the latter group were employed, 50 to 60 percent of those in the former were working post-injury.

With respect to those who did manage to obtain employment, Krueger and Kruse found that the earnings of the spinal cord injured were approximately 40 percent lower than the earnings of a matched set of non-disabled individuals. For each injured individual who had been working before his/her injury, Krueger and Kruse identified a comparable individual at the same workplace who had not been injured. They then compared the earnings of the injured and non-injured workers approximately five years after the injury occurred. Of this differential, approximately half arose because the injured parties worked fewer hours per week and half because they had lower hourly earnings.

Chronic Pain

In a recent paper, Crook et. al. ? Determinants of Occupational Disability Following a Low Back Injury: A Critical Review of the Literature,” Journal of Occupational Rehabilitation, 12 (4), December 2002, 277-295. surveyed the entire literature on the effects of chronic pain. Interestingly for the argument I made in my previous paper, they found that less than one percent of research studies they identified (19 out of 2,170) met a basic set of criteria for methodological reliability. Those studies reported that victims returned to work more quickly (following the onset of chronic pain) the younger they were, the greater was the availability of job modifications, the sooner they were referred for treatment, the less pain they had from standing and lying, and the greater was their flexibility. Males returned to work more quickly than females; and individuals with previous hospitalization or previous episodes of back pain took longer to return to work than did those without such histories.

Crook’s survey also found that females and older workers were the most likely groups not to return to work at all. Other factors making it more likely that patients would not return to work were: relatively large numbers of children at home and a lack of control over the workplace.

Finally, pain was more likely to be persistent, the older was the worker and the greater was the degree of depression.

Visually Impaired/Blind

I was able to identify only two studies of the visually impaired that provided data from large, statistically reliable sources.

  • Bruce, Christopher (2004) Assessment of Personal Injury Damages, 4th Edition, (Butterworths: Toronto), Chapter 8 (with Hao Wang).
  • Blackorby, Jose, and Mary Wagner, (1996), “Longitudinal Postschool Outcomes of Youth With Disabilities: Findings from the National Longitudinal Transition Study,” Exceptional Children 62 (5), 399-413.

The first of these is my own study, using Canadian census data for individuals who reported that they had difficulty, or were completely unable, to see “ordinary newsprint, (with glasses or contact lenses if usually worn).” The Blackorby and Wagner study is based on a survey of over 8,000 students who had been enrolled in special education classes at high schools across the United States and who had been interviewed between three and five years after completing secondary school. Although this group included individuals with other disabilities, it also included a substantial portion who reported “visual impairment.”

The main findings from my research are reported in Tables 3 and 4. There it is seen that although those with a seeing disability are only slightly less likely to complete advanced education than are the non-disabled, the former are much more likely to be found in the lower portion of the income distribution than are the latter.

Table 3

Table 4

These findings were confirmed in large part by Blackorby and Wagner. They found, for example, that 57 percent of visually impaired students had attended some form of postsecondary school, only slightly less than the 68 percent of non-disabled students. Nevertheless, they found that only 29.4 percent of the visually impaired were competitively employed – less than half of the 69 percent figure for the non-disabled.

Hearing Impaired/Deaf

The two most reliable sources of information about the hearing impaired are the same as for the visually impaired:

  • Bruce, Christopher (2004) Assessment of Personal Injury Damages, 4th Edition, (Butterworths: Toronto), Chapter 8 (with Hao Wang).
  • Blackorby, Jose, and Mary Wagner, (1996), “Longitudinal Postschool Outcomes of Youth With Disabilities: Findings from the National Longitudinal Transition Study,” Exceptional Children 62 (5), 399-413.

The main findings from my research are reported in Tables 5 and 6. As with the visually impaired, it is seen that those with a hearing disability are only slightly less likely to complete advanced education than are the non-disabled. The impact of hearing disabilities on income are much less, however, than is the impact of visual disabilities.

Table 5

Table 6

Again, these findings were confirmed in large part by Blackorby and Wagner. They found, for example, that 60 percent of hearing impaired students had attended some form of postsecondary school, only slightly less than the 68 percent of non-disabled students (and slightly more than the 57 percent of visually impaired). Similarly, they found that only 43.5 percent of the hearing impaired were competitively employed – almost 50 percent more than among the visually impaired.

Brain Injury

Two studies of the effects of brain injury appear to be based on large, representative samples. They are:

  • Dikmen, S. et al. (1994). “Employment Following Traumatic Head Injuries,” Archives of Neurology, 51 (2), 177-186.
  • Roberts, A.H. (1970) Severe Accidental Head Injury: An Assessment of Long-Term Prognosis (London: Macmillan)

Both studies provide data concerning the probability of returning to work, given various measures of brain damage that are commonly available from medical reports. (See Tables 7 and 8.) As would be expected, the more severe is the injury, the lower is the probability that the individual will return to work. Also, the Roberts study found that workers were less likely to return to work, the older they were.

Table 7

Table 8

Discussion

In my experience, most medical/psychological evidence concerning the impact of disabilities on education, employment, and earnings takes two forms. First, the expert offers an opinion concerning the possibility that the plaintiff will be able to return to competitive employment. Second, the expert may offer an opinion concerning the (set of) occupation(s) for which the plaintiff can re-train if he/she cannot return to his/her pre-injury occupation. Typically, in the former case, no mention is made of the probability that the plaintiff will enter competitive employment, and in the latter case, no mention is made of the possibility that the plaintiff will work fewer hours than before the accident. Furthermore, in neither case will the expert make reference to the studies that provide statistics concerning these probabilities. Yet, as I have argued here, if one is diligent, and cautious, it is possible to identify numerous studies that provide reliable information on many aspects of the disability-employment relationship.

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This article is based on a paper that Dr. Bruce presented at the Canadian Bar Association national conference, “Hot Topics in Litigation,” in Toronto on April 16, 2005.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Reliability of Statistical Evidence Concerning the Impact of Disability

by Christopher Bruce

This article first appeared in the winter 2004 issue of the Expert Witness.

Expert witnesses often testify that their experience, or the latest research, leads them to believe that a plaintiff’s injuries will have certain long-term physical, educational, or employment consequences. For example, the plaintiff’s injuries are predicted to worsen, or improve, along some projected time line. Or those injuries are expected to affect the probability that the plaintiff will be able to complete a planned educational program or enter a preferred occupation. Or an opinion will be given concerning the effect that certain disabilities will have on the income that the plaintiff will be able to earn.

When listening to such testimony, I am often reminded of Benjamin Disraeli’s famous complaint that “there are three kinds of lies: lies, damn lies, and statistics.” Expert testimony – particularly expert testimony with respect to the application of medical statistics to the determination of damages in personal injury cases – gives rise to three alternative interpretations that might be attached to Disraeli’s adage.

First, there is the sense in which I suspect Disraeli himself meant his quote: as a complaint that laypeople – judges and lawyers in this case, politicians in his – often find the (statistical) testimony of expert witnesses to be so confusing that they have difficulty distinguishing fact from fiction. That is, his was a call for more clarity; less use of obscure, technical language.

A second version might be recast as: there are “liars, damn liars, and those who abuse statistics.” This is a complaint against those who intentionally twist the interpretation of statistics, hoping either that the opposing expert has insufficient statistical knowledge to be able to recognise the deception, or that the court will have insufficient expertise to be able to determine which of the experts is telling the truth.

Finally, the sense in which Disraeli’s dictum is of greatest relevance to legal advocacy might be restated as: there are “liars, damn liars, and those who misuse statistics.” By this I mean the situation in which “experts” have insufficient knowledge of statistical analysis to realize that they have misunderstood or misrepresented the data that they are citing. My experience suggests both that this situation occurs with depressing frequency in personal injury cases, particularly with respect to medical statistics; and that opposing counsel allow these “misused” statistics to go unchallenged far too often.

The purpose of this paper will be to assist the courts to recognise the sources of statistical “misuse” and to institute methods of responding to the errors that arise. In a second paper, to be published in the next issue of the Expert Witness, I will report a number of statistics concerning the impact of disabilities on earning capacity, taken from sources that use reliable statistical techniques.

Sources of Statistical “Misuse”

There are three reasons why statistical evidence concerning the impact of disabilities on earnings might not be reliable. First, the expert may be basing his/her conclusions on past experience treating patients similar to the plaintiff, without taking into account the statistical uncertainties inherent in such an approach. Second, the expert, due to inadequacies in his or her own statistical training, may have misinterpreted data produced by a third party. Third, the expert may not have recognised that the data he or she is using to develop a prognosis were themselves collected or reported using unreliable statistical techniques. Examples of each of these types of error are discussed in this section.

1. The Expert’s Experience May Not Be Reliable

In many cases, experts drawn from the specialties that treat plaintiffs’ injuries – doctors, psychologists, physiotherapists, etc – rely upon their past experiences dealing with patients similar to the plaintiff to predict the impact that the plaintiffs’ injuries will have on his/her future ability to earn income. There are many reasons why the court should be reluctant to rely on this experiential evidence:

1. The plaintiff may not be representative of the patients that the medical expert normally treats: thus, the expert’s experience may not transfer easily to the plaintiff’s situation. For example, if the expert lives in a large city and the plaintiff comes from a rural area, the expert may not be familiar with the impact that a particular type of injury will have on the plaintiff’s ability to work on a farm. Or if the expert normally treats working-age patients, he/she may not be familiar with the impact of a particular type of disability on a senior or a minor.

2. If the medical expert has treated only a small number of individuals like the plaintiff, the sample size may be too small to draw statistically reliable inferences. For example, even a doctor who specialises in spinal cord injuries may have treated only a small number of quadriplegics. His/her experience with such a small number will provide only limited information concerning the plaintiff.

3. Even if the medical expert has treated a relatively large number of individuals like the plaintiff over his/her career, if the recommended treatment for those individuals has changed significantly recently, the expert may have treated only a small sample since that change. Again, the number of patients receiving the new treatment may not be sufficient to draw reliable inferences.

4. Often, the medical expert has been asked to comment on the impact that a disability has on employment, schooling, or earnings. As these are non-medical outcomes, the expert may not have systematically monitored them. Thus, the sample on which his/her information is based may be biased. For example, those patients who have adjusted well to their injuries, and who have returned to work, may be less likely to return to a doctor or psychologist for further treatment than those who have had difficulty adjusting. In this case, the doctor/psychologist may have developed an overly pessimistic view of the effects of the injury.

5. If the harm to the plaintiff is expected to continue for decades into the future and the medical expert has not been in practice long enough to have experience with patients whose treatment has continued for that length of time, the expert’s experience may not be reliable for predicting long-term consequences.

2. “Expert” Interpretation of Statistical Studies May Not be Reliable

When the expert attempts to supplement information drawn from his/her own experience with information drawn from studies conducted by third parties, a new set of problems arises. Specifically, the expert may lack sufficient knowledge or experience to be able to interpret statistical studies correctly:

1. The expert may have insufficient experience in the field to recognise deficiencies in the data. Many medical studies, for example, use a definition of “unemployment” that differs from that which is used by agencies such as Statistics Canada. The unsuspecting reader, who tried to compare the statistics drawn from the former with those drawn from the latter, could reach erroneous conclusions. Indeed, even within a reliable agency, such as Statistics Canada, similar-sounding names are often used to refer to quite different concepts. One must be careful, for example, to distinguish between “constant” and “current dollar” wages, between “net” and “gross” income, and between “real” and “nominal” interest rates. Failure to recognise these differences can lead to serious errors.

2. Because there is a lack of reliable data for predicting the effects of disability on labour market outcomes, experts are often forced to rely on data that were collected for other purposes. In many cases, this leads to the inappropriate use of such data. For example, doctors often use the American Medical Association “Guides to the Evaluation of Permanent Impairment” to calculate an index of the percentage of “whole body function” that has been lost due to an injury. Loss of an eye, for example, might be considered to reduce the patient’s “whole body” physical capacity by 25 percent.

Although the AMA did not design this index as a method of predicting the impact of disability on earnings, in the 1960’s and 1970’s it became common for experts to argue that a 25 percent reduction in whole body functioning implied a 25 percent reduction in earning capacity. Yet the connection between, say, loss of an eye or loss of a foot on the one hand, and loss of earnings capacity on the other is a tenuous one at best. Whereas loss of an eye could end the career of a professional athlete, for example, it might have very little impact on the career of an economist or lawyer.

Similarly, the rating system developed by Statistics Canada to categorise disabilities as mild, moderate, or severe yields statistics that are of very little value for predicting the effect of disability on the earnings of individuals within specific occupations. Yet many experts are currently using these statistics to make predictions of this nature.

3. The expert’s training in statistical analysis may be insufficient to allow him/her to distinguish reliable studies from unreliable ones. For example, studies that attempt to draw a connection between disabilities and labour market measures (such as income and employment) commonly rely on unsophisticated statistical techniques, making their conclusions very unreliable. Expert witnesses who are not well trained in statistical analysis may be unable to distinguish reliable studies from unreliable ones.

3. Published Studies May Not be Reliable

The most important problem facing the expert who wishes to predict the effect that disabilities will have on earning capacity is that many (if not most) of the statistical studies that have been published on this topic are unreliable. Some of the most important problems of which the courts should be aware include:

1. Many studies of the impact of disability on employment rely on very small samples. For example, it is not uncommon for articles on medical issues to study as few as 10 or 20 patients. Yet it is well known to statisticians that, in order to avoid the problem that “outliers” will bias statistical findings, it is usually necessary to have hundreds of observations.

2. Before the findings from a survey can reliably be projected to the population in general, it is crucial to ensure that the survey group is chosen in such a way as to be representative of the “population.” Many medical studies survey the patients from a single hospital or clinic, for example. But the findings of such a survey cannot reliably be projected to the general population if that hospital or clinic draws only from a sub-set of the population – for example, only from a relatively wealthy district or only from an urban population. And studies that attempt to contact patients many years after treatment may be biased in the sense that it may be easier to locate certain sub-sets of the group than others. For example, those paraplegics who have had the greatest success adjusting to their condition may be the ones who are most likely to have moved from the addresses they had at the time of admission to hospital and, therefore, may be the most difficult to reach at the time of the survey.

3. Although there are multiple factors that influence the effect of disability on employment and earnings, studies often collect information on only a small sample of these factors. For example, if older individuals are more likely to suffer from a particular disability (like arthritis) than are younger individuals, a data set that did not provide information about the ages of the individuals surveyed might appear to suggest that individuals with that disability earn higher average incomes than those who are not disabled (because individuals’ incomes tend to rise with age). Similarly, studies may overestimate the impact of a disability if more low-income than high-income individuals suffer from that disability.

4. Statistical studies can only show that variables – for example, disability and earnings – are correlated: they cannot show that one “causes” the other. That is, it is not clear whether disability causes low earnings, or whether occupations with low earnings have high accident rates. Labourers, for example, are more likely to experience on-the-job accidents than are office workers. If office workers earn more than labourers, data may appear to suggest that job-related accidents “cause” a significant reduction in earnings “because” those who have been injured earn less than the average person in the population. The more appropriate interpretation may have been that it was low income that had “caused” the accidents – that is, that it was the occupations with low earnings that had high accident rates.

One of the most common problems with medical studies is that they often do not report the age at which the disability became apparent. Yet we would expect that loss of a leg or an eye would affect individuals’ earnings differently if they were injured before they had completed their educations than if they were injured after they had established their careers.

What Can Counsel Do?

Medical experts often go unchallenged by the courts, even when they use unreliable statistical methods. How can the courts circumvent this problem, given that most lawyers and judges lack the expertise to question the bases of statistical testimony? I recommend three approaches:

1. If the opposing expert appears to be relying on his/her own experience as the basis for his/her predictions, at the “qualification” stage counsel should question the expert’s training in statistics. Do this not (necessarily) with the intention of convincing the court to reject his/her credentials, but to prepare the expert to agree with counsel that certain standards of data collection are important. Then use that agreement later to induce the expert to concede that his/her experience is inadequate for drawing reliable inferences.

2. Hire an expert in statistical analysis. Of those professions most commonly seen in court, actuaries and economists generally have the best training in advanced statistical techniques. Actuaries will have greater experience with life expectancy and fringe benefit data; while economists will have greater experience with data concerning education and incomes.

Other professions that also receive advanced statistical training are epidemiologists (often employed by medical schools) and statisticians (found in university departments of mathematics).

3. One option that is used occasionally in Canada, but less often than is justified, is to hire an expert in statistics to conduct original statistical analyses. As such an analysis is likely to cost at least $10,000-$20,000, it can not be justified for small, or “one-off” cases; but in a major injury case, in which the damages approach a million dollars, or with respect to the types of injury that counsel is likely to encounter many times, such an expenditure may well be justified. For example, my firm was hired by the defendants in one of the residential school sexual abuse cases. We used census data to estimate the earnings of individuals similar to the residents of those schools, but who had not been abused, and compared those earnings to the earnings of the plaintiffs. Similarly, in the second part of this paper (to be published in the next issue of the Expert Witness), I report the findings of a set of statistical analyses I conducted using Statistics Canada data, to determine the impact of various types of disabilities on educational attainment and income. These analyses could have been conducted by virtually any Ph.D.-trained economist in Canada.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Using family background to Predict Educational Attainment in Canada

by Carmen Anderson with Christopher Bruce

The article first appeared in the autumn 2004 issue of the Expert Witness.

Introduction

It is important, when predicting the lifetime income of a young plaintiff, to be able to identify the educational level that individual would have achieved, had he or she not been injured.

The economics literature contains numerous studies that have investigated the determinants of educational attainment. But all of these studies attempt to explain only tendencies in choice of education. Whereas they can tell us whether a minor is “more likely” to obtain post-secondary education if he or she comes from one socio-economic background than from another, they rarely attempt to predict the magnitude of these effects.

As a result, the literature is of only very general assistance to the court. In this article, we present the results of detailed statistical analyses we have undertaken, using a recent set of data compiled by Statistics Canada, that will allow us to provide more detailed predictions of educational attainment than have previously been available.

The Data

The data we employ, from the 2001 General Social Survey, allow us to compare the educational attainment of Canadians aged 30-39 with numerous characteristics from their family backgrounds.

Specifically, for each of approximately 5,000 survey respondents, we know whether the individual: failed to complete high school, completed high school, took “some” schooling beyond high school, completed a college diploma or trade certificate, or completed university. We have similar information for each of the respondent’s parents; and information about the respondent’s province of birth (or whether he/she was an immigrant), religion, and first language. We also know whether each respondent was an only child, whether the respondent lived with both of his or her parents while a child, and what size of city the respondent lived in when a child.

Table 1 presents a complete list of the variables available to us, along with their means and standard deviations. Notice that, with the exception of the education of the respondent at age 30-39, all the information presented in Table 1 would have been available when the individual was a teenager. Thus, if the respondent’s educational attainment is found to be correlated with that information, it may be possible to predict the ultimate education of individuals who are currently in their teens.

Table 1

Statistical Analysis

We subjected the data to a statistical technique known as regression analysis in order to determine which of the socio-economic variables were most closely correlated with educational attainment. We found that only three categories of variables had statistically significant effects. These were: the education of the parents, whether the individual lived with both of his or her parents until age 15, and (to a lesser extent) the population of the community in which the individual lived at age 15. Variables that proved to have no (or little) significant effect on educational attainment were: province of birth (if Canadian), whether the individual was an only child, immigration status, mother language, and religion.

Most importantly, we were able to use the results of our analyses to predict the probability that the respondent would achieve each of the five education levels, based on: parental education, whether the respondent lived with both parents until age 15, and the population of the community in which the respondent lived at age 15.

Parents’ Education

Tables 2 and 3 provide detailed information concerning the impact of parental education on the educational attainment of sons and daughters, respectively. As an example of how to read these tables, the top left box in Table 2 indicates that if both the mother’s and the father’s educations were less than high school (“< High School”), the probability that their son would also obtain less than high school education was 21 percent. The probability that he would finish high school was 24 percent, would finish “some” post-secondary schooling was 14 percent, would finish a trade or college education was 28 percent, and would finish university was 14 percent.

Table 2

Table 2 also indicates that, for males, the probability of completing the two “middle” levels of education – “some university or college” or
“college/trade school” – is not strongly influenced by parental education. For example, the probability of completing college or a trade varies only from 28 percent (when both parents had less than high school or had university) to approximately 34 percent (all other parents); and the probability of completing some college or university varies from 7 percent to 14 percent.

Similarly, Table 3 indicates that, for females, the probability of completing college or a trade varies only from 26 percent (when both parents had university) to 36 percent (most other parents); and the probability of completing some college or university varies from 5 percent to 15 percent (with a much smaller range if university educated parents are omitted).

Table 3

At either end of the educational range, however, parental education is a much more important predictor. When both parents have less than high school, for example, the probability that the child will complete high school or less is 42 percent for females (25 percent high school plus 17 percent less than high school) and is 45 percent for males; whereas when both parents have university educations, these probabilities fall to 5 and 8 percent, respectively.

Conversely, the probability that children will obtain university education rises from 13 percent for females and 14 percent for males, when both parents have less than high school, to 64 percent for females and 57 percent for males, when both parents have university degrees.

Furthermore, a one step change in parents’ education at either end of the educational range can have a dramatic effect on the child’s educational attainment. For example, whereas the probability that males would complete high school or less was 45 percent when their parents both had less than high school, that probability fell to 29 percent when their parents had completed high school.

And whereas the probability that females would complete university was 64 percent when both parents had also completed university, that percentage fell to 39 percent when both parents had college degrees or trade certificates.

Finally, it is important to note that the child’s educational attainment is influenced by the education of both parents. At most levels of education, an increase in the mother’s education has virtually the same effect on the child’s educational attainment as does an increase in the father’s education.

Lived with Both Parents

We were also able to use our statistical analyses to predict the effect that living with both parents had on individuals’ educational attainments. These predictions are reported in Table 4. There it is seen that, although living with both parents had a statistically significant effect on the child’s educational achievement, for practical purposes the impact is small. In particular, among both males and females, those who lived with both their parents were approximately 6 percent less likely to drop out of school before completing high school, and 9 percent more likely to complete university, than were those who lived with only one parent.

Table 4

Urban/Rural

Finally, Table 5 indicates that population of the area of residence makes very little difference to the educational decisions of females and has an important effect on the decisions of males only in very large cities, where males are approximately 10 percent more likely to attend university than are residents of smaller areas.

Table 5

Conclusion

Our results confirm earlier researchers’ findings that, in the prediction of the child’s educational attainment, virtually the only factor that is of importance is the education of the parents. Most importantly, the children of parents with less than high school education are much less likely to proceed beyond high school than are the children of parents at other educational levels. And the children of parents with university degrees are much more likely to complete university themselves than are the children of parents with lesser education.

Nevertheless, we also found that the education levels of the child’s parents were only indicative of a child’s educational attainment. The only situation in which 50 percent of the children of a set of parents had the same educational level as their parents (when both parents had the same education) was that in which both parents had university degrees. In every other case, it was rare for the probability that children would share their parents’ educational attainment to exceed 33 percent. This strongly suggests that, in the prediction of a child’s educational success, experts should generally present at least two (and, more often, three) alternative scenarios.

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From 2003 until 2005, Carmen Anderson was a consulting economist at Economica, with a Master of Arts degree from the University of Calgary.

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Impact of the “Net Income” Provisions of the Insurance Amendment Act, 2003

by Christopher Bruce

This article first appeared in the summer 2004 issue of the Expert Witness.

The Insurance Amendment Act, 2003, adds the following subsection to Section 626.1 of the Insurance Act:

(2) To the extent that an award is for or is determined with reference to loss of earnings, the amount of the award shall be reduced by

(a) income tax, if the award is not subjected to income tax,

(b) contributions by employees, and 50 percent of contributions by self-employed persons, under the Canada Pension Plan (Canada), and

(c) premiums under the Employment Insurance Act (Canada) relating to the state of being employed, that would be or would have been payable on or with reference to the lost earnings, both before and after the award, had the accident not occurred.

The purpose of this paper is to analyse the impact that this subsection will have upon the assessment of personal injury damages in Alberta. Four general topics will be discussed: calculation of “net income,” introduction of the “tax gross-up” claim, consideration of questions that remain unanswered, and impact of the amendment on the size of personal injury claims.

1. Calculation of “net income”

The effect of the Act is to require that a calculation be made of the plaintiff’s “net income” – that is, his or her income after deduction of income taxes, employment insurance premiums, and CPP premiums (payable by the employee) – in both the without-accident and the with-accident scenarios, both before and after trial. This adds two steps to the calculation of personal injury damages: a determination has to be made of the various types of deductions and tax credits that will be relevant to the plaintiff; and income taxes, EI premiums, and CPP premiums have to be calculated in each year of the plaintiff’s loss.

1.1 Income tax deductions and credits: An individual’s income taxes are affected by many factors other than earned income. Taxable income, for example, is found by deducting contributions to private and public pensions, union dues, and moving costs. And individuals are eligible for tax credits that are determined, in part, by age, marital status, disability, CPP contributions, EI premiums, medical expenses, educational expenses (for example, for a child’s university fees), and charitable donations.

Prior to the passage of the Insurance Amendment Act, none of these factors had to be taken into account in claims for personal injury damages. Now, all of these factors will have to be considered, not just for the plaintiff’s current situation, but also for all situations that might arise over the duration of the plaintiff’s injury. For example, if a young person has suffered a permanent injury, it will now be necessary to predict whether they would have married and had children; how many children they would have had, and when; whether they would have contributed to an RRSP; and, if so, how much and when.

1.2 Calculation of income taxes: One of the most important implications of the Insurance Amendment Act is that plaintiffs’ income tax obligations will now have to be calculated for every year of every scenario of their claims, from the date of the injury to the date on which the effects of the injury will have resolved, regardless of the size of those claims. In claims of short duration, it may be possible to obtain a rough estimate of these obligations simply by projecting the plaintiff’s past tax record forward. For example, if the plaintiff’s taxes were 20 percent of income in the year preceding the accident and he/she will now lose one year of employment (at the same employer, at a similar earnings level), it may be possible simply to assume that the lost income would also have been taxed at 20 percent.

However, if the plaintiff’s employment situation would have (or has) changed had the accident not occurred, or if the period of loss extends more than a few years, it will be necessary to calculate taxes for each period of the loss. Fortunately, a number of computer-based programs are available that will simplify such calculations. First, there are commercial packages such as QuickTax. Second, there is a number of free programs available on the internet. The most sophisticated of these is Canada Revenue Agency’s “TOD” program that can be downloaded from:

www.cra-arc.gc.ca/tax/business/tod

Also, a tax calculator that is much simpler to use, but provides less precision, is found on Ernst & Young’s website at:

www.ey.com/global/content.nsf/Canada/Tax_-_Calculators_-_Overview

In general, income taxes amount to approximately 15 to 25 percent of gross income. Hence, for most plaintiffs, the effect of the Insurance Amendment Act will be to reduce the size of their claim by that percentage.

1.3 Calculation of EI premiums: Employment Insurance premiums will also have to be calculated. However, this is relatively straightforward. For all annual incomes below $39,000, the employee pays 1.98 percent of his/her earnings. For all incomes above $39,000, the EI premium is capped at $772.20 per year. Hence, the maximum effect of this element of the Insurance Amendment Act will be to reduce plaintiff’s claims by less than 2 percent.

1.4 Calculation of CPP premium: Section 626.1(2) states that “…the amount of the award shall be reduced by… (b) contributions by employees, and 50 percent of contributions by self-employed persons, under the Canada Pension Plan (Canada)…” Perhaps surprisingly, this provision will have no effect on plaintiff claims, as it has already been the common practice for most financial experts to deduct these contributions.

This practice has been based on two observations: First, the employer and the employee make equal contributions to the CPP. Second, the present discounted value of the benefit payments from the CPP (once the employee has retired) is equal to (approximately) half of the present discounted value of the CPP contribution stream. (Essentially, the other half of the CPP contributions has been used to “top up” the Plan, which had been under funded.) Hence, restitutio requires that only half of the contributions to the employee’s CPP account be replaced. As the employee’s and the employer’s contributions are of equal value, one can replace half of the contributions by compensating the plaintiff for only one of the two sources. For example, one can compensate for only the employer’s contribution but not for the employee’s. This, in effect, is what the common practice has been in Alberta.

Thus, as the new Act mandates deduction of the employee’s contributions, but does not preclude addition of the employer’s contributions (a form of fringe benefit), it leaves the plaintiff in the same position in which he/she would have been before the Act. That is, the CPP provision of the Act will have no net effect on plaintiffs’ awards.

1.5 Sample calculations: In the attached table, I have calculated the impact of the Insurance Amendment Act on the loss of income claims of plaintiffs at various levels of income. In the calculation of income taxes, I have assumed that the individual has the minimum level of deductions and tax credits. Hence, the figures reported in the table should be taken as maxima. It is seen there that the effect of the Act will be to reduce awards by 15 to 25 percent.

Table 1

2. Income Tax

The Supreme Court of Canada has ruled, with respect to both fatal accident claims and claims for cost of future care, that if the annual loss is calculated net of income tax, the plaintiff is entitled to an “income tax gross-up” to ensure that the amounts available from the investment of the lump sum damages are sufficient to compensate the plaintiff for his/her future losses. As the Insurance Amendment Act does not explicitly prevent the courts from allowing a tax gross-up, it appears likely that they will allow this calculation. This means that, in every personal injury case in which the plaintiff’s damages are expected to affect his/her income for some time into the future, a tax gross-up calculation will have to be made.

2.1 The basis of the calculation: Assume that the plaintiff has lost a gross (before tax) income of $50,000 one year from now, that his income taxes on that amount would have been $10,000, and that the interest rate at which he can invest a lump-sum award is 5 percent. Prior to the passage of the Insurance Amendment Act, the plaintiff would have been entitled to an award of $47,619 – as investment of $47,619 at 5 percent will provide a return of $2,381; and $2,381 plus $47,619 is $50,000.

Under the new Act, however, the plaintiff is to be compensated only for his after-tax loss, of $40,000. Thus, if the taxes on interest were ignored, the lump-sum award would be $38,095 – as $38,095 plus 5 percent of $38,095 (= $1,905) is $40,000. However, assume that the interest on the lump sum award will be taxed at 20 percent. In that case, investment of $38,095 at 5 percent would yield a net (after-tax) return of only $1,524 ($1,905 minus 20 percent) and the plaintiff would have only $39,619 with which to replace his $40,000 loss.

The 20 percent tax on investment income has reduced the effective rate of interest by that 20 percent, from 5 percent to 4 percent. (Note that $1,524 is 20 percent less than $1,905, or 80 percent of $1,905.) Thus, if the plaintiff is to have $40,000 available to him one year from now, more than $38,095 will have to be invested today. In this case, that amount will be $38,462 – as $38,462 plus 4 percent of $38,462 (= $1,538) is $40,000. The difference between $38,462 and $38,095 is called the income tax gross-up. NOTE: The gross-up equals the income tax that must now be paid on the interest income that derives from investment of the lump-sum award.

2.2 The magnitude of the tax gross-up: Note that in my simple example, the tax gross-up was very small relative to the size of the lump sum award. This is because there was only one year of losses and, hence, the lump-sum award, (on which interest was to be calculated), was small relative to the size of the annual loss. In cases in which losses are expected to continue for longer time periods, however, both the lump-sum award and the interest earned on investment of that award will be larger relative to the size of the annual payments. In such cases, the gross-up will become a much larger percentage of the award.

For example, assume again that it has been determined that the plaintiff has lost $50,000 per year before taxes, that taxes on that income would have been $10,000 per year, and that the interest rate is 5 percent. Assume also that the loss is expected to continue for 40 years and that the lump-sum award required to replace this stream, before addition of the gross-up, would have been $500,000. If that amount is invested at 5 percent, $25,000 in interest will be generated in the first year and, at a tax rate of 20 percent, the plaintiff will be required to pay $5,000 in taxes. That $5,000, and comparable (but declining) amounts calculated in all 40 of the future years of the loss, will have to be added to the award to ensure that the plaintiff can replace his/her after-tax losses. These “additions” constitute the gross-up.

In many cases, the addition of the gross-up will increase the award by as much as half of the reduction that resulted from the omission of income taxes. For example, if the lump sum, without the gross-up, has been reduced by 20 percent, the gross-up will often add as much as 10 percent back to the award.

It is interesting to ask whether it is possible that the award with the gross-up could be higher than the award that would have resulted from application of the “old” rules, in which income taxes were ignored. The answer is that it is highly unlikely that this will occur. In the example above, the effect of the Insurance Amendment Act was to reduce the plaintiff’s annual claim by $10,000, from $50,000 to $40,000, due to the deduction of 20 percent income taxes. Before the gross-up calculation could return the lump-sum award to the level it would have had prior to the Act, the taxes on investment income – the amount to be added for the gross-up – would have to equal that $10,000. In my example, that would require that investment income be $50,000 per year as, at a tax rate of 20 percent, that would generate $10,000 worth of taxes. (For example, if the lump sum was $1,000,000 and the interest rate was 5 percent, $50,000 investment income would be generated each year.)

That is, before the tax gross-up calculation would “add back” the income tax that had been deducted as a result of the Insurance Amendment Act, (in this case, $10,000 per year), the interest income in each year would have to equal the loss of before-tax income in that year. In my example, the annual before-tax income was $50,000, on which taxes would be $10,000. In order for the investment of the lump-sum award to create $10,000 in taxes on investment income, (which is the amount to be added for the gross-up), at the same 20 percent tax rate, it would have to generate $50,000 in such income. (Again, at a 5 percent interest rate, the lump-sum would have to be $1,000,000.)

But assume that investment of the lump sum did generate $50,000 investment income. That would exactly equal the amount required to pay for both the tax on that income ($10,000) and the compensation required for the plaintiff’s loss of net income ($40,000). That is, after deduction of the two payments from the interest income, the lump-sum would be left intact. But that cannot be correct. It is clearly the intention of the court that the lump sum award be drawn down each year, to help pay for the annual losses, until there is nothing left at the end of the period of the loss. That can only occur if the investment (interest) income in each year is less than the payments for taxes and the plaintiff’s loss. And that implies that the taxes on the investment income (the gross-up) will be less than the taxes on (gross) employment income. In short, in all but very exceptional cases, the gross-up will not be sufficient to return the lump-sum to the level that would have been awarded in the absence of the Insurance Amendment Act.

3. Unanswered Questions

With respect to the income tax issue, the primary question that will have to be answered by the courts is whether a tax gross-up will be allowed. Some lesser questions may also be raised:

3.1 Collateral benefits: The Insurance Amendment Act requires that many collateral benefits be deducted from the plaintiff’s claim. It is not clear whether the plaintiff will be able to include the interest earned on the investment of such benefits in the calculation of the tax gross-up.

3.2 “Add backs”: Self-employed individuals are often able to write off personal expenses as business expenses for the purpose of calculating taxable income. For example, business owners often claim that a greater portion of their vehicle, telephone, and mortgage expenses are for business use than is actually the case. Commonly, in personal injury claims, the “personal” portions of these expenses are “added-back” to reported income in order to obtain a measure of “true” income.

How should income taxes be calculated on this “add back?” Assume, for example, that the plaintiff had been reporting earnings of $30,000 per year, on which she had been paying income taxes of $4,000. Assume also, however, that this individual had benefited personally from $5,000 worth of business expenses per year. When this amount is added back to obtain the “true” measure of income, $35,000, should the income tax calculation be based on that ($35,000) figure, even though the plaintiff had been paying taxes on only $30,000? Or should the court recognise that, in the absence of the accident, the plaintiff would have received $31,000 (= $30,000 reported income – $4,000 income tax + $5,000 “business” expenses) worth of benefits (after tax) from her employment?

3.3 Replacement cost: It is not clear how the Insurance Amendment Act will affect the determination of damages when damages are measured using the “replacement worker” method.

In many cases involving self-employed individuals it is unclear (a) what their true income would have been if they had not been injured; nor (b) what their income will be now that they have been injured. It is often possible to determine, however, how much it would cost to hire a “replacement worker” whose input would return the plaintiff’s business to its pre-injury level of profitability.

Assume, for example, that the plaintiff’s income would have been $50,000 per year if she had not been injured and that it will be $20,000 per year now that she has been injured, but that neither figure can be calculated with any degree of certainty. Assume, however, that it is known that if the plaintiff was to hire an assistant for $20,000 per year, the firm would be as profitable as it would have been if the plaintiff had not been injured. In that case, it is argued, if the plaintiff was paid $20,000 per year, she would be put back in the position she would have been in had she not been injured.

But notice, if the plaintiff had not been injured, her business would have earned a profit of $50,000 per year, on which she would have paid income taxes. With the hiring of the replacement worker, the business again makes a profit of $50,000 before payment of $20,000 to the replacement worker. But, after the replacement worker has been paid, the plaintiff’s business will show only a $30,000 profit; and it is on that number that taxes will be calculated. Thus, if the plaintiff is awarded $20,000 per year, with which to compensate the replacement worker, her net income “with injury” will be: $50,000 (= $20,000 plus $30,000) minus the taxes on $30,000. This is greater than her net income before injury, which was $50,000 minus the taxes on $50,000.

It is not clear how the court will wish to deal with this anomaly, if at all. Note that any attempt to calculate the tax implications of using the replacement worker method will require that estimates be made of both the plaintiff’s with- and without-income streams. Yet it was to avoid having to make those estimates that the replacement worker approach was devised.

4. Impact of Insurance Amendment Act

The Insurance Amendment Act will reduce damage awards by the greatest amount in the following situations:

  • Those in which the plaintiff had been earning a relatively high income and, therefore, had been paying relatively high income taxes.
  • Those in which the plaintiff’s injuries are expected to continue for a relatively long period of time, as the effect of compensating for only after-tax income will be compounded over the duration of the loss – and as the tax gross-up will not fully offset the reduction for taxes.
  • Those in which the plaintiff is not self-employed. Self-employed individuals are able to write off personal expenses against their business income. Assume that it has been determined that those expenses amount to $5,000 per year. Typically, under the current system, that $5,000 will be “added back” to reported income in order to obtain a “true” measure of income. However, the individual would have had to earn more than $5,000 in order to generate enough income to purchase $5,000 worth of goods if he/she had not been self-employed (because income taxes would have been payable on any such income). Hence, the current practice actually compensates the plaintiff only for his/her loss of after-tax income. As that is what will be required under the Insurance Amendment Act, such plaintiffs will be in the same position under this Act as they were previously.
  • Individuals who have a cost of care claim. The income tax gross-up on a cost of care claim will be higher, the greater is the award for loss of earnings. (The higher is the award for loss of earnings, the greater is the interest that will be earned on investment of that award and, therefore, the higher will be the income tax bracket in which other sources of income – for example, interest on the cost of care award – will be placed.) As the Insurance Amendment Act reduces awards for loss of earnings, it will also reduce awards for cost of care.

5. Conclusion

It is my expectation that Section 626.1(2)(a) of the Insurance Amendment Act will not introduce any significant legal principles that have not already been analysed carefully with respect to fatal accident and cost of care claims. The primary impacts of the amendments are (a) more time and effort will now have to be expended in the calculation of personal injury damages (particularly when a gross-up is required); and (b) personal injury damage awards will now be approximately 15 to 25 percent lower than they were previously.

Footnotes:

* This article is based on presentations Dr. Bruce gave to ACTLA seminars in Calgary and Edmonton on June 21 and 23, 2004. He thanks the participants at those seminars for the excellent feedback that helped him to revise his paper. [back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Forecasting the Rate of Growth of Real Wages (Productivity)

by Christopher Bruce

This article first appeared in the spring 2004 issue of the Expert Witness.

One of the most important determinants of the value of an individual’s lifetime income is the rate
at which that income will grow from one year to the next. The lifetime income of an individual whose earnings grow at 1 percent per year will be dramatically lower than that of an individual whose earnings grow at 5 percent per year. Two major factors determine this growth rate, once the individual has chosen an occupation. First, as workers obtain more experience, their earnings increase due to what is often called
“career progress.” Second, all workers in society tend to benefit equally from the long-term rise in wages across the economy. (If average wages rise by 50 percent over a period two decades, we expect that the wages of labourers and waitresses will increase by 50 percent also, even if the skills required for those two jobs remain unchanged.2)

Furthermore, economy-wide wage increases can be divided into those that are due to changes in the consumer price index – inflationary increases – and those that are due to changes in the “real” purchasing power of wages – real wage increases. (The observed, or “nominal,” rate of increase of wages equals the rate of price inflation plus the rate of increase of real wages.) Unfortunately, despite its importance for the calculation of damages, the forecast of real wage increases proves to be very complex. The purpose of this article will be to report some recent developments in the preparation of that forecast that should prove to be valuable to the courts.

Introduction

Effectively, an increase in the real wage is an increase in the purchasing power of workers’ earnings. But, in the
long run, the average worker will only be able to consume more goods and services if output per worker has increased. Therefore, one would expect there to be a correlation between the long run rate of growth of real wages and the rate of growth of (real) output per worker, or “labour productivity.”

Depending upon the purpose to which it is to be put, a number of different definitions of labour productivity have been proposed. The definition that is most relevant to the determination of real wages is output per hour worked. Changes in this measure are influenced by three factors: increases in the amount of capital goods (machinery, buildings, computers, etc.) per worker, improvements in the technology “embodied” in capital (technological change), and changes in the productivity of workers (usually attributed to improvements in education).

Theory

Because a portion of any change in output per worker is attributable to changes in the quality and quantity of the capital available to workers, some of that increase in output will be paid to the owners of capital. Recently, most economists have come to accept the view that the allocation of gains between capital and labour will be determined in large part by the relative scarcity of those two factors.3 That is, in periods in which labour is in short supply (relative to capital), workers will be able to capture most of the gains from increased productivity and the percentage increase in real wages will equal or exceed the percentage increase in productivity. Conversely, when capital is in short supply relative to labour, it is capital that will capture most of the gains.

One of the attractive features of this theory is that it helps to explain many of the movements in real wages and labour productivity that have been observed over the last five decades. In the 1950s and 1960s, when the economy was growing rapidly and labour was (relatively) in short supply, real wages rose quickly, and at a rate higher than the rate of increase of output per worker. In the 1970s and 1980s, however, when the baby boom generation began to enter the labour market, labour supply increased significantly. Furthermore, because young adults borrow heavily – to purchase homes, cars, furniture, etc. – the influx of young baby boomers drove up interest rates, impeding firms’ ability to borrow for investments in capital. As a result, real wages stagnated even though productivity rose steadily. In the latter half of the 1990s, however, the baby boomers began to approach retirement age. Not only did the supply of labour start to fall, but older workers began to accumulate retirement savings, making funds available for capital investments. The result is that labour has become scarce relative to capital; and economists are now predicting that increases in real wages will begin to match, or exceed, the growth in output per worker.

Empirical evidence

Many economists believe that the reversal in the relative scarcities of labour and capital began in the mid-1990s. Some evidence in support of this conclusion is provided in Table 1. There it is seen that, between 1990 and 1995, the real incomes of Canadian males (25-44 years old, working full-time, full-year) decreased by 0.8 percent per year. (Nominal incomes increased by 1.4 percent per year during that period, while inflation averaged 2.2 percent.) However, between 1995 and 2000, average incomes increased by 3.1 percent while inflation was 1.7 percent, resulting in real income growth of 1.4 percent per year. Table 1 also reports that the real incomes of university graduates grew at 1.7 percent per year in the late 1990s; and that those of high school graduates and holders of trades diplomas and certificates made modest, but positive, gains in that same period.4

Table 1

Most Canadian economists appear to believe that, over the long run, output per worker will increase at between 1.5 and 2.0 percent per year. The 2.0 percent forecast is the consensus prediction of a group of Canada’s leading academic and government economists.5 The lower predictions have been made by forecasting agencies: Global Insight has forecast 1.9 percent per year over 2002-26; Informetrica has forecast 1.6 percent over the same period; and the Conference Board of Canada has forecast 1.46 percent over 2002-15.6Thus, as the model described above suggests that real wages will increase more rapidly than productivity, as the baby boomers age, a conservative estimate would be that real wages will increase by 2 percent per year over the next two decades.

>Conclusion

It is important to note that this means that all workers’ real wages will increase by 2 percent per year. Economy-wide productivity gains are like a rising tide, they carry all workers with them equally. Even the individual who remains in the same job, with no personal increase in productivity and no promotions, can expect, on average, to benefit from real wage increases of 2 percent per year. With inflation predicted also to be 2 percent per year, he or she is predicted to benefit from nominal wage increases of approximately 4 percent per year – a 2 percent inflationary increase plus a 2 percent real increase.

Footnotes:

1. This discussion is taken from Chapter 5 of Christopher Bruce, Assessment of Personal Injury Damages, 4th Edition, Butterworths, 2004.[back to text of article]

2. Evidence that all wages in the economy rise together, regardless of differences in the rate of increase of productivity among industries, was provided by Christopher Bruce in The Connection Between Labour Productivity and Wages (The Expert Witness Vol. 7, No. 2).[back to text of article]

3. See, especially, J. C. Herbert Emery and Ian Rongve, “Much Ado About Nothing? Demographic Bulges, the Productivity Puzzle, and CPP Reform,” Contemporary Economic Policy, 17 January 1999, 68-78; Henning Bohn, “Will social security and Medicare remain viable as the U.S. population is aging?” Carnegie-Rochester Conference Series on Public Policy 50 1999, 1-53; and William Scarth, “Population Aging, Productivity and Living Standards;” in Andrew Sharpe, France St.-Hilaire, and Keith Banting, eds. The Review of Economic Performance and Social Progress 2002, Institute for Research on Public Policy, Montreal, 2002, 145-156.[ back to text of article]

4. U.S. data also suggest that there was a striking switch to a high productivity growth regime in the mid-1990s. See, for example, James Kahn and Robert Rich, “Tracking the New Economy: Using Growth Theory to Detect Changes in Trend Productivity,” Staff Reports, Federal Reserve Bank of New York, No. 159, January 2003.[ back to text of article]

5. Andrew Sharpe,
“Symposium on Future Productivity Growth in Canada: An Introduction,” International Productivity Monitor, 7, Fall 2003, 44-45.[ back to text of article]

6. These figures are taken from Andrew Sharpe, ibid. pp. 44-45.[ back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Economica’s Privacy Policy

by Christopher Bruce

On January 1, 2004 the federal Personal Information Protection and Electronic Documents Act was extended to every organization that collects, uses or discloses personal information in the course of a commercial activity within a province. On the same date Alberta’s Personal Information Protection Act came into effect. The purpose of the (Alberta) Act is to “govern the collection, use and disclosure of personal information by organizations” (see www.psp.gov.ab.ca/faq.html). In light of these events, we outline Economica’s privacy policy:

  • We do not reveal any information concerning the specifics of any case, including the names and personal circumstances of the litigants, to any party other than the law firm that has retained us – unless that firm has specifically requested that we do so. We will not, for example, provide copies of our reports to the plaintiff or defendant, to any other expert who has been retained in the litigation at hand, or to any other law firm that is involved in the litigation without a specific request by the firm that has retained us.
  • All of the documents that we receive concerning the specifics of a case are kept in secure areas and/or in secure computer files. All such documents will be maintained in such a manner that they are not accessible to casual observation by visitors to our offices.
  • We will not discuss a case with any party other than the firm that has retained us, without previously having received the permission of that firm. We will not, for example, request personal information from the plaintiff, the plaintiff’s family, or the plaintiff’s employer, or from other experts without first informing the firm that retained us.
  • When speaking with third parties, such as employers, we will not reveal the name or circumstances of the plaintiff unless it is necessary to do so. If, for example, it is possible to obtain details concerning the plaintiff’s pension plan from his/her employer without revealing the plaintiff’s name, we will do so.
  • When disposing of confidential files concerning any litigant, we will have those files shredded by a professional firm.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Why have automobile insurance premiums been rising?

by Christopher Bruce

According to the most recent Statistics Canada data, automobile insurance premiums in Alberta increased by 68.6 percent between 2001 and 2003 (29.9 percent per year), at a time when the consumer price index increased by only 8.0 percent (3.9 percent per year). Similarly, over the 10-year period 1994-2003, premiums increased by 97.8 percent (7.9 percent per year) while the consumer price index increased by only 26.4 percent (2.6 percent per year). (See Figure 1.)

Although the government has reacted to this increase by introducing wide-ranging legislative changes, no satisfactory explanation has been given for why premiums should have risen so dramatically. The purpose of this article is (i) to review eleven of the explanations that have been given for rising premiums and (ii) to investigate those explanations to determine whether they are consistent with the evidence.

Figure 1

1. Number of accidents

Everything else being equal, an increase in the number of accidents per driver must increase insurance companies’ average payouts and, therefore, their average premiums. However, statistics indicate that the number of accidents has not increased significantly in the last decade. Between 1994 and 2001, for example, the number of collisions increased only from 431.4 to 460.5 per 10,000 vehicles, an average rate of increase of less than one percent per year. This cannot explain the sizeable premium increases of the last few years.

2. Severity of accidents

Even if the number of accidents had declined, the costs of claims per driver might have increased if the average severity of accidents had risen. If fewer people had been injured than in the past, but each injury had been much more serious than previously, total costs of claims might have risen.

With respect to severity, it is known that whereas the number of collisions involving injuries or fatalities increased only slightly between 1994 and 2001 – from 72 to 83 per 10,000 registered vehicles – and the number of collisions involving property damage remained almost constant – at about 360 per 10,000 registered vehicles – the number of “bodily injury” claims almost doubled – from 65 to 112 per 10,000 registered vehicles – over the same period. As bodily injury claims are generally much more expensive than other types, this trend suggests that the average cost of claims should have risen over the 1994-2001 period. Indeed, the Insurance Bureau reports that the average cost of injury claims rose by 44.6 percent (4.2 percent per year) between 1993 and 2002.

What these statistics do not explain, however, is why automobile insurance premiums increased so dramatically in 2002 and 2003. The statistics indicate that whereas the dramatic rise in premiums has been a recent phenomenon, the number and severity of bodily injury claims per vehicle has increased steadily for almost ten years. This evidence suggests that the recent rise in premiums is not closely connected with the increase in severity of accidents.

3. Damages

Even if the number and severity of accidents had remained constant, it is possible that the average cost of accidents could have risen if the courts had become more liberal in their awards of damages to accident victims. With respect to serious personal injury and fatal accident claims, the evidence on this question is clear, however – in the last 20 years there has been virtually no change in the manner in which the courts assess damages. Although there are no definitive statistics on this issue, the principles of damage assessment, in major injury cases, have not changed in Alberta since the mid-1980s. If damages for major injury cases have increased, it is not because there has been a change in the attitude of the courts; it is because Albertans’ incomes have been rising – necessitating larger awards to compensate victims for their losses of income.

It is possible that damage awards for minor injuries have increased substantially. However, it is noteworthy that insurance companies, who have argued that this is one of the major causes of increased premiums, have not released any data to back this claim. It seems reasonable to draw an adverse inference from this failure. Surely if the data supported the insurance industry’s arguments, they would have made those data public.

4. Fraud

Insurance companies commonly argue that consumer fraud is a major source of inflationary pressure on insurance rates. There are two major problems with this argument. First, although insurance fraud undoubtedly occurs, insurance companies have been unable to provide any statistically reliable evidence to show that fraudulent claims amount to more than a small percentage of payouts.

Second, and more importantly, even if fraud was a major problem, no evidence has been put forward to suggest that fraudulent claims have increased substantially in the last two years. For an increase in fraud to explain a significant portion of the 69 percent increase in premiums that has been observed, fraudulent claims would have to have increased dramatically. There is no evidence at all that this has occurred.

5. Medical costs

A recent study by the Insurance Research Council (a U.S.-based agency) found that “escalating medical costs are the key factor behind” the growth in automobile insurance claims in the past five years. It seems unlikely that this source could account for a significant portion of the recent rise in premiums in Alberta, however, as a substantial portion of medical costs resulting from automobile accidents are covered by Alberta Health Care. Since 1996, those costs have been covered under an annual levy that has increased at a relatively steady rate, of approximately 12 percent per year. For this source to explain a significant portion of the 69 percent increase in premiums seen in the last two years, there would have to have been a dramatic increase in the annual levy, an increase that has not been observed.

6. Legal costs

An additional component of the cost of insurance is the fees charged by lawyers and other experts. Although a substantial portion of victims’ legal fees are paid by the victims out of their damages – and, therefore, do not contribute to insurance companies’ costs – insurers have to hire their own lawyers and may sometimes have to pay a portion of the victims’ legal fees. Nevertheless, any argument that these costs have contributed to the substantial increase that has been observed in automobile insurance premiums founders on a lack of evidence that these fees have increased substantially in the last few years. It is one thing to argue that legal fees may, or may not, be “too high,” it is another thing altogether to argue that they have risen as a percentage of insurance costs.

7. Return on investment

To a certain extent the costs of operating an insurance company are offset by the company’s ability to invest the premiums it has received until drivers make their claims. The higher is the interest on those investments, the less does the company have to charge in the form of premiums. Some commentators have argued recently that the observed increase in premium costs has resulted from the decline in the average rate of return on investments.

This is not a compelling argument, however, as this decline cannot explain more than a small portion of the dramatic increases in premiums. If insurance companies hold premiums for half a year on average (that is, if premiums are collected at the beginning of the year and then spent at a constant rate over the year), and if the rate of return on investments is, say, 8 percent, then the interest that is collected will (on an annual basis) equal 4 percent of premiums. If the rate of return then declines to 5 percent, the effective return on the investment of premiums will fall to 2.5 percent, a drop of only 1.5 percent. As this is roughly the order of magnitude of recent declines in rates of return, this factor cannot explain a significant percentage of the recent increases in premiums.

8. Administrative costs

Approximately 25 to 30 percent of an insurance company’s costs are for administration – salaries of salespeople and adjusters, rent, cost of supplies, advertising expenses, etc. There is no evidence to suggest that these costs have risen significantly in the last few years.

9. Re-insurance

Insurance companies have argued that one of the most important sources of increased costs in the last two years has been the increase in premiums that they have had to pay to re-insurance companies since September 11, 2001. This argument is implausible. Figure 1 illustrates the increases in both automobile and homeowners’ insurance premiums in Alberta in recent years. If re-insurers had raised their rates in response to the perceived increase in terrorism, they would have raised those rates by at least as much for homeowners’ insurance as for automobile insurance. But it is seen clearly in Figure 1 that homeowners’ insurance premiums rose by far less than did automobile insurance premiums. This provides compelling evidence that increases in re-insurance premiums have not been a major source of the reported increase in automobile insurance premiums.

10. Collusion

Some critics of the insurance industry have argued that the recent increases in automobile insurance premiums have resulted from collusive behaviour among insurance companies. This argument is suspect for two reasons. First, it is difficult to explain why insurance companies would have raised premiums for automobile insurance and not for homeowners insurance. Second, there are more than 100 automobile insurance companies operating in Alberta. Over a century of experience suggests that it is extremely difficult even for an industry of only three or four firms to maintain a collusive stance. It is unlikely that 100 firms could do so.

11. Statistical interpretation

There is some concern that the dramatic increases that have been observed in automobile insurance premiums in the last few years have resulted from the way that statistics are collected and reported rather than from “real,” underlying factors. Two arguments have been made in this respect.

First, the Insurance Bureau argues that the manner in which Statistics Canada collects information about automobile insurance premiums produces misleading results. Nevertheless, the Bureau’s own data (published in the December 2003 issue of their newsletter Perspective) indicate that automobile insurance premiums in Alberta rose by approximately 63 percent (5 percent per year) between 1993 and 2003 and by approximately 30 percent (14 percent per year) between 2001 and 2003. Although these numbers are much lower than those produced by Statistics Canada, they are still substantially higher than the overall consumer price inflation figures for those periods. (Also, whereas Statistics Canada’s data measure changes in the price of a fixed “basket” of insurance policies, the IBC data measure changes in the costs of actual insurance policies that have been purchased. Thus, if, as premiums rise, consumers purchase less comprehensive policies, the IBC data will underestimate the rate of increase of given policies.)

Second, it is well known to observers of the automobile insurance industry that premiums move in a cyclical manner. When premiums are relatively low, insurers’ profits fall and many firms leave the market. This reduces competition and allows premiums to rise. But as that happens, profits also rise, attracting new firms, and driving down premiums again. Typically, this cycle takes approximately 10 years. The data in Figure 1 show, for example, that there were significant increases in premiums in the early 1980s, early 1990s, and early 2000s; and stagnation of premiums in the mid-1980s and mid-1990s.

This observation suggests that the recent, dramatic increases are simply part of a larger, cyclical movement in automobile premiums. Even if this is true, however, the average increase over the last 10 years – even when calculated on the basis of the IBC figures (5 percent per year) – has been more than double the average rate of consumer price inflation. Clearly, cyclical and statistical factors alone cannot account for this substantial increase.

Table 1

Conclusion

The information that has been reviewed in this paper suggests that two factors are primarily responsible for the pattern of premium changes that have been observed in Alberta in the last decade. First, the dramatic increases in the last two years represent a “natural” upturn in a long term cycle in premiums. Past patterns suggest that these increases will be followed by stagnation of premiums for the next six or seven years.

Second, there is some evidence to suggest that the average severity of personal injury claims has been rising. As I find no evidence that this increase has been due to fraud, to an increase in the number of accidents, or to changes in the criteria employed by the courts to calculate damages, it appears that the most plausible explanation is that the losses suffered by plaintiffs have been increasing in value.

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A large number of individuals were kind enough to provide me with assistance in the preparation of this article. I would particularly like to thank Don Higa, Jim Rivait, Walter Kubitz, Derek Aldridge, and Harris Hanson.

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Policies to deal with rising premiums

by Christopher Bruce

In the first article in this newsletter, I analyzed the arguments concerning eleven possible sources of increased automobile insurance premiums. The purpose of this article will be to review each of those sources to determine whether there are changes in government policy that might reduce premium costs.

1. Number of accidents – Experience Rating.

The Alberta government has already taken one of the boldest and most innovative steps possible towards reducing the number of automobile accidents. This is their proposal to introduce experience rating – the direct tying of premium values to drivers’ accident-causing behaviour – to the automobile insurance sector.

Experience rating has two highly desirable characteristics. First, the individual driver has complete control over his or her premiums. If individuals drive cautiously, avoiding accidents and driving violations, their premiums will decline to the lowest available rate. Furthermore, individual drivers’ rates will not be relatively high just because they happen to belong to a group, like young males, that has a relatively high accident rate.

Second, there is a substantial body of statistical evidence to show that when insurance premiums are related to experience, accident rates fall. When individuals know that they can reduce their premiums significantly by driving more carefully, they do so.

Under the government’s proposal, the impact of a serious driving offence or an at-fault accident will be much greater than it is currently, under what is known as “actuarial” rating of premiums. For example, under the proposed system, a typical Edmonton driver who has recently begun to drive (i.e. who has no “experience”) will pay a premium of about $2,000. After four years of no accidents or driving offences, that driver will pay only $700 – a saving that will continue for each and every year into the future as long as the driver has no accidents or convictions. One would expect an annual saving of $1,300 to be of sufficient size that it would induce most individuals to take additional precautions against unsafe driving.

Furthermore, the proposed system would move the driver four steps up “the premium ladder” each time he or she had an at-fault accident. So the driver with four years of accident free driving would be bumped from the reduced $700 premium to the $2,000 base premium, losing the entire $1,300 “bonus”.

And the incentive to avoid driving convictions is even stronger. A single impaired driving conviction would increase premiums by 200 percent.

These proposals are highly desirable. The government deserves far more credit than it has received for recommending them. Nevertheless, the government needs to reconsider two aspects of its plan.

First, it is mistaken in its proposal that a government agency should set the base premium rate. For example, in the case discussed above, the $2,000 base premium for Edmonton drivers was not one chosen by the insurance companies, but by the government. This is unreasonable for two reasons. First, the government cannot know what the true cost is to the insurance companies of providing insurance. As a result, the base rate that it will choose is almost certain to be either too high or too low.

If it is too high, insurers will make excess profits at the expense of Alberta drivers. If it is too low, insurance companies will make losses and some of them will refuse to provide coverage to Albertans.

Second, when the government sets premiums, the competitive incentive for insurance companies to find ways to lower rates is lost. If insurance companies are forced to charge the same rates regardless of how efficient they are, there is less incentive for them to seek ways of being efficient. It is these competitive pressures that keep premiums from rising more than they have.

There is a simple solution to these problems: the government should set only the percentage increases and decreases that are to result from various “experiences” and leave the insurers to set the base rates from which those increases and decreases are to be calculated. This will get the government out of the business of setting rates, while leaving intact the strong incentives created by a system of experience rating.

The second problem with the new legislation is that it does not deal with the adverse incentives that it gives to insurance companies. Specifically, experience rating results in a situation in which insurers know they will make substantial profits on some classes of customers and lose money on others. Thus, it gives them a strong incentive to refuse to insure the money-losing group. In the scheme proposed by the Renner committee, that group will be composed primarily of young males.

Insurers will lose money on this group because the number of accidents drivers have had in the past is only loosely related to the number that they can be expected to have in the future. What decades of statistics tell us is that a nineteen-year-old male with a perfect, three-year driving record is more likely to have an accident in the next year than is a forty-year-old male with the same driving record. And a nineteen-year-old who had an accident last year is more likely to have an accident next year than is a forty-year-old with the same experience. This means that insurers will expect to pay out more claims to nineteen-year-old drivers than to forty-year-old drivers.

Assume, for example, that ten percent of nineteen-year-old drivers who have had a clean record for three years will have an accident in the next year; whereas only five percent of forty-year-olds with a similar record will have an accident next year. If the average accident costs the insurance company $10,000, it will expect to pay out an average of $1,000 for each nineteen-year-old and $500 for each forty-year-old.

If the government forces insurers to charge the two groups the same premium, they will have to charge something between $500 and $1,000 just to cover their expected claims costs. For example, if the two groups were the same size, the premium would be $750 (the average across the two). But this means that they will expect to make a $250 profit on the average driver in the older group and a $250 loss on the average driver in the younger group.

As insurance companies are profit-driven, we can expect that they will respond by doing their best to attract older drivers – and to turn away younger drivers. The stakes are high. Those companies that find themselves with a relatively high percentage of young drivers will lose money and will soon be forced out of the market. Companies will use every loophole at their disposal to attract as many drivers in the older age groups as possible.

For example, companies might offer to sell automobile insurance through employers, in much the same way they currently sell long-term disability and dental plans. As employees are predominantly in the 25-64 year age group, and as high risk drivers are predominantly in the 16-24 and 65+ age groups, such a practice would allow firms to “skim” off the low-claim drivers.

The government will need to introduce strict controls to ensure that companies are not seriously disadvantaged if they write insurance for groups whose average claims exceed average costs.

2. Severity of accidents – Improved policing.

Reductions in severity are most likely to come from improvements in the design of automobiles; and in the use of safety devices such as seat belts and air bags. Nevertheless, provincial governments can reduce severity by enforcing highway speed limits more strictly – particularly on segments of roads that are known to have high accident rates.

Recent scientific evidence, published in journals such as Accident Analysis and Prevention, Injury Prevention, and the Canadian Medical Association Journal, concludes that the two changes that offer the greatest promise for reducing the incidence and severity of accidents are: first, raising the legal drinking age; and, second, banning the use of hand-held cellular telephones by drivers of moving vehicles.

3. Damages – Restrictions on tort.

Many of the proposals that have circulated in the last year or so have had to do with the placement of restrictions on tort damages. In general, these proposals are based on the assumption that victims are currently being “overcompensated;” hence, a reduction in damages will not cause a hardship to victims. The two most commonly-made proposals are that individuals should not be able to claim from two insurers for the same loss – the “double compensation” issue – and that loss of income should be calculated net of income taxes – because victims do not have to pay taxes on their awards, they will be adequately compensated if damages are based on after-tax income.

Typically, double compensation occurs when the victim is compensated for loss of income both by the defendant and by the victim’s own long-term disability insurance. Under the new legislation in Alberta, victims will be allowed to collect from only one of these parties. This proposal seems reasonable except that it is usually suggested that the victim be required to collect from his or her own insurance company. Effectively this requires that the victim be made to pay for damages caused by a negligent driver – and it allows the negligent driver to evade responsibility for his/her actions. Neither of these outcomes seems defensible. Furthermore, if disability insurers are able to re-write their policies in such a way as to avoid paying damages when their clients are able to collect from negligent drivers, the legislation will affect only disability insurance premiums (which will decrease), not automobile insurance premiums.

The second proposal for reducing tort damages – that victims be compensated only for after-tax losses – also seems reasonable. As plaintiffs do not pay taxes on court-awarded damages, the payment of “gross” income overcompensates them. The primary argument against this proposal is that plaintiffs currently rely on this “overcompensation” to help them pay for their legal fees (which are only partially paid by the defendant). If plaintiffs have to pay for their legal fees out of after-tax income, their awards net of legal fees will leave them undercompensated.

A third element of the new legislation sets limits on the award of “non-pecuniary” damages. This is not based on the assertion that victims are being overcompensated by the courts. Rather, it is based on the assertion that victims of “minor” injuries are exaggerating their injuries and, therefore, defrauding the system. The issue of fraud is discussed in the next section.

4. Fraud.

Setting limits on damages is an entirely inappropriate method of dealing with fraudulent claims, primarily because it punishes the innocent. If fraud is an important factor in the determination of automobile insurance premiums, there are two appropriate responses. Insurers can increase their vigilance; and, in cases of egregious behaviour, they can ask the government to lay criminal charges. As both of these responses are already available to the insurance industry, the government does not need to take further steps.

5. Medical costs.

It is clear that public policy towards medical costs is unlikely to be influenced significantly by government concern over automobile insurance premiums. In this area, drivers and insurers can only hope that government health policy incidentally acts to reduce personal injury claims costs.

6. Legal costs – no fault.

It is often argued that legal costs could be minimized if a form of no fault insurance was introduced. Whatever the advantages of no fault might be, there are three important problems with it that must be dealt with before such a proposal can be considered seriously.

First, because more parties can make claims in a no fault system than in a fault system (“at fault” drivers can make claims in no fault systems but not in fault systems), there is very little chance that no fault will reduce premiums. Indeed, the evidence shows that no fault jurisdictions have premiums very similar to those in fault jurisdictions.

Second, the purported source of savings in a no fault system is that accident victims are denied access to the court system; hence legal bills are reduced. But, the courts serve an important function – they allow parties to appeal decisions made by their insurance companies that they feel are unfair. It is possible that an appeal system can be introduced to no-fault insurance, but there is some evidence to suggest that if such a system really is fair, it will cost as much as do the courts. In short, any savings in administrative costs tend to come at the expense of justice.

Third, there is consistent, strong evidence to suggest that there are more accidents in no fault jurisdictions than in fault jurisdictions because drivers in the former do not have to take responsibility for their actions. (Recent statistical studies conclude that when no fault insurance is introduced, the accident rate rises by approximately 6 percent.) Indeed, not only are the drivers who are at fault for their own injuries not made to pay higher premiums, they are fully compensated by the insurance system for any costs they incur.

7. Return on investment.

If insurance companies have been harmed by falling rates of return on their investments, there is nothing the government can do to help, short of making short-term loans at below-market rates.

8. Administrative costs – Public insurance.

It has often been suggested that administrative costs could be reduced if the private insurance system was replaced by a government-run monopoly. This suggestion ignores the fact that monopolies have been found, almost universally, (i) to be less responsive to their customers than are competitive firms; and (ii) to be less efficient than are firms that have to face competitive pressures. (Some proponents suggest that automobile insurance is less expensive in Saskatchewan and Manitoba than in Alberta because it is provided by monopoly in the former two provinces. However, this ignores the many subsidies that those insurers receive from their governments and also ignores the fact that British Columbia’s premiums are not significantly different from Alberta’s.)

9. Re-insurance.

Following the terrorist attacks of September 11, 2001, re-insurance companies have raised their premiums significantly. As the terrorist attacks should have only a negligible effect on automobile insurance claims, the re-insurers’ actions are unjustifiable. It might be appropriate for the Government of Alberta to provide re-insurance coverage to firms working within Alberta until re-insurance rates return to a level that is consistent with the risk that is being faced.

10. Collusion.

Unless some evidence is presented to suggest that automobile insurers are colluding, no action needs to be taken on this issue.

11. Statistics.

If Statistics Canada has overestimated the rate of increase of automobile insurance premiums and if premiums do follow a regular cycle, which is currently at its peak, then there is little or no rationale for the Alberta government to do anything about premiums. Alberta might cooperate with the Insurance Bureau and Statistics Canada in reassessing the method by which premium inflation is measured; but, otherwise, Alberta merely needs to wait a year or two and that inflation rate will fall significantly by itself. The drastic changes proposed by the government are completely out of line with the (non) seriousness of the situation.

Summary

This article has concluded that the government would be justified in adopting the following policy changes:

  • Introduce experience rating, as proposed by the Renner committee, but without government control over the base premium rate.
  • Increase police surveillance of moving traffic violations, particularly in areas identified as being of high risk.
  • Raise the legal drinking age.
  • Ban the use of hand-held cellular telephones by drivers of moving vehicles.
  • Introduce a regulation that losses of income be made on an after-tax basis.
  • Provide re-insurance to the automobile insurance industry until rates return to a level that can be justified based on expected claims.
  • Cooperate with Statistics Canada and the Insurance Bureau of Canada in investigating the manner in which the inflation rate of automobile insurance premiums is measured.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

How are Automobile Insurance Premiums Determined?

by Christopher Bruce

Although automobile insurance rates seem to be in the news constantly, there is often confusion in the media about the process by which premiums are determined. The purpose of this article is to provide a brief introduction to that process. Three topics will be discussed: actuarial rating, rating classes, and experience rating.

1. Actuarial Rating

In Alberta – and all jurisdictions with private insurance – automobile insurance premiums are established through a technique that is generally referred to as “actuarial rating.” Fundamentally, under this system the premium the driver pays is equal to the cost that the insurance company expects the driver will impose upon it. If, on average, insuring a driver will cost the insurer $1,000 per year, the premium it will charge will equal $1,000 (plus an allowance for the company’s profit margin).

Assume, for example, that an insurance company has 10,000 customers; that there is a 10 percent chance that each driver will have an accident that results in an insurance claim each year; and that the average claim is $7,000. On average, therefore, 1,000 customers will make a claim each year, imposing a total cost of $7,000,000 on the insurer. Spread across the company’s 10,000 customers, therefore, the cost of claims, per customer, is $700.

In addition, the insurer will have to pay for its own costs of administration and will have to collect enough money to provide it with at least the minimum amount of profit to keep its shareholders satisfied. Assume that administrative costs amount to $250 per customer per year and that the minimum “acceptable” profit level can be represented as $50 per customer per year.

In this case, the insurer will have to collect at least $1,000 per year from each of its clients – $700 to cover the average cost of accident claims, $250 to cover administrative costs, and $50 for profit. The theory of actuarial rating predicts that this insurance company will set its premiums equal to that $1,000 figure. The “proof” of the theory’s prediction is as follows:

First, imagine that the company was to set a premium that was higher than $1,000, say, $1,050. Now, the company’s expected profit would be $100 per customer (= $1,050 – $700 – $250), twice the $50 figure that insurance companies require in order to remain in business. A second insurer would see the opportunity to make substantial profits by offering to insure the first company’s clients for less than $1,050, say $1,025. At this rate, its profits of $75 per customer would still be higher than the $50 that shareholders demand. But this would attract additional companies who would be willing to offer an even lower rate. As long as profit exceeds the minimum necessary to attract investors – that is, as long as the premiums charged exceeded $1,000, new firms would continue to enter the market, driving the premium down. In the long-run, the premium rate could not remain above the cost of insurance plus the minimum profit level.

Second, imagine that the insurer was to set its premium below $1,000, say at $900. It would soon discover that the costs of insurance exceeded the premiums that were being collected and it would be forced either to raise its premiums or to go out of business. In either event, premiums would rise until they at least equaled insurers’ costs (plus the minimum profit level).

In short, as long as there is competition in the insurance market – that is, as long as firms are able to compete for the business of their rivals; and firms do not collude to prevent such competition – the premium level will always tend towards the cost of insurance plus a minimal profit level. When premiums are set in this way, they are called “actuarially fair.”

2. Rating “Classes”

In the preceding discussion, I assumed that each client had the same probability of making a claim – 10 percent per year. In reality, of course, some customers have a higher claims probability than others. The theory of actuarial rating predicts that insurers will attempt to identify different “classes” of customers, according to those customers’ claims probabilities, and will charge a premium to each group that is a function of its accident risk.

Assume, for example, that the insurance company discussed above realizes that 2,000 of its 10,000 customers have a higher-than-average probability of making an insurance claim, say 20 percent per year. If it is still assumed that the average probability across all 10,000 customers is 10 percent, that implies that the probability that each of the company’s remaining 8,000 customers will make a claim is 7.5 percent. That is, when the 2,000 high-risk customers each have an accident probability of 20 percent and the 8,000 low-risk customers have an accident probability of 7.5 percent, the average probability of an accident across the two groups together is 10 percent. Thus, the expected number of claims is still 1,000 per year – 400 (= 0.20 × 2,000) by the high-risk group and 600 (= 0.075 × 8,000) by the low-risk group.

If the company continues to charge each of its customers $1,000 per year, it will still make an average profit of $50 per customer. (Because its customers have the same number of accidents and pay the same premiums, the same amount is left over for profit). However, if another company notices what is happening, it will realize that it could make a higher profit than average by attracting away some of the first company’s low-risk drivers.

For example, if the second insurer was able to attract 1,000 customers by charging $900 to the low-risk group, it would find that, on average, 75 of those customers (= 0.075 × 1,000) would have accidents. At an average cost of $7,000 per accident, total accident costs would be $525,000, or $525 per client. Assuming that administrative costs remained at $250, this company’s total costs per client would be $775, leaving a $125 profit from the $900 premium.

Soon, other insurance companies would recognize this profit-making opportunity and they would also offer reduced premiums to the low-risk group. By the theory of actuarial rating, the equilibrium premium for drivers in that group would eventually settle at $825 – the $775 cost per driver plus $50 for profit.

At the same time, as low-risk drivers were being attracted away from the first company, that company would find itself with a higher and higher percentage of drivers from the high-risk group. Assume that, ultimately, all of its clients came from that group. If each of those drivers had a 20 percent probability of making a claim and the average claim cost $7,000, then the average value of claims per driver would be $1,400. When $250 is added to this figure for administrative costs and $50 for profit, the firm would have to charge a premium of $1,700 to each of these drivers to remain in business.

But, high-risk drivers have no incentive to reveal to insurers that they have high probabilities of making claims; and low-risk drivers may find it difficult to signal credibly that they are members of the low probability group. (If insurance companies offer low premiums to those in the low-risk group, it will be in every driver’s interest to claim to belong to that group.)

Hence, insurance companies have looked for ways to construct “classes” of drivers based on characteristics that can be observed readily. There are two types of such characteristics – those over which drivers have little or no control, like age, sex, and (to a lesser extent) area of residence; and those over which they have a significant amount of control, like number of “fault” accidents and number of moving violations.

Age and Sex

It is well known that young males – and, to a lesser extent, young females – have a higher probability of making claims against their insurers than do older drivers. In this sense, young males are similar to the high-risk group discussed in the preceding section.

For this reason, in a competitive market, insurers will be forced to charge higher premiums to young males than to other groups. An insurance company that averaged all drivers together when setting its premiums (for example, setting a single premium of $1,000 in the example above) would soon lose all of its low-risk drivers to other firms that offered those drivers premiums that were related to their expected costs ($825 in the preceding example).

Furthermore, even though some young males are low-risk drivers, they will be charged the high premiums associated with their group. The reason is that, from the insurance company’s perspective, all young males look alike. As long as they drive the same kinds of cars, have the same driving records, etc, insurers will be unable to determine which young males are low risk and which are high.

In a competitive insurance market, there is no way around this issue. Any insurance company that offered premiums that were less than its expected costs of covering young males would find, first, that it would attract a very large percentage of young male drivers and, second, that it would, on average, lose money on those drivers. It would soon be forced to change its policy or be driven out of business.

Driving Experience

A second way of classifying drivers into low-risk and high-risk groups is to observe their driving behaviours. For statistical reasons, it is known that those who have had accidents in the current year have a higher than average probability of having accidents in the next year than do those who did not have accidents in the current year.

Assume again that there are two groups of drivers – 2,000 high-risk drivers, who have a 20 percent probability of making a claim in any given year, and 8,000 low-risk drivers, who have a 7.5 percent probability of making a claim. Assume also that the insurance company is unable to determine, on the basis of characteristics such as age and sex, which drivers belong in each category. In that case, the average probability of an accident across the two groups is 10 percent and, in the first year, the actuarial insurance premium will be $1,000.

During the first year, however, 400 of the high-risk drivers and 600 of the low-risk drivers will have accidents. This means that, among the group “drivers who had an accident in year 1,” 400, or 40 percent of the group, have a 20 percent chance of having an accident in year 2 and 600, (60 percent), have a 7.5 percent chance. On average, the drivers in this group have a 12.5 percent chance of having an accident in year 2. Their actuarial premium, (the premium that covers their expected costs plus profit margin), will be $1,175.

The remaining group, “drivers who did not have an accident in year 1,” will be composed of 1,600 drivers from the high-risk group and 7,400 from the low-risk group. Their average accident risk in year 2 will be approximately 9.72 percent and their actuarial premium will be approximately $980.

What is seen here is that the reason there is a premium differential between drivers who have had accidents and those who have not is not because insurers are trying to “recover the payments” they have had to make on behalf of clients who had accidents. Rather, because the group “those who have had accidents” has a disproportionate number of high-risk drivers (because they are the most likely to enter this group), its expected claims costs must be above average – meaning that its premiums will be proportionately higher also.

This means that the premium differential between those who have had accidents and those who have not will increase as the size of the high-risk group increases (thereby increasing their representation in the “have had an accident” group) and as the risk differential between low- and high-risk drivers increases.

3. Experience Rating

Automobile insurance is designed to protect the purchaser from catastrophic loss. The consumer pays an annual premium in return for a promise from the insurer that the latter will pay for any losses incurred by the former.

But insurance also has a second, unintended effect – it reduces the incentive for drivers to avoid accidents. In the absence of automobile insurance, drivers would have to bear the full financial impact of any negligent behaviour – under the assumptions used in the preceding section that would be $7,000 for each accident. This threat could be expected to induce them to take precautions against such behaviour.

In the presence of automobile insurance, however, the financial impact of negligent behaviour is the difference between the premium charged to drivers who have had accidents and those who have not. In the preceding section, it was shown that this amount could be quite small – less than $200 under the plausible assumptions employed there. This significant reduction in financial risk (relative to the no-insurance situation) can be expected to reduce substantially the incentive to avoid negligent behaviour.

In response, many commentators have suggested that the current actuarial rating system should be replaced by one based on experience rating – that is, a system in which premiums are tied closely to occurrences of driver negligence. For example, insurance companies might be required to ensure that the premiums charged to drivers who had had accidents or serious moving violations were at least double those charged to drivers who had “clean” driving records.

Note that experience rating cannot arise independently in a market in which a large number of firms compete for customers. As was shown in Section 1, above, competition forces firms to charge premiums that are based on actuarial rating. Experience rating can only arise in markets in which there is no competition – such as in provinces like British Columbia and Saskatchewan in which the government has a monopoly – or in jurisdictions in which the government establishes legislation to force private insurers to use that rating system.

Among the legislative changes that were contained in Alberta’s recent Bill 53, (see www.autoinsurance.gov.ab.ca/calculate.html), is a proposal to impose a version of experience rating. Although binding regulations have not been announced yet, the current proposal would require that insurers increase premiums by as much as 50 percent in the year following a single “at fault” claim and by an additional 30 to 40 percent in each subsequent year for six years or more; (that is, by as much as 250 percent when added across the six years following a single claim). The proposed system would also require that insurers increase premiums by 200 percent in each of the two years following a criminal code violation – such as impaired driving or criminal negligence causing death.

Economic theory predicts that experience rating systems – such as the one proposed by the Alberta government – will produce substantial increases in the levels of precautions taken by drivers – and corresponding substantial decreases in the number of accidents. It will be interesting to observe (i) whether the Alberta government will have the political willpower to force such a restrictive rating system on an unwilling and politically powerful insurance industry; and (ii) if it does so, whether such a system will yield the anticipated benefits.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The impact of parental divorce or death on adolescents’ education & earnings

by Christopher Bruce
& Mohamed Amery

This article first appeared in the summer 2003 issue of the Expert Witness.

It is sometimes argued that individuals’ earnings will be lower if they grow up in single parent homes than in homes with two parents. If this argument is correct, it is possible that the loss of earnings experienced by a child who has been injured will be lower if that child came from a one-parent family than from a two-parent family. Conversely, however, the loss suffered by a child whose parent has been killed may be higher than would normally be assumed if the loss of that parent has meant that the child must now grow up in a single-parent family.

A number of studies are available that have explored the effect of parental absence due to divorce or death on adolescents’ labour market outcomes as adults. Although these studies are consistent in finding that the absence of a parent has some effect on adult earnings, they disagree on what that effect is. Corak, for example, concluded that whereas the earnings of women were the same regardless of family backgrounds, those of men from divorced families were approximately three percent lower than those of men from intact families.

Lang and Zagorsky confirmed Corak’s finding that “parental presence early in life [has only a minor effect on] economic well-being in adulthood” (p. 255). Nevertheless, whereas they found that a father’s presence is important for the educational attainment of both sons and daughters, a mother’s presence is significant only for the educational attainment of daughters. Also, contrary to Corak, they found (p. 255) a “strong impact of father’s presence on [a] son’s probability of being married”.

Fronstin et. al. concluded that the wages of “females, but not males, appear to be adversely affected by a father’s death, particularly when the death occurs before the child’s sixteenth birthday” (p. 151). The primary impact on men was higher unemployment rates (at age
33), particularly if the father had died when the son was between 16 and 22. Fronstin et. al. also found that disruptions occurring prior to “middle teenage years have somewhat greater adverse effects on educational attainment, while disruptions occurring into young adulthood have [their primary] adverse effects on … labour market outcomes” (p.
168).

In their book, Growing Up with a Single Parent, Sara McLanahan and Gary Sandefur, summarized the findings of a number of studies that had been conducted in the 1980s. Those studies generally found that children who were raised in single-parent families were somewhat less likely to attend college than were children of two-parent families, and much less likely to graduate from college. However, there was clear evidence that these effects were much less severe if one parent had died than if the child’s parents had divorced or had never married. These results suggest that it is not “single-parenting” per se that yields adverse effects. Rather, single parenting appears to act as a proxy for the underlying factors that lead parents not to marry, or to divorce. It is those unobserved factors that appear to have the primary impact on children’s labour market success.

Finally, Boggess found that living with a widowed, divorced, or separated mother had no effect on educational attainment. Interestingly, however, he concluded that “living in a stepfather family appears to have a persistent negative effect on high school graduation rates” (p. 205).

What these studies appear to suggest is that a child from a single-parent family may obtain slightly less education, and perform slightly less well in the labour market, than a child from a two-parent family. However, this effect will be much more pronounced if the child’s parents had never married or had divorced than if one of the child’s parents had died.

References

Boggess, S. (1998) “Family Structure, economic status, and Educational Attainment” 11(9) Journal of Population Economics,
205
222.

Corak, Miles (2001), “Death and Divorce: The Long-term Consequences of Parental Loss on Adolescents” 19(3) Journal of Labor Economics,
682-715.

Fronstin, P. et al. (2001) “Parental Disruption and the Labour Market Performance of Children When they Reach Adulthood” 14(4) Journal of Population Economics, 137 – 172.

Lang, K. and J. L. Zagorsky (2000) “Does Growing Up With a Parent Absent Really Hurt?” 36(2) The Journal of Human Resources, 253-272.

McLanahan, S., and G. Sandefur, Growing up with a Single Parent (Cambridge, Mass.: Harvard University Press), 1994.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Mohamed Amery was a research assistant with Economica and an honours economics student at the University of Calgary.

Experience-Rating of Automobile Insurance: A Good Idea that Won’t Work

by Christopher Bruce

This article first appeared on page A21 of the October 16, 2003 Calgary Herald, and then in the summer 2003 issue of the Expert Witness.

Imagine you have two drivers who drive the same kind of car, live in the same city, and have the same driving record over, say, the last three years. Doesn’t it make sense that they should pay the same automobile insurance premiums?

Apparently, it made sense to the provincial government’s Automobile Insurance Reform Implementation Team. Yesterday, they recommended legislation that will require automobile insurance companies to use “experience rating.”

In a nutshell, experience rating refers to a system in which the only factor that determines your premiums is your driving record. All drivers who have no “experience” of accidents, speeding violations, drunk driving charges, etc. pay the same, relatively low base premium. Then, as they experience one or more of these events, their premiums rise accordingly – and, as they have additional years in which they do not experience these events, their premiums decline.

Experience rating has two highly desirable characteristics. First, the individual driver has complete control over his or her premiums. If you drive cautiously, avoiding accidents and driving violations, your premiums will decline to the lowest available rate.

Most importantly, your rate will not be higher than anyone else’s just because you happen to belong to a group, like young males, that has a relatively high accident rate.

Second, it has been shown consistently that when insurance premiums are related to experience, accident rates fall. When individuals know that they can reduce their premiums significantly by driving more carefully, they do so. And, of course, if the number of accidents decreases, so will insurance premiums.

It seems like experience rating is a win-win proposition. If so, then why hasn’t it been introduced before? The simple answer is that it results in a situation in which insurers know they will make substantial profits on some classes of customers and lose money on others. Thus, it gives them a strong incentive to refuse to insure the money-losing group.

In the scheme proposed by the government, that group will be composed primarily of young males.

Insurers will lose money on them because the number of accidents a driver has had in the past is only loosely related to the number that they can be expected to have in the future. What decades of statistics tell us is that a nineteen year-old male with a perfect, three-year driving record is more likely to have an accident in the next year than is a forty-year old male with the same driving record.

And a nineteen year-old who had an accident last year is more likely to have an accident next year than is a forty-year old with the same experience.

This means that insurers will expect to pay out more claims to nineteen year-old drivers than to forty year-old drivers.

Assume, for example, that 10 percent of nineteen year-old drivers who have had a clean record for three years will have an accident in the next year; whereas only 5 percent of forty year-olds with a similar record will have an accident next year. If the average accident costs the insurance company $10,000, then it will expect to pay out an average of $1,000 for each nineteen year-old and $500 for each forty year-old.

If the government forces insurers to charge the two groups the same premium, they will have to charge something between $500 and $1,000 just to cover their expected claims costs. For example, if the two groups were the same size, the premium would be $750 (the average across the two).

But this means that they will expect to make a $250 profit on the average driver in the older group and a $250 loss on the average driver in the younger group.

As insurance companies are out to make profits, we can expect that they will respond by doing their best to attract older drivers – and to turn away younger drivers.

The stakes are high. Those companies that find themselves with a relatively high percentage of young drivers will lose money and will soon be forced out of the market. Companies will use every loophole at their disposal to attract as many drivers in the older age groups as possible.

Advertising will be focused on older drivers – ads will appear primarily in magazines that appeal to middle-aged consumers, for example, and music in TV ads will be taken from the 1960s. Agents will be instructed to make it difficult for younger drivers to obtain insurance. And incentives, like toaster ovens for new clients, will be offered that will appeal primarily to older drivers.

The result is that the government will have to introduce ever-stricter regulations, to ensure that all drivers are able to obtain insurance. It will be interesting to see whether this degree of interference in the private sector is something that a market oriented government is willing to countenance.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Selecting the Discount Rate – An Update

by Christopher Bruce, Derek Aldridge, Kelly Rathje, and Scott Beesley

This article first appeared in the spring 2003 issue of the Expert Witness.

In the Autumn 2000 issue of this newsletter, we conducted an extensive review of the various methods of measuring the real rate of interest, or discount rate, and presented evidence concerning the movement of those measures over the period 1995-2000.

That survey was subsequently updated in our Winter 2001/2002 issue (Vol. 6, No. 4). What we found was that interest rates had begun to fall, relative to the historically high levels that had persisted over most of the 1990s.

At that time, we concluded that the best estimate of the long-run discount rate was 3½ percent. But we also argued that, as interest rates on short-term bonds and GICs were lower than those on longer term investments, it would be appropriate to employ an interest rate of 2½ percent on the first five years of any investment.

The purpose of this article will be to provide five additional quarters (15 months) of data to determine whether the trend we observed at the beginning of 2002 has continued, or whether a revision in our recommended interest rate is appropriate.

Revised data

Tables 1 and 2 provide updates of the information contained in the equivalent tables of the Winter 2001/2002 article. In particular, we have added data for all four quarters of 2002 plus the first quarter of 2003.

Table 1 reports the “raw” data from which some of the real interest rate figures in Table 2 have been calculated. The first column reports the “core rate of inflation” – a measure of the rate of inflation that removes the effects of change in those components of the price index that often move erratically, such as food, energy, and taxes. It is often argued that this measure offers a more reliable predictor of future changes in prices than does the “standard” measure of price inflation. (See the Autumn 2000 article for a detailed description of the core rate of inflation.)

The next three columns in Table 1 report the rates of return on Government of Canada 5-year and 10-year bonds and on 5-year Guaranteed Investment Certificates (GICs). The former represent the minimum rates of return that investors can expect on safe investments. The rate of return on GICs, on the other hand, represents the interest rate available on a mixed, low-risk portfolio of stocks and bonds.

Table 1

Table 2 reports seven measures of the real rate of interest – that is, the rate of interest net of the expected rate of inflation. The first of these is the market-determined rate of return on “real rate of return bonds” – bonds whose value is denominated in terms of the real rate of interest. These bonds are of particular importance because they are purchased by sophisticated investors and because they tend to held for long periods of time.

The second, fourth, and sixth columns report the 5- and 10-year government bond interest rates and 5-year GIC rates net of the core inflation measure.

Finally, columns three, five, and seven report the government bond and GIC rates net of the Bank of Canada’s target rate of inflation of 2 percent. As the Bank has managed to keep the core rate of inflation within a small band around this target for the last eight years, it is widely believed that 2 percent is the rate that is expected by most investors. That is, investors are believed to act as if the real rate of interest is the observed, nominal rate less 2 percent.

Table 2

Interpretation of the data

The data in Table 2 indicate that real rates of interest have continued the downward trend that began in 1996/1997. Whereas we concluded a year ago that long-term interest rates were approximately 3½ percent and short-term rates approximately 2½ percent; it appears that those rates have now fallen to 3 percent and 2¼ percent, respectively.

Note that the latter rate is close to the rates reported in the Bank of Canada’s Monetary Policy Report of April 2003 (Chart 19, p. 24).

In addition, 3 percent is the rate at which the Bank of Canada recently issued a new set of 33-year real rate of interest bonds. As we argued in the Autumn 2000 issue of the Expert Witness, the rate of return on these bonds is a particularly reliable estimate of the expected real interest rate as they are purchased primarily by large institutional investors (like pension funds) that have made considerable investments in the prediction of future rates of interest and inflation.

For this reason, we believe that it would be appropriate to revise our existing 2½ and 3½ percent two-part forecast of real interest rates. Based primarily on the observed rate on 5-year Government of Canada bonds, we propose to use a rate of 2¼ percent for the first five years of all calculations. For all subsequent years we propose to use a rate of 3¼ percent – though we note that a rate as low as 3 percent could be supported based on the most recent observed rates on 10-year Government of Canada bonds and based on the Bank of Canada’s current issue of real rate of return bonds. Our long-term rate is perhaps slightly conservative, but we will re-examine this issue next year and decide then if changes are warranted.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Scott Beesley is a consultant with Economica and has a Master of Arts degree (in economics) from the University of British Columbia.

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

Duty to Care for Orphaned Minors

by Christopher Bruce

This article was originally published in the April 24, 1998 issue of The Lawyers Weekly. We reproduced it in the Summer/Autumn 2002 issue of the Expert Witness because the topic had arisen in one of our cases.

In a number of recent cases, the courts have been asked to calculate the loss of dependency of orphaned minors. In all of the reported cases, these children have been taken into the care of relatives – aunts, uncles, grandparents, or stepparents. An important issue that is raised by this arrangement is whether the expenditures incurred by the surrogate parents should be set off against the children’s loss of dependency on their natural parent(s).

In the leading Ontario case of Butterfield v. Butterfield Estate (1996) 23 M.V R. (3d) 192 (Ont.C.A.), for example, two children aged six years and six months, respectively, were taken into the care of their aunt and uncle. The defendants argued that the children’s claim of dependancy on their mother’s income should be reduced by the value of the expenditures which their aunt and uncle (who planned to adopt them) would make on them.

Similarly, in the leading British Columbia case of Skelding (Guardian ad litem of) v. Skelding (1994) 118 D.L.R. (4th) 537 (B.C.C.A.), the defendants argued that the children’s loss of dependency on their mother was extinguished because their father (with whom they lived) had remarried.

The differing approaches that have been employed to resolve this issue provide evidence of a fundamental division in our courts with respect to the purpose of tort law. Two conflicting paradigms can be identified.

In what I will call the ex post approach, the court takes the view that, as the tortious act has already occurred, that act cannot be undone. Rather, the best the court can do is to ensure that the victims are restored, as best as possible, to the position they would have been in had the act not occurred.

In the competing, ex ante approach, the court recognises that any decision that it makes in the current case may influence the behavior of parties in similar, future cases. Hence, what is important in the current case is to set a precedent which will direct future parties to behave in the socially desirable manner.

The appellate court in Skelding clearly adopted the ex post approach. Relying heavily on the Supreme Court decision in Ratych v. Bloomer (1990) 69 D.L.R. (4th) 25, the majority concluded that the stepmother had replaced the natural mother. Hence, no further claim was necessary to return the children to the position they would have been in had their mother lived.

Notably, this decision is exactly consonant with a well-developed line of cases which have concluded that a widow(er)’s loss of dependency may be extinguished upon marriage to a new spouse whose income is similar to that of the deceased. Particularly important for Skelding was the B.C. case of Ball v. Kraft (1966) 60 D.L.R. (2d) 35 in which both the widow and her children were denied compensation after the date of her remarriage.

In addition to its reliance on Ratych, the B.C.C.A. also defended its decision by reference to B.C.’s Family Relations Act. This Act imposes a legal requirement on parents to provide “reasonable … support and maintenance of the child.” As “parents” are defined in the Act to include stepparents and guardians, the court found that the services which Mr. Skelding’s new wife provided to his children were not “gratuitous.”

Interestingly, in making the latter decision, the court came into direct conflict with its own decision in Grant v. Jackson (1986) 24 D.L.R. (4th) 598 which it had made only eight years earlier. In Grant the court had held that services provided by a father to his children, following the death of their mother (his wife), were not required by the Family Relations Act.

Despite Skelding’s grounding in Ratych, the vast majority of cases dealing with orphaned children have been careful to distinguish themselves from Skelding. Most of these cases employ what I called the ex ante approach to justify their decisions. In particular, they argue that the precedent established by Skelding may create perverse incentives for the friends and families of orphaned children.

The leading statements of this view appear in Tompkins (Guardian ad litem of) v. Byspalko (1993) 16 C.C.L.T. (2d) 179 and Ratansi v. Abery (1995) 5 B.C.L.R. (3d) 88. In both cases, the trial judges argued that if Skelding was followed, the risk would be created that “… in some cases, family members who would otherwise take orphaned children into their care may decline to do so until or unless an award has been made in the children’s favour.”

And in Tompkins, Spencer, J. went further, arguing that “… a surviving parent may refrain from remarriage, advantageous from the children’s point of view, because the presence of a new spouse who replaces services to the children may reduce their award”.

These cases, therefore, adopt the view that the finances and services provided by family members are in the nature of collateral benefits and should not be deducted from the children’s dependency on the deceased parent.

Most of the cases that adopt this view also respond to the argument in Skelding that the Family Relations Act (or its equivalent in other provinces) imposes a legal requirement that a “parent” provide reasonable support.

In Butterfield (cited above), for example, the Ontario Court of Appeal implied that an aunt and uncle had no legal obligation to provide for the children, even though they intended to adopt the children formally. And in Ratansi (cited above) and Schellenberg v. Houseman (1996) 18 B.C.L.R. (3d) 209, the courts concluded that support provided by family members who had been appointed legal guardians was also to be treated as a collateral benefit.

Yet, B.C.’s Family Relations Act would have defined the family members in all three of these cases to be “parents.” Either these cases were in error or Skelding was.

Finch, J.A., the dissenting judge in Skelding, offered a resolution to this dilemma. He noted, first, that fatal accident legislation generally requires that the damages must have “resulted” from the death of a family member. Conversely, he argued, support received from a third party could not be considered to have offset the plaintiffs’ loss unless that support also resulted from the death in question. He concluded, therefore, that, as the marriage of Mr. Skelding to his second wife could not be considered to have resulted from the death of his first wife, the support provided by the second wife to Mr. Skelding’s children must be considered to be a collateral benefit.

This argument notwithstanding, the minority view in Skelding faces another challenge. Finch, J.A. argued that the income of Mr. Skelding’s new wife should not be offset against the children’s loss of dependency on their natural mother; yet it is well-settled law in Canada that the new wife’s income should be offset against Mr. Skelding’s loss of dependency on his first wife. This discrepancy remains to be “explained.”

To summarise, the courts’ treatment of claims by orphans for loss of dependency offers insight into a question that goes to the foundations of tort law. Should the courts concentrate strictly on the facts of the case at hand – the ex post approach? Or should they take into account the impact that the decision in the current case will have on the future behaviour of other individuals – the ex ante approach? Although the response to Skelding (and to Ratych) suggests that most courts are leaning towards the ex ante approach, the issue is far from settled.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Connection between Labour Productivity and Wages

by Christopher Bruce

This article first appeared in the summer/autumn 2002 issue of the Expert Witness.

Many readers of this newsletter will have received personal injury damage assessments in which the expert has argued that wages in a particular industry will increase at some rate – for example, 1.5 percent per year – “because” output per worker (productivity) in that industry is projected to increase at that rate.

What I wish to show in this article is that, as appealing as this argument may be to the layperson, it is wrong. Not only does economic theory predict that the connection between industry productivity and wages in that industry will be tenuous at best; empirical evidence reveals that there has been virtually no connection whatsoever between industry wages and industry productivity in Canada.

I proceed by first describing the method that agencies like Statistics Canada use to measure labour productivity. I then describe the economic theory of how wages are determined within industries and occupations. In a third section, I contrast that theory with the theory of national wage determination. Finally, I present some recent statistical data concerning the relationship between the rate of growth of productivity and the rate of growth of wages at the industry level in Canada.

Measurement

Statistics Canada obtains an index of the “real”
level of output in each industry by dividing the total revenues received by the firms in that industry by an index of the industry’s prices. For example, if total revenue in the clothing industry was $100 billion in 2001 and the clothing retail price index was 125, the index of real output would have been calculated to be 800 million. If revenues rose to $110.5 billion in 2002 and the price index rose to 130, the output index would have risen to 850 (million).

Labour productivity, or output per hour of work, is then found by dividing the (real) output index by the number of hours worked by individuals in that industry. If clothing workers worked 100 million hours in both 2001 and 2002, for example, output per worker hour would be found to have increased from 8.00 to 8.50 between those years, or by 6.25 percent.

Note that there is no connection between revenues per worker and output per worker. It is quite possible, for example, for revenue to rise because prices have risen while labour productivity has remained unchanged. Conversely, even if output per worker has risen substantially, if prices have fallen revenue per worker may have remained constant or even fallen.

Theory – Industry Wage Levels

Those who believe that there is a connection between labour productivity and wages within an industry (or occupation) implicitly assume the following: When output per worker increases, workers’ contributions to firm revenue increase causing demand for workers to increase also. As wages are determined by supply and demand, an increase in demand will imply an increase in wages.

This “theory” is wrong for two reasons. First, there is no necessary connection between output per worker and revenue per worker. As was pointed out above, if demand for the industry’s product is decreasing, the price that can be charged for that product will also be decreasing. Hence, even if output per worker rises, revenue per worker may fall.

Furthermore, when output per worker increases, the industry will have to sell additional units of output; that is, industry supply will rise. But, by the laws of supply and demand, when supply increases, prices decrease. That is, the increase in worker productivity may cause a decrease in prices.

In some cases, this decrease in prices is so extreme that an increase in worker productivity may actually cause a decrease in revenue per worker. The clearest example of this phenomenon has occurred in agriculture, where farm incomes are under constant downward pressure even though productivity gains have been greater in that sector than in most other industries.

Second, even if an increase in labour productivity does lead to an increase in revenues generated per worker, it is not necessarily the case that the consequent increase in demand will be associated with a long run increase in wages (relative to other industries). The reason for this is that, in the long run, additional workers can be supplied to that industry, which offsets the upward pressure on wages. That is, when demand for an industry’s workers increases, wages in that industry do not rise relative to wages in other industries. Rather, it is employment in the high productivity industry that will rise relative to employment in other industries.

Assume, for example, that there is a large group of workers who would be approximately indifferent between working as plumbers, carpenters, and electricians. Assume also that, initially, all three receive the same wage rate. Now, if productivity rises among electricians, there will be an increase in demand for electricians. In the short run, say a year or two, it will not be possible to train additional electricians and wages may be bid up.

But, when wages are higher among electricians than among plumbers and carpenters, students graduating from high school will prefer to train as electricians. Soon, the supply of new electricians will increase and the supply of new carpenters and plumbers will decrease. Wages will fall among electricians and will rise among plumbers and carpenters.

Ultimately, the wages of all three occupations will equalize. All three will enjoy higher wages than they did initially. But, among plumbers and carpenters this will have occurred without any increase in productivity. And, among electricians, the wage increase will have been much smaller than the productivity increase, because the effect of that increase will have been diluted by the influx of workers from other occupations.

Indeed, if the initial number of electricians had been considerably smaller than the number of plumbers and carpenters, it is possible that the wage increase experienced by all three groups would have been negligible. The number of workers who would have to leave the plumbing and carpentry trades would have been so small, relative to the total numbers in those trades, that their exit would have had very little effect on wages in those occupations.

The primary effect of the productivity increase among electricians is that the number of electricians will increase and the numbers of plumbers and carpenters will decrease.

Similar effects can be seen in other industries. We know, for example, that in the last 50 years there have been far greater productivity gains in “fast food” restaurants than in restaurants serving “classic cuisine.” Yet, wages have not increased in the former relative to the latter. The primary reason is that every increase in demand for fast food workers has been met by an influx of workers from other unskilled industries.

This is not to say that there is no connection between productivity and wages at the industry level. If the number of workers in an industry is not responsive to changes in wages, an increase in productivity may produce a permanent wage increase. There may, for example, be institutional barriers preventing additional workers from entering an industry – such as union regulations or restrictions on the numbers of students training for that industry at university or college. Alternatively, there may simply be a limited number of individuals who have the aptitude to enter certain industries or occupations. Once that number had been exhausted, further wage increases might not call forth additional labour supply.

Theory – National Wage Levels

Even if there is only a limited connection between wages and productivity at the industry level, there may still be a strong connection at the national level. When productivity gains drive up wages in one industry or occupation, it is anticipated that workers will be drawn from other industries and occupations, thereby returning relative wages to their initial level. If productivity increases at the
national level, however, the equivalent effect would require that workers be drawn from other countries. But, as Canada restricts the number of immigrants, this effect will be much less important for national wage levels than it was for industry wage levels.

Also, a productivity gain at the national level is less likely to lead to a reduction in output prices than is an equivalent gain at the industry level. When output increases in an industry, everything else being constant, the industry may have to lower prices in order to sell that increase. When output increases in the nation as a whole, however, all workers will have higher incomes and those incomes may be used to purchase the increased output. In a sense, the increased output “creates” the increased demand to purchase that output. Prices need not fall.

And if prices do fall, the “real” incomes of all workers will increase. That is, even if observed (or nominal) wages do not change, workers will be able to buy more goods and services with their incomes. They will be better off in a “real” sense. Thus, an economy-wide increase in productivity could cause an increase in the welfare of workers, not through an increase in observed money wages, but through a decrease in average prices.

Evidence

The evidence concerning the connection between industry-level wages and productivity is clear. In its recent publication, Productivity Growth in Canada, Statistics Canada provided information concerning relative productivity growth and relative changes in wages for 46 Canadian industries, from 1961-1995.

These statistics have been plotted in the figure below, with industries ranked from lowest to highest productivity growth over that period. It is seen clearly in that figure that there is virtually no correlation at all between an industry’s relative productivity growth and its growth in relative wages. Indeed, regardless of an industry’s growth in productivity, its relative wages remained unchanged.

Figure 1

Conclusion

There are sound theoretical reasons for predicting that there will be very little correlation between an industry’s productivity growth and its wage growth. The empirical evidence provides strong support for this prediction. Indeed, that support is so strong that it is incumbent on any expert who would argue that a correlation exists between productivity and wages to justify that argument.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Complementarity in the Retirement Behaviour of Older Married Couples: An Update

by Daryck Riddell & Christopher Bruce

This article first appeared in the spring 2002 issue of the Expert Witness.

When forecasting the earnings streams of individuals over 50, one of the most important factors is predicted age of retirement. For example, changing the projected retirement age from 63 to 60, when the individual is currently 57, will decrease the future loss of earnings by approximately 50 percent.

It is often argued that one indicator of likely retirement age among individuals in this age group is the retirement decision of the plaintiff’s spouse. If a 57 year-old woman’s husband has already retired, that could indicate that she will retire earlier than would otherwise have been predicted.

Economists have observed three factors that might suggest a correlation between the retirement ages of spouses. These we refer to as: similarity of profiles, sharing of household finances, and complementarity of leisure.

Similarity of Profiles

Sociologists, psychologists, and economists have long observed that individuals choose mates who have socio-economic profiles similar to their own. If professionals marry professionals or high school leavers marry high school leavers, then the retirement ages of spouses will be similar, not because the retirement decision of one spouse affected the retirement decision of the other, but because the spouses’ decisions were affected by similar work-related influences.

Spouses who both worked in physically demanding jobs might both retire earlier than the population average, for example. Or spouses who were both self-employed – say, doctors or lawyers – might both retire later than average. In such cases, one might be tempted to conclude that because one retired soon after the other that the retirement of the first had “caused” the retirement of the second when, in fact, what had happened is that they had both been affected by the same external factors.

Sharing of Income

It has long been recognised in the economics literature that the likelihood that one spouse will leave the labour market will increase as the income of the other spouse increases. That is, the spouses of high income earners are more likely to be retired at any age than are the spouses of low income earners.

This observation suggests two hypotheses. The first of these is that if one spouse’s social security benefits increase, the “other” spouse will be more likely to retire. Evidence for this hypothesis has recently been obtained in two studies. Both Coile (1999) and Baker (2002) found that both wives and husbands were more likely to retire when the wives were eligible for income supplements than when the wives were not. It appears that wives’ retirement ages, however, were not strongly influenced by husbands’ availability of income supplements.

The second implication of “sharing of income” is that spouses’ retirement ages will be negatively correlated. That is, if one spouse has retired, the other will be less likely to retire. The reason for this is that when one spouse retires, that spouse’s income decreases (often, dramatically), thereby decreasing the probability that the other spouse will leave the labour force.

Complementarity of Leisure

A third hypothesis is that spouses will obtain greater pleasure from retirement if they retire together. In economic terminology, the benefits that one spouse obtains from leisure are complementary to the amount of leisure enjoyed by the other. For example, if the wife plans to spend her retirement travelling, she may expect to obtain more pleasure from her retirement if she anticipates that her husband will also be retired and will travel with her.

Clearly, this hypothesis suggests that spouses’ retirement ages will be positively correlated. That is, if one spouse retires, the other will be more likely to retire, as the second spouse will expect to obtain greater benefits from retirement leisure than if the first spouse had not retired.

Blau (1998) has recently provided evidence that this complementarity is an important factor in determining spouses’ retirement ages. His study examines the joint labour force behaviour of older married couples in the United States.

Using the Retirement History Survey (RHS), a longitudinal study that followed men and women who were age 58-63 in 1969, Blau constructs labour force histories for each married couple from the time the husband turned 55. The joint labour force status of the couple in any given time period is characterized by four possible states: both employed, neither employed, husband employed but wife not, wife employed but husband not.

The data set has some interesting features. Foremost among them is that the labour force transitions of one spouse are strongly associated with the labour force status of the other spouse. The wife’s exit rate from the labour force is 63 percent higher when the husband is not employed than when he is employed. Similarly, the husband’s exit rate when his wife is not working is 53 percent higher than when she is employed. Conversely, quarterly entry rates for both husband and wife are larger if the other spouse is employed rather than not employed.

Another feature is that the incidence of joint retirement is quite large. Between 11.4 percent and 15.7 percent of all couples exit the labour force in the same quarter and between 30.3 percent and 40.6 percent exit in the same year.

The key conclusion from this paper is that there is strong evidence of the preference to share leisure. This sample from the 1960s and 1970s shows a high incidence of joint retirement and a positive effect of non-employment of one spouse on the other spouse’s labour force exit rate, as well as a negative influence of non-employment of one spouse on the other’s entry (or re-entry) rate.

Summary

Economists have put forward three hypotheses concerning the likelihood that the retirement ages of spouses will be correlated. The first of these – similarity of profiles – suggests that, on average, spouses will retire at similar times because spouses tend to have similar socio-economic profiles. That is, the factors that act on retirement age independently of marital status will affect husbands and wives in similar manners.

The second hypothesis is that individuals will be more likely to retire, the higher is their spouse’s income. This hypothesis suggests that there will be a negative correlation between spouses’ retirement ages. When one spouse retires, family income will decrease and the second spouse will be provided with an incentive to remain in the labour force.

Finally, if the leisure activities of husband and wife are complementary, there will be a positive correlation between spouses’ retirement ages. Recent evidence suggests that this effect has been a significant determinant of retirement ages in the United States.

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Daryck Riddell was a graduate student in Economics at the University of Calgary

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Destruction of evidence

by Christopher Bruce

This article was originally published in the Winter 2001/02 issue of the Expert Witness.

In many cases, the information required to establish negligence remains in the possession of one of the parties. In the absence of any penalties, a party who believes that this evidence may suggest that he or she should be held liable will have an incentive to destroy the evidence.

The purpose of this article is to develop a model of the legal process that will offer insight into the determination of legal remedies for the destruction of evidence by a defendant. I base this model on the assumption that the first role of such remedies must be to discourage the defendant from destroying any information that might reasonably be expected to assist the court in the determination of liability.

Three Questions

I believe that any legal analysis of the destruction of evidence by a defendant must investigate three questions:

  • Did the defendant have reason to believe that it was the subject of litigation?
  • Did the defendant believe that the information in its possession could assist the court in the determination of negligence or liability?
  • Did the defendant intentionally or negligently destroy the evidence, or was that destruction “accidental?”

Was the Defendant the Subject of Litigation?

Businesses and individuals destroy private information every day. That destruction only becomes of concern to the court when it has an impact on the court’s ability to assess liability (and assign damages). For that reason, no legal “remedy” is required if a party had no reason to believe that destruction of information would have a bearing on any legal proceeding.

For example, if a factory has no reason to believe that its emissions have any harmful effects on its neighbours, destruction of information concerning those emissions should not subject it to penalties. To rule otherwise would require that all individuals and all businesses save all information indefinitely. Only if a subjective test concludes that the defendant should have been aware that its actions might be the subject of a legal action should it be held responsible for preserving records of those actions. This test should be stronger, the greater was the likelihood that the actions in question might become the subject of litigation.

Was the Information Determinative of Liability?

Assume that the first question has been answered in the affirmative – the defendant has been found to be aware of the possibility of litigation. Assume also that it could be determined ex post that the defendant knew that information in its possession would prove it to be negligent and liable; and that the defendant has intentionally destroyed that information.

The appropriate legal remedy would be to impose the same level of liability and damages on the defendant as would have been imposed if the information had been preserved. Such a ruling would simultaneously retain the plaintiff’s right to compensation and remove the incentive for the defendant to destroy the information.

Thus, if the court was able to determine ex post that the destroyed evidence would have contributed to the determination of liability, its appropriate response would be to reach the same conclusion that would have been reached had the information been preserved.

Conversely, if the court was able to determine ex post that the destroyed information would not have contributed to the determination of liability, its appropriate response would be to excuse the destruction of that information.

But when evidence has been destroyed, the courts often cannot determine whether that evidence would have been determinative of liability. (If liability could have been determined without that information, the issue of destruction of evidence would not have arisen in the first place.)

It is always in the defendant’s interest to argue that the information that it has destroyed was irrelevant to the case at bar. Once that information has been destroyed, it will be difficult, if not impossible, to lead either objective or subjective evidence to contradict the defendant’s argument.

The court is left with a dilemma. If it knew that the destroyed evidence would have proven the liability of the defendant, it should set damages as if liability had been proven. Whereas if it knew that the destroyed evidence would not have been of assistance to the court, it should ignore that destruction. But the defendant will always argue the latter and the court (and the plaintiff) will not be able to prove otherwise.

The issue then, is how can the court induce the defendant to preserve evidence that might prove to be relevant to the determination of liability? The simplest rule would be to place the onus on the defendant to prove that the destroyed evidence did not bear the importance that the plaintiff has claimed for it. That is, the normal onus of proof would be reversed.

Under this rule, if the defendant was of the honest opinion that the information it proposed to destroy was not relevant to the case, it would be induced to preserve that information until the trial date, if it was inexpensive to store. Or, if the information was expensive to store, it would be induced to offer to obtain the permission of the plaintiff to destroy that information. (If the plaintiff refused, the defendant might be allowed to claim storage costs against the plaintiff if the plaintiff’s case was not successful.)

And if the defendant was of the opinion that the information was relevant to the determination of liability, it would have an incentive to preserve that information. If it preserves the information, there may be some chance that it will be able to convince the court that it was not negligent or liable. Whereas if it destroyed the evidence, the proposed rule would find it liable with certainty.

That is, under all circumstances, the proposed rule would induce the defendant either to preserve potentially damaging evidence or to obtain the plaintiff’s permission to destroy that evidence. As this is the desired outcome, the rule may be said to be efficient.

Did the Defendant Destroy the Evidence “Intentionally?”

In the preceding section, I argued that if the defendant intentionally destroyed evidence, it should be found responsible for the same level of damages that would have been awarded had it been found liable. But what would the efficient rule be if the evidence was destroyed for reasons that were beyond the control of the defendant? Or if the evidence was destroyed as a result of the negligence of the defendant?

In the former of those cases – the destruction was “an act of God” or was, for other reasons, unforeseeable – the imposition of damages could not have the desired effect discussed above, of encouraging the defendant to preserve the information.

For example, if the defendant had stored information on a type of video tape that would disintegrate over time, the threat of damages could not induce the defendant to alter that behaviour if it had no reason to suspect that the tape had that characteristic. Similarly, the threat of damages could not induce it to protect itself against unforeseen floods or acts of terrorism.

In such cases, therefore, the courts’ rulings could not have the desired effect that I discussed above; namely, that of encouraging defendants to preserve valuable information. Rather, the only effect that imposition of damages could have in such cases would be to make the defendant the “insurer” of the plaintiff – a result that the courts have often rejected. Therefore, in cases of unforeseen destruction of evidence, the defendant should be excused from any liability to the plaintiff.

The more complex cases are those in which defendants recognised that their actions (or inactions) might lead to the destruction of evidence, but failed to alter their behaviour accordingly. For example, the defendant might have recognised that information would be lost if certain documents became wet but failed to provide storage facilities that were protected against moisture.

The efficient rule in this situation is to place the onus on the defendant to prove that the evidence does not have the import claimed by the plaintiff if it can be shown that the defendant’s actions (or inactions) were negligent. As with the rule concerning the intentional destruction of evidence, discussed above, this rule would leave the decision concerning the destruction of information in the hands of the party that is able to determine the probability that that information will be relevant to the assessment of liability.

As long as the defendant is aware that the information in its possession may be relevant to the determination of liability, this rule will normally induce the defendant to take all those precautions necessary to avoid a finding of negligence. That is, rather than face the prospect of being found liable for the plaintiff’s damages, the defendant will normally prefer to meet its standard of care. As this is the desired outcome – the court would never ask the defendant to take more precautions than necessary to meet its standard – this is the efficient rule.

Spoliation

In some jurisdictions the courts have been asked to treat the destruction of evidence as a tortious act, independently of whether that destruction affected the determination of liability. Under this tort, often called spoliation, the plaintiff asks that the defendant be punished for the harm it has caused to the legal system.

Implicitly, the argument in this article has been that no independent tort need be established. The harm caused by the destruction of evidence is that both the compensatory and deterrent effects of tort law are impaired. If the underlying function of the law is to ensure that innocent victims are compensated, for example, the destruction of evidence may prevent that function from being performed.

If a set of rules can be designed that induces defendants to take all reasonable steps to preserve relevant information, the basic function of tort law will also be preserved. But that is precisely what the rules described in this article can be expected to do. Hence, no additional rules – such as punishing the defendant for the destruction of evidence that could not reasonably have been expected to assist the court in its deliberations – are necessary.

Summary

My argument in this article has been that the goal of rules concerning the preservation of evidence must be to induce defendants to avoid the intentional or negligent destruction of any information that they believe may be useful in the determination of liability (or damages). I have argued in this paper that a sufficient rule is that a defendant that has intentionally or negligently destroyed evidence be treated as if liability had been found against him or her.

Furthermore, no distinction should be made between those cases in which the defendant argues that the evidence would not have been of value to the court and those in which it admits that the evidence would have been relevant. The only defences available to the defendant should be (a) that the destruction of the evidence was unforeseeable; or (b) that the destruction of the evidence had occurred even though the defendant had met its standard of care.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Selecting the Discount Rate – An Update

by Christopher Bruce, Derek Aldridge, Scott Beesley, and Kelly Rathje

This article was originally published in the Winter 2001/02 issue of the Expert Witness.

In the Autumn 2000 issue of this newsletter, we conducted an extensive review of the various methods of measuring the real rate of interest, or discount rate, and presented evidence concerning the movement of those measures over the period 1995-2000.

At that time, we concluded that our best estimate of the long-run discount rate was 4.0 percent. But we added the caveat that, as interest rates in 2000 had deviated significantly from the average of the preceding years, it would be important to maintain a close watch on those rates – to determine whether 2000 was an aberration or whether it represented the beginning of a new trend.

In particular, we concluded that article with the statement:

If bond rates do not rise relative to the rate of inflation in the near future, we will be revising our real rate of interest forecast downward.

The purpose of this article will be to provide five additional quarters (15 months) of data to determine whether such a revision is appropriate.

Revised data

Tables 1 and 2 provide updates of the information contained in Tables 1 and 2 of the Autumn 2000 article. Four changes have been made to the latter tables. First, we have added data for the fourth quarter of 2000 and for all four quarters of 2001. Second, in some cases, the relevant statistical authorities have revised their estimates of the figures we reported previously. In those cases, we have provided the revised figures.

Third, we have added information concerning interest rates on five-year Government of Canada bonds. Finally, in the interest of space, we have omitted the estimates of the real rate of interest that relied on information concerning the “standard” inflation rate.

Table 1

Table 1 reports the “raw” data from which some of the real interest rate figures in Table 2 have been calculated. The first column reports the “core rate of inflation” – a measure of the rate of inflation that removes the effects of change in those components of the price index that often move erratically – such as food, energy, and taxes. It is often argued that this measure offers a more reliable predictor of future changes in prices than does the “standard” measure of price inflation.

The next three columns in Table 1 report the rates of return on Government of Canada 5-year and 10-year bonds and on 5-year Guaranteed Investment Certificates (GICs). The former represent the minimum rates of return that investors can expect on safe investments. The rate of return on GICs, on the other hand, represents the interest rate available on a mixed, low-risk portfolio of stocks and bonds.

Table 2 reports seven measures of the real rate of interest – that is, the rate of interest net of the expected rate of inflation. The first of these is the market-determined rate of return on “real rate of return bonds” – bonds whose value is denominated in terms of the real rate of interest. These bonds are of particular importance because they are purchased by sophisticated investors and because they tend to be held for long periods of time.

The second, fourth, and sixth columns report the 5- and 10-year government bond interest rates and 5-year GIC rates net of the core inflation measure.

Finally, columns three, five, and seven report the government bond and GIC rates net of the Bank of Canada’s target rate of inflation of 2 percent. As the Bank has managed to keep the core rate of inflation within a small band around this target for the last six years, it is widely believed that 2 percent is the rate that is expected by most investors. That is, investors are believed to act as if the real rate of interest is the observed, nominal rate less 2 percent.

Table 2

Interpretation of the data

The data in Table 2 indicate that real rates of interest are lowest on the shortest-term investments, GICs and 5-year bonds, and highest on the longest-term investments, 10-year bonds and real rate of interest bonds. This suggests to us that investors believe that the current slowdown in the economy, which has induced central banks to lower interest rates very significantly, may continue for two or three years but will not continue in the long term.

For this reason, we believe that it would be appropriate to adopt a two part forecast of real interest rates. Based primarily on the observed rate on 5-year Government of Canada bonds, we propose to use a rate of 2.50 percent for the first five years of all calculations. Based primarily on the observed rate on 10-year Government of Canada bonds, we propose to use a rate of 3.50 percent for all subsequent years. Note that the latter rate is close to the average real rate of return on GICs over the period 1964 to 1998, (3.58 percent), reported in Bruce, Assessment of Personal Injury Damages, Third Edition, at page 231.

Once again, however, in recognition of the uncertainty facing our economy, we will revisit this question at the end of this year.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Scott Beesley is a consultant with Economica and has a Master of Arts degree (in economics) from the University of British Columbia.

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

No-Fault Automobile Insurance

by Christopher Bruce & Angela Tu Weissenberger

This article was originally published in the Autumn 2001 issue of the Expert Witness.

In a recent paper, Norma Nielson and Anne Kleffner, of the Faculty of Management, University of Calgary, recommended that Alberta adopt a no-fault automobile insurance system.

The purpose of this article is to provide a response to Nielson and Kleffner. The article is divided into five sections, in which we discuss:

  • the deterrent effect of tort rules,
  • the high cost of no-fault insurance systems,
  • arguments concerning the role of lawyers,
  • evidence concerning the costs of bodily injury claims, and
  • evidence concerning insurance fraud.

The Deterrent Effect

Although Nielson and Kleffner argue that one of the functions of an ideal “…system for compensating accident victims [is to] … provide individuals with incentives to behave in a way that minimizes accidents and the resulting injuries…” they choose to ignore this function in their paper. As the majority of recent empirical studies have shown that accident rates are higher in no-fault regimes than in tort-based regimes, their failure to address this issue seriously biases their conclusions.

For example, recent evidence suggests that fatal accident rates are between 5 and 10 percent higher in no-fault jurisdictions than in tort-based jurisdictions. This means that, at the 1998 highway fatality level of 429, the introduction of no-fault insurance would result in the deaths of between 21 and 42 Albertans per year.

We have identified five studies published in the 1990s that offer rigorous analyses of the effects of no-fault insurance on automobile accident rates. These studies argue that no-fault may reduce the deterrent effect of insurance in two ways.

First, insurers have historically provided a deterrent to accident-causing behaviour by increasing drivers’ insurance premiums when they have been found to be at fault for accidents. Under no-fault insurance systems, however, fault is not measured. As a result, insurance companies find it more difficult to tie premiums to driving behaviour and the deterrent effect is weakened.

Second, in tort systems, the party that has been found to have “caused” an accident is required to bear most of his or her own costs. The threat of having to bear these costs is presumed to act as a deterrent to accident-causing behaviour. In no-fault systems, on the other hand, the parties are compensated fully for all of their costs, regardless of fault. Thus, the threat of having to bear those costs is removed and the deterrent effect of insurance is once again weakened.

A concern of all of the studies identified by us is that, because the incentive to report accidents may vary among insurance regimes, changes in the reported number of accidents may not reflect true changes in the underlying accident rate. Accordingly, three of the studies restricted their analyses to fatal accident rates, as these rates are not subject to reporting error. All three studies found that the incidence of fatal accidents increased following the introduction of no-fault.

In the first of these, Devlin (1991) found that the number of fatal accidents increased by 9.62 percent after the introduction of no-fault in Quebec.

Similarly, Cummins et. al. (1999) found that fatal accident rates were between 5.5 and 9.9 percent higher in US states that had no-fault insurance than in those that permitted full access to the tort system.

And Sloan et. al. (1994) estimated that for every 10 percent of drivers who were denied access to the tort system (by no-fault insurance), the fatal accident rate rose by 7.2 percent. (For example, a move from a system that permitted full access to tort law to one that allowed access to only 80 percent of drivers would increase the fatal accident rate by 14.4 percent.)

A second approach was adopted by Cummins and Weiss (1991). They argued that, as no-fault insurance systems did not alter the legal rules involving property damage claims, there should be no direct effect of no-fault on those claims. However, if no-fault affected driving behaviour through changes to the rules concerning personal injury claims, an indirect effect on property claims would be expected. That is, if no-fault reduced the incentive to take precautions to avoid personal injury, that reduction should increase both personal injury and property damage claims.

Accordingly, Cummins and Weiss compared property claims between tort and no-fault states. Their finding that property claims were 4 percent higher in no-fault states led them to conclude that the introduction of no-fault had reduced the deterrent effect of automobile insurance and increased the number of automobile accidents.

Finally, Devlin (1997) investigated the effect of no-fault insurance on the severity of automobile accidents in the United States. She found that the probability of sustaining a serious accident was significantly higher, and the probability of sustaining a minor accident significantly lower, in no-fault states than in tort states. That is, even if the overall accident rate was the same between two states, the average severity of accidents would be higher in the no-fault state than in the tort state.

These studies show convincingly that no-fault insurance reduces the incentive for drivers to take precautions. The result is that, under no-fault insurance, there is an increase in the number of fatalities, in the overall number of automobile accidents, and in the average severity of accidents. Although these effects were ignored by Nielson and Kleffner, it is clear that they must be taken into account when changes to the insurance system are being considered.

The High Cost of No-Fault Insurance

Empirical analyses of no-fault insurance jurisdictions indicate that there are virtually no cost savings to be obtained by switching from tort law to no-fault insurance. Indeed, experience in no-fault states and jurisdictions around the world indicate that the system is not effective in reducing the overall cost of accident compensation.

Our review of the research indicates that there has been no realization of lower insurance premiums as a direct result of the adoption of no-fault insurance.

  • According to the National Association of Insurance Commissioners data (1988-1998), liability premiums in the US no-fault states are amongst the highest in the country. New Jersey (a no-fault state) has the highest average liability premiums and exceeds the national average premium by 71%.
  • In their analysis and evaluation of no-fault Laws, the Foundation for Taxpayers and Consumer Rights (1997) point out:
    • Though many states have experimented with various forms of no-fault plans, few have been shown to obtain reduced insurance premiums.
    • No-fault states have the highest average automobile insurance premiums.
    • Between 1989 and 1995 premiums in mandatory no-fault states rose nearly 25 percent more than in no-fault states.
    • Premiums fell immediately in states that repealed no-fault insurance.
  • The Insurance Bureau of Canada (1991) reports that during the first year following the implementation of the no-fault scheme in Ontario, insurance industry profits increased by $750,000,000 with no appreciable decrease in premiums.
  • Nielson and Kleffner (2001) report that no-fault has not reduced auto insurance costs, but rather, costs are higher due to the very generous benefits paid out (e.g. in Quebec and Manitoba there is no time or amount limit on medical payment benefits). This further raises the question of how a no-fault system implemented in Alberta can realize significant cost savings.
  • The few jurisdictions that cited savings due to no-fault attribute the reduction in costs to the elimination of non-economic loss award for persons whose injuries do not exceed a prescribed threshold (Carroll and Kakalik, 1991). Regardless of the threshold level, non-economic loss is real. Eliminating or restricting individuals’ compensation for losses concerning pain and suffering and mental anguish means denying them the funds necessary for physiotherapy, psychological treatment etc. which are critical to reparation for non-economic loss. This is at odds with the very intent of no-fault insurance, which is to compensate an individual adequately for losses arising from the accident regardless of fault.
  • Nielson and Kleffner claim that no-fault plans match compensation more closely with economic loss by increasing the fraction of economic loss that is compensated and by reducing the amount of compensation paid people in excess of their economic loss. In other words, they recommend reducing victim compensation in order to save money.

Attorney Involvement

Nielson and Kleffner suggest that attorney involvement in claims is a key contributor to the escalation of bodily injury costs. Their conclusions are based on a study conducted by the Insurance Research Council that examined medical utilization in cases that did and did not involve attorney representation. That study concluded that represented claimants were more likely than non-represented to seek treatment from medical practitioners and that the former had a higher average number of visits to practitioners than did the latter.

Nevertheless, the authors suggested that claimants represented by lawyers were no better off than those who were not represented. In particular, despite the fact that average gross compensation to the represented claimants was higher than that to claimants not represented; the former netted less for their injuries than did the latter. The difference is explained by the fact that represented claimants incurred higher costs – including legal fees and court costs – than did non-represented claimants.

The All-Industry Research Advisory Council (1988) shows households that hired attorneys had longer settlement times for injury claims than those who did not. Households that reported large economic loss were more likely to have hired an attorney. Further, although 80 percent of households that did not hire lawyers were satisfied with the overall amount that they received from all benefit sources, only 58 percent of claimants who did hire attorneys were satisfied.

These studies do not support Nielson and Kleffner’s claim that lawyers provide no valuable function in the claims settlement process.

  • The studies ignore the fact that cases requiring legal representation are usually more complex than those that do not require representation. Individuals who choose not to hire lawyers usually do so because they have relatively simple cases. Nielson and Kleffner have the causal relationship reversed. It is not that lawyers “cause” cases to take longer to settle; it is that plaintiffs seek legal representation when they recognise that they have complex cases.
  • Households are not forced to use lawyers. The fact that many choose to do so indicates that they believe that lawyers provide a valuable service. Hiring a lawyer to assist in the pursuit of a damage claim is analogous to hiring a realtor to help in the sale of a property. Individuals have the option of selling their property privately. The fact that many people choose to hire realtors provides strong evidence that people perceive value in doing so – otherwise they would not do it. Similarly, purported “evidence” that claimants obtain little or no value from the hiring of lawyers must be set against the undeniable evidence that most claimants do hire lawyers.
  • Satisfaction and payout of benefits cannot be compared on a consistent basis. Such comparisons assume that the severity and complexity of injuries is the same. It also assumes that all people hire lawyers for the same reasons.

Nielson and Kleffner conclude that since attorney involvement in settling claims “results” in lower net settlement amounts and longer time to settlement, it would appear that reducing attorney involvement would be one way to increase satisfaction of claimants.

But there is no empirical evidence to show that reducing attorney involvement would increase satisfaction of claimants. On the contrary any restriction on such involvement would be expected to lead to more dissatisfaction as the claimant no longer has a choice or a place to turn for representation should he or she not agree with the claim offered by the insurer.

Increasing Proportion of Accidents Producing Injury Claims

According to Nielson and Kleffner, in Alberta the number of bodily injury claims has been rising much faster than property damage claims. During 1986-1999: the number of vehicles insured increased 24 percent, the number of bodily injury claims increased 157 percent, property damage claims frequency decreased from 4.94 to 3.04, and the number of property damage claims decreased 22 percent from 59,353 to 45,996. Claims cost for bodily injury losses (cost per insured vehicle) increased 200 percent while the consumer price index increased only 43 percent.

Nielson and Kleffner attribute the dramatic rise in bodily injury costs to a purported change in the claiming behaviour of motorists and passengers. They suggest that many of these claims are in fact not legitimate. However, the statistics that they report do not allow them to draw this conclusion.

  • The argument assumes implicitly that all drivers are identical and suffer exactly equivalent injuries in any accident. It ignores the fact that increased costs to treat injuries could be attributed to an increase in severity of injuries due to more crowded road conditions, increased number of passengers per vehicle, and/or the requirement to compensate for rising income losses.
  • That bodily injury claims costs increased more rapidly than the consumer price index does not provide any evidence of fraud or increased litigiousness. First, over the period investigated by Nielson and Kleffner (1986-1999) per capita medical costs rose by more than 75 percent in Canada (almost double the rate of inflation over that period). Second, wages and salaries also increased more rapidly than inflation, thereby increasing claims costs for lost earnings. Third, and most importantly, the Supreme Court rulings in the “trilogy” cases in 1978 led to a dramatic change in the way that damages were assessed in Canada. These changes allowed plaintiffs to obtain damages that much more closely reflected the losses they had incurred than had been possible previously. The result was that, over the 1980s, bodily injury damages rose while the lower courts absorbed and applied the Supreme Court’s new rules.
  • Bodily injuries can arise independently of property damage. While there might be fewer fender benders, the increase in bodily injury claims and costs may be attributed to an increased severity of automobile accidents and increased number of passengers per vehicle.
  • Furthermore, with improvements in the quality of automobile bodies, there may have been an increase in the number of accidents that do not cause significant property damage yet result in serious personal injuries (particularly to the neck and back).

Changes in Claims Behavior

Nielson and Kleffner cite two studies that purport to show that no-fault insurance reduces the propensity to exaggerate claims for personal injuries – studies by Cassidy et. al. (2000) and by Carroll et. al. (1995). Both of these studies are so seriously flawed as to be of no value.

Nielson and Kleffner identify the Cassidy study as the most important Canadian research examining the link between claiming behavior and treatment patterns. In this study, funded entirely by Saskatchewan Government Insurance, Cassidy et al examined 7462 whiplash injury claims filed in Saskatchewan in the six months before, and the twelve months after, that province converted from a tort liability to a no-fault system.

They claimed to have found that plaintiffs recovered from their injuries much more quickly under the no-fault system than under tort. The purported evidence for this finding was that insurance files for whiplash claims were “closed” much more quickly under no-fault than under tort. The implication drawn by Cassidy et. al. was that plaintiffs were more likely to exaggerate the extent of their injuries in a tort system, where parties are allowed to obtain compensation for “pain and suffering,” than in a no-fault system where such a claim is usually denied.

There are several flaws with this study:

  • It is clear that the primary reason the whiplash files closed more quickly under no-fault than under tort was that claimants were provided with a forum in which they could appeal the insurance company’s rulings in the latter but were denied that opportunity in the former. Under Saskatchewan’s no-fault automobile insurance system, decisions about the claimant’s treatment and compensation are made administratively, by the insurer. Under the previous tort system, the plaintiff had the opportunity to appeal the insurer’s decision to the courts, and often did. It was the removal of the freedom to appeal that resulted in claims being closed more quickly, not a sudden decrease in drivers’ willingness to defraud the insurer.
  • The study did not give conclusive evidence regarding whether people were physically better or worse off as a result of no-fault. All the research was able to show was that claims closed faster under no-fault than under the tort system.
  • The tort claims investigated by the authors were restricted to the period six months prior to the implementation of no-fault. But in the US it has been found that claims filings increase substantially in the six months to a year before no-fault is introduced as claimants expect to be dealt with more fairly in a tort system than under no-fault. As a result, claims experience in the six months prior to the introduction of no-fault cannot be assumed to be representative of all claims under tort.

The second paper cited by Nielson and Kleffner in support of their claim that drivers have been making “excessive” claims against their insurers is Carroll, Abrahamse, and Viana (1995). We have carefully reviewed this paper and conclude that it provides no support for Nielson and Kleffner’s claim.

First, many of the results in the Carroll paper are conditional on the assumption that general (non-pecuniary) damages are highly correlated with damages for economic loss. It is their assertion, for example, that if the loss of income resulting from a broken leg in one accident is twice as large as the loss resulting from the same injury in a second accident, the general damages (damages for “pain and suffering”) in the first will be approximately twice as large as in the second. The result, Carroll et. al. argue, is that individuals have a double incentive to exaggerate the extent of their economic losses.

Nielson and Kleffner imply that this incentive to exaggerate economic losses exists in Canada. It does not, for three reasons.

  • The Supreme Court of Canada has set an absolute limit on the size of general damages, of approximately $260,000. The lower courts have interpreted this limit to imply that general damages on “lesser” injuries (for example, a broken leg) must be proportional to those on the most serious injuries, like quadriplegia (that is, on those eligible for the maximum damages). Thus, general damages for a broken leg cannot exceed a relatively low amount, no matter how large the attendant economic damages might become.
  • General damages in Canada are determined by the physical nature of the injury, not by the level of economic damages that are consequent on the injury.
  • In cases of serious injury (the cases that Nielson and Kleffner argue constitute the bulk of dollar claims in Canada), claims for economic damages are subject to intense scrutiny by phalanxes of lawyers, economists, medical practitioners, vocational consultants, and numerous other expert witnesses in a process that is carefully monitored by both the courts and the insurance industry. The opportunities for exaggeration are severely constrained by both the professionalism of the participants and the adversarial nature of the process.

Second, Carroll et. al. argue that there will be fewer incentives to exaggerate economic damages in states with no-fault insurance if plaintiffs must meet a “verbal” threshold (i.e. must show that their injury is present on a list of eligible injuries) before they can sue under tort than if the plaintiffs must meet a “dollar” threshold (i.e. must show that economic damages exceed a pre-specified level). They conduct two tests of this hypothesis.

First, they calculate the ratio of “soft” injuries (those, such as soft tissue injuries, that are relatively easy to disguise) to “hard” injuries (those, such as broken bones, that are objectively verifiable) in each of the U. S. states. When they find that the two “verbal” threshold states – Michigan and New York – have among the lowest ratios, they “conclude” that their hypothesis has been confirmed. Plaintiffs in the “non-verbal” threshold states are exaggerating their “soft” claims.

This conclusion cannot be supported by the data. It is clear that the reason the ratio of soft to hard injury claims is low in New York and Michigan is that the verbal thresholds in those states exclude most soft injuries from the approved list. Plaintiffs suffering from non-approved injuries are denied the opportunity to make tort claims. Thus, the ratio of soft to hard injury claims is low in the verbal threshold states primarily because plaintiffs have been excluded by administrative fiat, not because claimants refrained from exaggerating the extent of their injuries in the latter.

Furthermore, the second test that is offered by Carroll et. al. is inconclusive. They argue that, because general damages (for “pain and suffering”) are correlated with pecuniary damages (for medical expenses and lost earnings), individuals have an incentive to exaggerate the level of their pecuniary damages. They predict, therefore, that the average level of damages will be higher in tort states than in no-fault states – particularly those no-fault states that require claimants to meet a verbal threshold before general damages can be awarded.

The evidence they provide, however, shows clearly that there is only a tenuous correlation between damages for soft injury claims and the nature of the legal system. Indeed, if the figure on page 18 of their report shows any correlation it is that average damages are higher in verbal threshold states than in tort states.

To conclude, the Carroll study, like the Cassidy study, provides no reliable evidence that injured parties are more likely to exaggerate their claims in a tort system than they are in a no-fault system.

References

All-Industry Research Advisory Council. (1988) Attorney Involvement in Auto Injury Claims, December, 1988. Oak Brook, IL.

Carroll, Stephen, Allan Abrahamse, and Mary Vaiana. (1995). The Costs of Excess Medical Claims for Automobile Personal Injuries. Santa Monica, CA: RAND, Institute for Civil Justice.

Carroll, Stephen J. and James S. Kakalik. (1991). “No-Fault Automobile Insurance: A Policy Perspective.” Santa Monica, CA: RAND, Institute for Civil Justice.

Cassidy, J. David, Linda Carroll, Pierre Cote, Mark Lemstra, Anita Berglund, and Ake Nygren. (2000). “Effect of Eliminating Compensation for Pain and Suffering on the Outcome of Insurance Claims for Whiplash Injuries,” New England Journal of Medicine, 342 (16), 1179-1186.

Cummins, J. David, and Mary Weiss. (1991). “Incentive Effects of No-Fault Automobile Insurance: Evidence from Insurance Claim Data,” in G. Dionne, (ed.) Contributions to Insurance Economics. Norwell, MA: Kluwer Academic Publishers, 445-470.

Cummins, J. David, Mary Weiss, and Richard Phillips. (1999). The Incentive Effects of No Fault Automobile Insurance. Wharton School, University of Pennsylvania. Working Paper 99-38.

Devlin, Rose Anne. (1991). “Liability Versus No-Fault Automobile Insurance Regimes: An Analysis of the Experience in Quebec,” in G. Dionne, (ed.) Contributions to Insurance Economics. Norwell, MA: Kluwer Academic Publishers, 499-520.

Devlin, Rose Anne. (1997). No-Fault Automobile Insurance and Accident Severity: Lessons Still to be Learned, Department of Economics, University of Ottawa. Working Paper 9707.

Foundation for Taxpayers and Consumer Rights. (1997). A Failed Experiment: Analysis and Evaluation of No-Fault Laws.

Insurance Bureau of Canada. (1991). Quarterly Industry Analysis Survey, Fourth Quarter.

National Association of Insurance Commissioners, Research Division. (1988-98). State Average Expenditures and Premiums for Personal Automobile Insurance.

Nielson, Norma and Anne E. Kleffner. (2001). “Recommended Reforms to Alberta’s Auto Insurance System”. Unpublished paper, April 23.

Sloan, Frank, Bridget Reilly, and Christoph Schenzler. (1994). “Tort Liability versus Other Approaches for Deterring Careless Driving,” International Review of Law and Economics 14, 53-71.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Angela Tu Weissenberger is principal of ATW Economics Group Inc. where she is a specialist in strategic market positioning and industry analysis with an emphasis on economics and finance. Prior to founding the ATW Economics Group, she led a team of analysts responsible for the risk assessment of energy companies at one of Canada’s largest financial institutions. Angela holds B.A. in Economics and an M.A. in Economics with a specialization in Law and Economics from the University of Calgary. Her graduate work focused on the deterrent effect of no-fault automobile insurance systems.

The Deduction for “Expenses Related to Earning Income” in Rewcastle

by Christopher Bruce & Derek Aldridge

This article was originally published in the Autumn 2001 issue of the Expert Witness.

The recent case of Rewcastle v. Sieben (9801 16002, Calgary, July 20) concerned an estate claim brought under the Survival of Actions Act (SAA). In his decision in that case, Justice Hutchinson introduced a new method for calculating the deduction for “expenses directly related to earning income.” In this article, we summarise Justice Hutchinson’s method and comment on its broader applicability.

The Decision

As is true in many fatality claims brought under the SAA, Bryana Rewcastle was a teenager when she was killed. Hence, when determining the value of her estate’s claim, Justice Hutchinson first recognised that her family status would have changed a number of times over her lifetime.

He found that from her teenaged years until her mid-twenties, she would have been single. Then she would probably have married and had children. Eventually, her children would have grown up and left home, leaving her, with her husband, a part of a two-person family.

Following a number of previous Court of Appeal decisions, Justice Hutchinson concluded that the percentage of Bryana’s income that would have been available to her would have been smaller, the larger was her family. For example, this issue was addressed in the October 2000 Alberta Court of Appeal decision in Duncan Estate v. Baddeley (2000 ABCA 277):

…Under the Harris approach, the deceased’s proportionate share of joint family expenses are included in personal living expenses. Duncan bore a one-fourth share of joint family expenses based on the trial judge’s finding that had Duncan lived, he would have had a wife and two children; had it been four children, only one-sixth of the shared family expenses would have been deducted. (Duncan [2000] at paragraph 22.)

In particular, Justice Hutchinson accepted evidence that 100 percent of her income would have been available to her when she was single, 50 percent when she was married but had no children, and 25.8 percent when she was married with two children. (The latter figure was not 25 percent as it was assumed that the children would not share in family expenditures on cigarettes and alcohol.)

He also accepted evidence that she would have been single for 6 years of her life (ages 22-27), would have been married with no children for 14 years (ages 28-30 and 51-62), and would have been married with two children for 20 years (ages 31-50). He found, therefore, that across those three stages of her life, an average of 45.4 percent of her income would have been available for expenditure on goods and services that would have benefited her.

But not all of that income would have been spent on “expenditures directly related to earning income.” Specifically, he accepted evidence that only 72.8 percent of family expenditures are spent on such items. [See Rewcastle, para. 171].

Hence, the living expenses deduction in her case was calculated to be 72.8 percent of 45.4 percent, or 33.05 percent. It is the latter figure that Justice Hutchinson deducted from the present value of Ms. Rewcastle’s lifetime after-tax income in order to obtain her estate claim.

We accept Justice Hutchinson’s general approach. However, we do question some of the specific numbers that he has employed.

Personal Expenditures

Justice Hutchinson concluded that a woman would have 100 percent of her own income available to her when she was single, 50 percent when she was married with no children, and 25.8 percent when she was married with two children.

Clearly, the 100 percent figure is correct.

We also accept that the 50 percent figure is correct. Following from Harris, the usual assumption is that the husband and wife each benefit personally from approximately 30 percent of family income and benefit equally from the remaining 40 percent. That is, total personal benefit is 30 percent plus half of 40 percent, or 50 percent.

The 25.8 percent figure is more problematic, however. The reason for this is that it is usually assumed that children consume a slightly lower percentage of family income than do adults. Thus, for example, assume (as is common) that the deceased parent’s personal expenditure would have amounted to 22 percent of family income and that expenditures common to the whole family would have amounted to 30 percent of family income (with the remaining 48 percent being divided among the other spouse and the two children).

In that case, the deceased would have benefited from 29.5 percent of the family’s income – 22 percent plus one-quarter of 30 percent.

This is a relatively minor point, however: if 29.5 percent is used instead of 25.8 percent in the Rewcastle case, the percentage of income available over Bryana’s lifetime would only have increased from 45.4 percent to 47.25 percent.

Expenditures Related to Earning Income

We have greater concern with Justice Hutchinson’s conclusion that 72.8 percent of income is devoted to items that are “related to earning income.” In particular, that figure was obtained by summing the percentages of income spent on: food, shelter, clothing, transportation, household furniture, household operation, health care, personal care, and education. (The omitted categories were: recreation, reading, tobacco and alcohol, miscellaneous, security, and gifts and contributions.)

But take just one of those categories, transportation, on which Ms. Rewcastle was assumed to spend 15.7 percent of her after-tax income. As that income was assumed to average approximately $35,000 (after tax), the assumption is that the entire $5,495 (= $35,000 x 0.157) she would spend annually on transportation would be “related to earning income.”

More specifically, as the Court of Appeal has ruled that expenditures on luxuries and on discretionary items are not to be included in the items assumed to be “related to earning income,” Justice Hutchinson’s decision requires that none of Ms. Rewcastle’s $5,495 annual transportation expenditures represented discretionary or luxury items. None, for example, would have provided her with discretionary “extras” on her automobiles or with luxury trips to sunny resorts.

Similarly, his decision requires that none of her $5,285 expenditures on food (15.1 percent of after-tax income), $7,735 on housing, and $1,785 on clothing were for discretionary or luxury items.

This assumption appears implausible to us. Surely some of her expenditures on clothing would have been for luxury goods, some of her expenditures on food would have been for restaurant meals, and part of her expenditures on housing might have paid for a main floor family room or a luxurious en suite bathroom.

If, reasonably, it is assumed that as little as 25 percent of her expenditures were for discretionary or luxury items, the percentage of her income devoted to items “related to earning income” would fall from 72.8 to 54.6, and the overall deduction for those expenditures would fall from 33.05 to 24.79 percent.

Conclusion

The Rewcastle decision has provided additional information concerning the method that is to be used to calculate losses in Survival of Actions cases. Nevertheless, some important questions, particularly those concerning the evaluation of discretionary and luxury items, remain unanswered. It is our understanding that the defendants in Rewcastle have sought leave to appeal. If they are successful, it is possible that the appellate court will resolve some of these questions.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

The Deduction of Accelerated Inheritance

by Christopher Bruce

This article was originally published in the Summer 2001 issue of the Expert Witness.

In Brooks v. Stefura, the Court of Appeal stated that “accelerated inheritances” should be deducted from each plaintiff’s dependency award. The Court did not, however, state clearly what it meant by “accelerated inheritances.” In this article, I offer a number of observations that may cast some light on this issue.

First, note that the “gain” in the present is to be reduced by the loss of the same amount in the future, at the deceased’s without-accident expected age of death. When the asset inherited “today” is physical in nature – for example, a house or piece of land – one must be careful to take into account the probability that the value of that asset would have increased significantly before the deceased’s natural death. The greater would this rate of increase have been, the lesser will the “gain” be from having inherited “early.”

For example, assume that a child inherits a house with a value of $100,000 (after payment of outstanding debts) today instead of at his mother’s natural date of death 20 years from now. If the rate of inflation of house prices is 3 percent per year, the house would have been worth $180,000 at the mother’s date of death. Assuming a rate of interest of 6 percent, it would be necessary to invest $56,300 today to generate $180,000 20 years from now. Thus, receiving $100,000 today instead of $180,000 20 years from now yields a gain of $43,700.

If, however, the rate of inflation of house prices is 4 percent, the house would have been worth $219,000 20 years from now. At a rate of interest of 6 percent, that amount could be replaced by investing $68,300 today. In that case, the receipt of $100,000 today, instead of $219,000 20 years from now, provides a benefit to the survivor of only $31,700.

More importantly, when the asset that is inherited today is financial in nature – for example, stocks or bonds – there is no gain at all from early inheritance. For example, assume that the asset is a secure bond that pays 8 percent per year for the next 10 years. Assume also that the deceased had a 10-year life expectancy. It is unlikely that the heirs could sell the bond and invest it in a secure financial instrument that pays more than 8 percent. Hence, they have gained nothing by receiving ownership of the bond today rather than 10 years hence.

Second, the deduction of “accelerated inheritances” results in the dependants of spendthrifts receiving larger awards than will the dependants of frugal individuals, everything else being equal. For example, assume that two individuals both earn $50,000 per year after taxes and both own houses valued at $200,000 that they purchased 10 years ago. Individual A has been devoting $20,000 per year to the payment of his mortgage, whereas individual B has been devoting only $10,000. As a result, at the time of his death A has paid off $140,000 of his mortgage while B has paid off only $60,000. The decision of the Court of Appeal would result in a much larger deduction from A’s estate than from B’s.

Third, in most cases, the most important inheritance will be the equity in the family home, left to the surviving spouse. It is not clear, however, that receipt of this equity “accelerates” the benefits enjoyed by the survivor. Assume, for example, that the home in question is worth $200,000. In most cases, the surviving spouse would have owned half of the home. Thus, it is the deceased’s half of the house that, presumably, the survivor has “gained.” But if the deceased had lived, the survivor would have had the benefit of that half of the house. It is difficult to see, therefore, what it is that the survivor has “gained” and, therefore, why there should be some deduction of the “accelerated’ inheritance.

The leading doctrine in damage assessment is restitutio in integrum, restoration of the plaintiff to his or her “original position.” The original position of the survivor is that he or she enjoyed use of 100 percent of the family home and some percent (usually, approximately 70 percent) of the other spouse’s (after-tax) income. For the Court to rule that some portion of the equity in the home should be deducted from the survivor’s claim against the dependency on income is tantamount to a ruling that the survivor should not be returned to his or her original position.

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In a companion article, Scott Beesley considers these same issues, and offers a different perspective.

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Evidence About “Customary Practice”

by Christopher Bruce

This article was originally published in the Spring 2001 issue of the Expert Witness.

The standard of care that is expected of a commercial enterprise is often determined by examining the “customary practice” followed by businesses in the defendant’s industry. Obstetricians are compared with other obstetricians; taxi drivers with other taxi drivers; and police departments with other police departments.

The determination of what constitutes the customary practice in an industry is usually left to the testimony of experts drawn from that industry.

In a recent University of Chicago Law School working paper, William Meadow (Associate Professor of Pediatrics) and Cass Sunstein (Professor of Jurisprudence) warn that such expert testimony is likely to be systematically biased. (“Statistics, Not Experts,” John M. Olin Law & Economics Working Paper No. 109, (2d Series) 2000.)

Their argument is not the traditional one – that experts will be reluctant to testify against their colleagues and, therefore, may understate the level of precautions “normally” taken. Rather, they argue that experts will systematically overstate the level of precautions that are normally taken, thereby raising the implicit standard against which defendants will be measured.

M & S base their argument on the oft-noted observation that “most normal people tend to be risk optimists, in the sense that they believe themselves to be relatively immune from risks that are faced by similarly situated others.” For example, they report that 90 percent of drivers believe themselves to be less likely than the average to be involved in a serious accident; and most heavy smokers believe they are not at increased risk of cancer or cardiovascular disease.

M & S report that physicians have been found to be particularly susceptible to this “optimism bias.” In one study, for example, 88 percent of doctors overestimated length of survival for seriously ill patients, by roughly a factor of three. In another, doctors made inaccurate predictions in 80 percent of cases, with overestimates in 63 percent. In a third study, physicians accurately predicted the survival time of cancer patients in only 10 to 30 percent of cases, and the rest of the time they overestimated survival by a factor of two to five.

M & S predict that this proclivity to optimism will affect doctors’ (and other experts’) ability to provide correct estimates of “customary practice.” In particular, they predict that this optimism will lead doctors to overestimate the ease with which they and their colleagues can recognise and treat symptoms and to underestimate the time required to react to medical emergencies.

To test this hypothesis, M & S asked a large number of emergency room physicians to estimate the average time that would elapse between the arrival of a child with bacterial meningitis in their emergency room to the start of antibiotic therapy for that child. They contrasted these estimates with statistics of actual times elapsed that they were able to obtain from their own study of two Chicago area medical centres and from two studies reported in the academic literature.

What they found was that the actual elapsed times were almost double the estimated times. Whereas the physicians’ average estimate was 65 minutes, the statistical studies revealed an actual average of 120 minutes.

Imagine now that a hospital has been sued in negligence for failing to treat a child within a “reasonable” time. If that hospital had treated the child within 110 minutes, it would actually have outperformed the average. But the average “expert” witness would have testified that most hospitals would have treated the child within 65 minutes. The behaviour of the defendant would be found to have fallen below the standard of “ordinary practice.”

(Of course, this does not necessarily mean that the defendant would be found negligent, as the court could conclude that the average hospital took less time to treat children than was required. However, this would be an unusual outcome.)

M & S further argue that this overestimation of the standard of ordinary practice will be common not only to physicians but also to experts within most other disciplines – from engineers to truck drivers – because they believe that most experts share doctors’ optimism. The result is that use of such experts will systematically bias the finding of negligence in favour of the plaintiff.

They conclude that:

  1. The courts should be very skeptical of testimony that attempts to identify ordinary practice based solely on the estimates of “expert practitioners.”
  2. Wherever possible, statistical evidence should be used in preference to practitioner evidence when determining ordinary practice.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Incorporating the Effect of Reduced Life Expectancy into Awards for Future Costs of Care

by David Strauss, Robert Shavelle, Christopher Pflaum, & Christopher Bruce

This article was originally published in the Winter 2000 issue of the Expert Witness.

1. Introduction

Some of the largest personal injury and medical malpractice actions are brought on behalf of plaintiffs with chronic disabilities such as cerebral palsy, spinal cord injury, and traumatic brain injury. Such plaintiffs require extensive care and assistance for the rest of their lives, and the cost of future care is often the largest part of the claim.

There are three components to the calculation the present value of the cost of lifetime care:

  1. A discount rate, specifying the interest rate at which it is assumed the lump sum award will be invested.
  2. The dollar cost of providing care during each year. The rate at which this amount is assumed to grow over time is usually, though not necessarily, lower than the rate of discount.
  3. A probability distribution specifying the probability that the plaintiff will live to each possible age in the future. In the calculation of the present value of future costs of care, the cost of care in each possible year in the future is multiplied by the probability that the individual will live to the age at which that cost is required. This is equivalent to reducing the required cost by the probability that the plaintiff will not live to a given age and, therefore, that the plaintiff will not require the assumed cost of care. [Note that this is analogous to multiplying the annual loss of income by the probability that the individual would have been working during that year, in order to capture the effect of the probability that the individual would have been unemployed.]

When the injury is not one that reduces life expectancy, the survival distribution that is used is that of the general population. The distribution can be obtained from an ordinary life table. (In Canada, this is the Life Tables 1990-1992.) Our interest here, however, is the case in which life expectancy is reduced, and it is no longer obvious how the annual survival probabilities should be chosen.

2. Alternative methods of calculating the impact of reduced life expectancy

Typically, medical opinion concerning reduced life expectancy is conveyed in the form of an average number of years of expected survival. For example, the medical experts might agree that the effect of the plaintiff’s injury is to reduce her life expectancy from 50 years to 30. The question we wish to consider here is how economists should incorporate this opinion in their calculation of the changes in annual probabilities of survival. A number of alternative techniques are commonly used.

Life certain – A very simple technique is to assume that the plaintiff will live exactly the number of years estimated by the medical experts and then die. For example, a 30 year-old who has a probability of 1.0 of living to each age between 30 and 50, and a probability of zero of living to any age beyond that, has a life expectancy of 20 years.

Although this technique is sometimes used to obtain to obtain very rough approximations, it is certain to produce estimates that exceed the true value by a substantial amount. The reason for this is that the life certain approach leaves all of the costs of care in the immediate future, (in this case, in next 20 years). In reality, the plaintiff has some probability of dying during the next 20 years and a corresponding probability of living more than 20 years. Hence, in reality, the costs of care should be reduced in the near future (to allow for the possibility that the plaintiff will die before needing them) and increased in the distant future (to allow for the possibility that the plaintiff will live beyond 20 years). But, as discounting reduces the present value of ‘distant’ costs more than it reduces the present value of ‘near’ costs, moving costs further into the future will reduce the discounted value of future costs.

Rating up – A simple method for obtaining a probability of survival to each possible age in the future is to find a “statistical person” who has the life expectancy of the injured plaintiff and to use that person’s probability distribution to represent that of the plaintiff. For example, consider a boy with severe cerebral palsy who has an agreed upon life expectancy of 20 additional years. The rating up method identifies the age in the general population at which the life expectancy is likewise 20 years.

According to the U.S. Decennial life tables, for example, this is 58 years. For each future age, the probability of survival for a 58 year old is substituted for that of the 5 year old. For example, the 5 year-old’s probability of living to age 15 is assumed to equal the probability that an average 58 year old would live to 68.

The attraction of this method is that it provides a probability distribution with the correct average, (here, 20 years). There is a problem, however: it is the wrong distribution. As the research literature makes clear, a child with a short life expectancy is subject to a fairly constant risk over the life span; he may well die in the next few years but he also has a reasonable chance of living another fifty. By contrast, the man of age 58 is at a relatively low risk over the next few years, but his risk increases steeply over the decades and he has almost no chance of surviving another 50 years.

Like the life certain method, the rating up method places too many of the costs of care in the immediate future, and too few in the distant future (relative to the “true” values). Hence, it systematically overestimates the present value of future costs of care.

Relative risk – In this approach, the economist multiplies all the age-specific mortality rates in a standard life table by a constant. The constant is chosen to result in the desired life expectancy, and is easily determined by trial and error. For example, if the annual probabilities that a male will die are multiplied by 47, the life expectancy of a 5 year-old will become 20 years. Although the argument is more complex than that made with respect to rating up, the relative risk approach also systematically overestimates the present value of future costs.

3. An Example

Table 1 shows lump sum awards for a 5 year-old boy with life expectancy 20 years who is to receive $100,000 for each remaining year of life. A discount rate of 4 percent is employed.

Table 1

The first row applies to a hypothetical child who will survive exactly 20 more years. This is the life certain distribution discussed above, and it leads to the largest award: $1,413,394. The second row is the result of rating up to age 58, which currently, perhaps, is the most widely used approach. The award of $1,296,174 is appreciably smaller than the $1,413,394 of row 2.

Row 3 uses the relative risk method. As indicated above, when the mortality rates of a standard life table are multiplied by 47, the life expectancy for a boy of age 5 years becomes 20 years. This is the multiplier that has been used. The resulting award of $1,297,290 is very similar to that obtained from rating up. Finally, row 4 gives the award when the correct life table, based on the latest evidence concerning cerebral palsy, is used. Use of the correct probability distribution leads to an award of $1,147,979.

In this example, both rating up and the relative risk method lead to awards that are too high by 13 percent, or approximately $150,000. And the life certain method leads to an award that is too high by almost 25 percent.

4. Comparison of the methods

The size of the discrepancy between the approximate methods and the correct survival distribution depends on several factors, of which the most important are the cost schedule, the discount rate, and the plaintiff’s life expectancy. Discrepancies will tend to increase as the rate of growth of costs decreases, as the discount rate increases, and as post-injury life expectancy falls.

Tables 2 and 3 show the percentage overestimation for various discount rates with the rating up and relative risk methods, respectively. In addition to the case of a five year old with cerebral palsy (Tables 2a and 3a), we also consider that of a 25 year-old with traumatic brain injury and a life expectancy of 20 years (Tables 2b, 3b). As expected, the amount of overestimation decreases as the net discount rate (the discount rate minus the rate of growth of costs of care) decreases, and is negative when the net rate is negative.

Table 2

Table 3

5. Conclusion

To calculate the present value of the lifetime care of a disabled person we need more than a life expectancy – the whole life table is needed. We have seen that rating up and other approximate methods can lead to substantially different present values from the values derived from the correct life table. In the common case of positive net discount rates, the approximate methods systematically overestimate the correct values. These overestimates can often amount to more than $100,000. This is an issue that has received far less attention from the courts than it deserves.

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David Strauss, Ph.D., FASA, and Robert Shavelle, Ph.D., MBA, are the principals in Strauss & Shavelle, a San Francisco firm that specialises in calculation of life expectancy.

Christopher Pflaum, Ph.D., owns Spectrum Economics, an Overland Park, Kansas firm specialising in the calculation of personal injury damages.

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

What is Econometrics?

by Kelly Rathje & Christopher Bruce

This article was originally published in the Winter 2000 issue of the Expert Witness.

Commonly, economic experts will testify that a particular characteristic of the plaintiff, such as his years of education or his marital status, is “correlated” with one of the factors that is of interest to the court, such as future income or retirement age. The branch of economics that seeks to determine whether such correlations exist is called econometrics. In this article, we explain briefly how econometric techniques work.

Assume that we are interested in determining whether the annual incomes that individuals earn are correlated with, or determined by, years of education. Assume also that 70 individuals have been observed and that for each individual, we know their number of years of education and annual income.

We have plotted the observations for these individuals in Figure 1. For example, individual A has 15 years of education and an annual income of $45,000.

Figure 1

When income levels are plotted against years of education, one would expect that the observations would be scattered, as seen in Figure 1. What the econometrician wishes to do is determine whether these scattered points form a “pattern.” One simple pattern that is often tested is that of a straight line. In this case, the formula for a straight line is:

I = a + b1(E)

where I is income; a is a constant; b1 measures the amount that education influences income; and E is years of education.

What the econometrician tries to do is to find the line which minimises the distances between the observations and the points on that line. The straight line which appears to meet this criterion with respect to the observations in Figure 1 has been drawn there. The formula for this line is

I = 6,850 + 2,000(E) (1)

This formula says that if the individual has 12 years of education, his income is predicted to be $30,850.

I = 6,850 + 2,000(12) = 30,850

It can be seen from Figure 1 that, in general, the observations lie fairly close to the line. For this reason, we would conclude that the hypothesis that education affects income is supported. Furthermore, because the “sign” on the 2,000 component of the equation is positive, we would also conclude that education has a positive effect on income. (In this case, each extra year of education appears to lead to 2,000 extra dollars of annual income.)

Equation (1), which investigates the effect which only one variable has on another, is not typical of the equations that are normally of interest to economists. Typically, for example, we would assume that there is a large number of factors, in addition to education, that will affect income. In that case, econometricians extend their equations to include numerous variables.

For example, suppose the economist has additional information about the age of each individual in the data set. This variable can also be added to the equation to help “explain” income. The equation would become:

I = a +b1(E) + b2(A),

where A is “age.” The resulting estimated equation might be something like:

I = 5,000 + 1,900(E) + 200(A) (2)

This model now indicates that for every extra year of education an individual has, they will earn an extra $1,900, on average, and for each additional year in age, there is an increase of $200. In other words, if an individual has a high school diploma, and is 34 years old, then the equation indicates on average, they will earn $34,600 (= 5,000 + [1,900 x 12] + [200 x 34]). Similarly, if an individual holds a bachelor’s degree (16 years of education), and is 34 years old, then the equation indicates that, on average, they will earn $42,200 (= 5,000 + [1,900 x 16] + [200 x 34]).

The variables used as examples to this point – income, education, and age – all share the characteristic that they can easily be measured numerically. Other variables which might influence the wage rate are less easily converted to numerical equivalents, however. Assume, for example, that our hypothesis was that incomes were higher in rural areas than in cities, or that men were paid higher incomes than women, all else being equal.

As econometric analysis is a statistical technique, it requires that the economist enter all of his or her information as numbers. The way that econometricians deal with this problem is to construct what are called “dummy variables.”

In this procedure, one of the observations is arbitrarily chosen to be the “reference variable” and it is given the value of 0 whenever it appears. The other observation is then given the value of 1. For example, if “female” was the reference category, then the dummy variable would be given the value 0 whenever the observed individual was female and would be given the value 1 whenever the individual was male.

Assume that this has been done and equation (2) has been re-estimated with a male/female dummy variable included. The new equation might look like:

I = 3,000 + 1,900(E) + 200(A) + 4,000(M) (3)

where M is 1 if the individual is male and 0 if she is female. The interpretation that is given to the value that appears in front of M in this equation is that income is $4,000 higher when the worker is a male than when the worker is female.

Alternatively, because the dummy variable takes on the value 0 when the worker is female, the relevant regression equation for females is simply equation (3) excluding the dummy variable:

I(female) = 3,000 + 1,900(E) + 200(A)

And because the dummy variable takes on the value 1 when the worker is male, the relevant equation for males becomes:

I(male) = 3,000 + 1,900(E) + 200(A) + 4,000(1)

= 7,000 + 1,900(E) + 200(A)

The income model is one example of how econometrics is used, and how it is useful to determine trends and relationships between variables. Other uses may include forecasting prices, inflation rates, or interest rates. Econometrics provides the methodology to economists to make quantitative predications using statistical data.

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Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Ontario’s Mandated Discount Rate – Rule 53.09(1)

by Christopher Bruce

This article was originally published in the Autumn 2000 issue of the Expert Witness.

Recently, Ontario changed its Rules of Court concerning selection of the discount rate. Previously, Rule 53.09(1) required that the courts use a real interest rate of 2.5 percent when discounting future earnings.

The new rule divides the future into two periods – the next 15 years, and beyond 15 years. In the first period, Rule 53.09(1) requires that the courts use the rate observed on real return bonds for the 12 months ending August of the year preceding the date of calculation, less one percent, rounded to the nearest one quarter percent.

For example, as the average rate for the 12 months ending August 2000 was 3.87 percent, all calculations performed in 2001 must use a discount rate of 2.75 percent – that is, 3.87 minus 1.00 rounded to the nearest 0.25.

In the second period, for losses beyond 15 years into the future, 2.5 percent is still to be used.

The wording of Rule 53.09(1) clearly states that the figure obtained by deducting 1 percent from the rate on real return bonds is to represent the discount rate. The committee that recommended the changes to Rule 53.09(1), (the Subcommittee of the Civil Rules Committee on the Discount Rate and Other Matters), deliberately selected this wording.

It was their view that because real return bonds are not traded very frequently and because they receive “unfavourable tax treatment,” “economic and risk factors” biased the reported rate upwards. That is, it was felt that a risk free investment would have a lower rate of return – by 1 percent – than that reported for real return bonds.

I do not agree with the committee’s conclusions on this matter. The committee seems to have been confused about the rationale for using the rate on real return bonds. As was indicated in the article “Selecting the Discount Rate” in this issue, the proposal is not that plaintiffs purchase real return bonds. Rather, the rate of return on those bonds is to be used as an objective indicator of the forecast that sophisticated investors are making of the real rate of interest.

This is not to say that some discount should not be made for the fact that so few of these bonds are bought and sold. But a discount of 1 percent seems well out of line. This was seen clearly in the last section of “Selecting the Discount Rate,” in which recent statistics concerning real interest rates in Canada were summarised.

There it was reported that real rates of interest on risk-free Government of Canada bonds have been very similar to the rates reported on real return bonds in the last three years. It appears that the committee was reluctant to choose an interest rate that would differ significantly from the previous mandated rate of 2.5 percent.

Interestingly, the Ontario Court of Appeal, in Martin v. Listowel Memorial Hospital (Docket C31222, November 1, 2000), concluded that the current real rate of interest is approximately 4 percent, not the 2.75 percent implied by its own Rules of Court. Indeed, in the Martin decision, the Court seemed to signal that it was willing to accept evidence concerning the discount rate on a case-by-case basis – hardly a ringing endorsement of the newly-established Rule 53.09.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Selecting the Discount Rate

by Christopher Bruce, Derek Aldridge, Scott Beesley, & Kelly Rathje

This article was originally published in the Autumn 2000 issue of the Expert Witness.

One of the most important determinants of the lump sum award for future losses is the discount rate, or real rate of interest. Simply put, this is the rate of interest at which the plaintiff is assumed to invest the award, after the effects of price inflation have been removed.

For example, assume that the court has found that if the plaintiff was to incur a loss today, the value of that loss would be $10,000. But, because the loss will occur one year from now, and the rate of inflation between today and one year from now will be 2 percent, the loss will actually be $10,200.

The court must determine how much the plaintiff will have to invest today in order to ensure that he or she will have $10,200 available one year from now. The discount rate is the interest rate that is used to make this calculation. The purpose of this article is to determine the current value of the discount rate.

We proceed in four steps. First, we distinguish between “nominal” interest rates and “real” interest rates and explain why the latter are generally used in preference to the former. Second, we review a number of alternative methods of measuring the interest rate. Third, we review a number of methods of estimating the expected rate of inflation. Finally, we report the values of these alternative measures for the years 1997-2000 and we conclude with a recommendation concerning the appropriate value to be used today.

Real versus nominal interest rates

There are two methods of calculating the present value of a future loss. The first is to “discount” the loss by the “nominal” rate of interest – that is, by the rate of interest that is observed at financial institutions. The second is to remove the inflationary estimate from the projected loss, to obtain what is called a “real” loss, and then discount that loss by the “real” rate of interest – that is, the nominal rate after the rate of inflation has been removed. The two methods yield identical results.

For example, assume that the nominal rate of interest is 6 percent. The first method of determining the award is to divide $10,200 by 1.06, (that is, by 1 plus the interest rate). That number is found to be $9,623. It can easily be confirmed that if 6 percent of $9,623 is added to $9,623 one obtains $10,200. That is, if the plaintiff was to invest an award of $9,623 at 6 percent, he or she would have $10,200 at the end of one year.

In the second method, one first “removes” inflation, here 2 percent, from both the future loss and the nominal interest rate. In both cases, this is done by dividing by 1.02, (that is, by 1 plus the inflation rate). Thus, as intuition would suggest, the real level of damages is found to be $10,200/1.02 = $10,000. The real interest rate is found to be 1.06/1.02 = 1.0392, or 3.92 percent. (Note that, in the same way that 1.06 is 1 plus the nominal interest rate, 1.0392 is 1 plus the real interest rate.) When $10,000 is divided by 1 plus the real interest rate, 1.0392, one obtains $9,623, exactly the same answer that was obtained using the nominal method.

Economists generally prefer to use the real loss/real interest rate approach when calculating lump sum awards for future losses. The primary reason for this is that real interest rates tend to be much more stable and, therefore, much more easily predicted, than either inflation rates or nominal interest rates.

Alternative measures of the interest rate

Because plaintiffs often have to rely on the investment of their awards to provide a significant portion of their future incomes, it is important that they place their awards in relatively risk-free investments. For this reason, the discount rate is usually based on the rate of return on either long-term government bonds or secure private sector investments. Once a nominal rate has been determined for one of these investments, it is then necessary to determine an expected rate of inflation (over the duration of the investment) in order to calculate the real rate of return.

In this section, we will consider three types of secure investments. In the following section, we will discuss three methods of estimating the expected inflation rate.

Real return bonds The first investment vehicle is Government of Canada real return bonds. These are long-term, secure bonds whose rate of return is denominated in terms of a real interest rate. (That is, the government guarantees that the investor will receive a specified (real) interest rate plus the actual rate of inflation.) There are a number of advantages to using the rate of return on these bonds.

First, when that rate is used, it is not necessary to make a separate projection of the rate of inflation.

Second, these bonds are guaranteed by the government of Canada.

Third, the estimate of the real rate of interest that is obtained by observing the prices at which these bonds are traded in the financial markets provides an objective measure of the real rate of interest that is forecast by sophisticated investors. Note, we are not suggesting that plaintiffs should, or will, invest their awards in real return bonds. Rather, we are arguing that the observed returns on these bonds provides an excellent, objective measure of the expected real rate of return – as these bonds are purchased primarily by individuals who are close observers of money markets and who have a great deal of money at stake when selecting their investments. (Generally, it is pension fund administrators who purchase real return bonds.)

Recently, Ontario revised its Rules of Court concerning the selection of the discount rate. Whereas the previous rule required that the courts use a fixed rate of 2.5 percent, the new rule bases the rate on current observations of the interest rate on real return bonds. For further analysis of Ontario’s new rule, see the accompanying article “Ontario’s Mandated Discount Rate – Rule 53.09(1).”

Guaranteed investment certificates A second approach to the determination of the real discount rate is to identify a measure of the rate of return on a “safe portfolio” of investments (i.e. the kind of portfolio in which a plaintiff could be expected to invest) and to deduct from that rate the expected rate of inflation. We have long recommended that the rate of return on five year guaranteed investment certificates, GICs, be used for this purpose.

Again, as we commented with respect to real return bonds, we are not suggesting that the plaintiff should use his or her award to purchase GICs. Rather, as the types of investments contained in GICs are similar to those that one would expect a prudent investor to purchase, the rate of return on GICs provides an objective measure of the rate of return that plaintiffs can expect to obtain. (Furthermore, as the quoted rate on GICs is net of investment management fees, there is no need to make a separate calculation of the management fee.)

Long-term Government of Canada bonds The rate of return on long-term government bonds can be used as a benchmark against which to measure the returns on other investments. As these bonds are widely held by private citizens (unlike real return bonds) and as they are among the most secure investments available, it would be expected that plaintiffs would never earn a nominal rate of return less than that obtainable from Government of Canada bonds. (If the plaintiff’s investments began to obtain a lower rate of return, the plaintiff could always, easily, transfer his or her investments to government bonds.) Hence, any suggested discount rate must pass the test that it is not lower than the rate obtainable on government bonds. Conversely, we would suggest that the discount rate used should also not significantly exceed the government bond rate, as that would imply that plaintiffs should place their awards in unacceptably risky investments.

Estimating the rate of inflation

The real rate of interest is calculated by removing the effects of price inflation from the nominal rate of interest. As the interest rate is to apply to investments that will continue for many years into the future, the relevant rate of inflation is the average rate that is expected to apply over that future. We will discuss three methods of forecasting this rate.

Current rate of inflation One simple method is to assume that the current rate of inflation will continue into the future. Use of this rate is based on the observation that investors appear to adjust their expectations of the future when current conditions change. Often it is assumed that this shift of expectations occurs with a short “lag,” of six months to two years. But, in periods in which the rate of inflation is not changing quickly, only small errors will be produced if the current rate is used.

Core rate of inflation In Canada, the reported rate of inflation is measured as the change in the price level of a representative “basket” of goods over a 12 month period. For example, the rate of inflation reported for January 2001 will be the percentage change in prices between January 2000 and January 2001.

What this means is that if there is a large, one-time increase in prices in January 2000, measured inflation will be relatively high in each month from January 2000 to December 2000 and then will fall significantly in subsequent months. The reason for this is that the increased price level produced by the January 2000 price increase will continue to be in effect in every future month. Hence, in every month between January 2000 and December 2000, prices will be higher than in the corresponding month a year earlier. Inflation in those months will be correspondingly high.

For example, assume that the CPI had been 100 in every month during 1999, had risen to 110 in January 2000, and stayed at that level for the rest of the year. Then, in every month during 2000 the CPI would be 110, in comparison with 100 in the same month the year before. Hence, in every month in 2000 the rate of inflation would be reported as 10 percent – even though there had not been a price increase since January.

But, when calculating the January 2001 inflation rate, the price level for that month will be compared to a price level (January 2000) that already contains the one-time increase of January 2000. Hence, the measured rate of inflation in January 2001 (i.e. between January 2000 and January 2001) will drop back to the long-run maintainable rate.

In our example, if the CPI remains at 110 in January 2001, inflation between January 2000 and January 2001 will be 0 percent. The one time increase in January 2000 will have had only a temporary impact on the rate of inflation.

What this observation implies is that if we wish to use the current rate of inflation to forecast the long-run rate of inflation, we must first remove the effect of one-time price increases. The Bank of Canada attempts to provide such a measure of long-run price inflation with what it calls its core rate of inflation. In particular, this measure removes movements in the costs of food and energy and movements in prices due to the effects of indirect taxes.

For example, the core rate of inflation would not include the effects of the doubling of oil prices during 2000. Why? Because, although a doubling of prices from $15 a barrel to $30 (and higher) was not completely unexpected, very few observers expect to see prices rise much higher. Hence, even if prices remain at their current level, within 12 months of the initial increases, inflation (the change in the level of prices) will fall. (The increase in oil prices is an example of the one-time increase we discussed above.)

And, of course, if prices should fall back to their pre-2000 levels, short-term inflation will fall even more – perhaps into negative numbers – for the next 12 months. But no one will expect those low levels of inflation to continue any more than they expect the current high levels to continue.

The implication, then, is that the core rate of inflation may be a better indicator of the long-run, expected rate of inflation than is the measure that is usually reported in the press. For this reason, in the tables below, we report both the core rate and the published rate.

The Bank of Canada’s target rate For the last decade, the Bank of Canada’s monetary policy has been directed at producing a rate of inflation of 2 percent (plus or minus 1 percent). As anyone who can remember the 1970s and 1980s can attest, the Bank has been singularly successful in reaching this goal.

Indeed, it has been so successful, that we believe that it can be argued that most investors have come to believe that the long-run rate of inflation will be (approximately) 2 percent. (The Bank itself reports that most financial analysts are predicting inflation rates of approximately 2 percent. See Bank of Canada Monetary Policy Report, November 2000, p. 32.) For this reason, when determining the real interest rate, in the tables below, we report calculations employing an inflation rate of 2 percent.

The data

We present two tables. Table 1 reports quarterly values of the two nominal interest rates – 10-year Government of Canada bonds and GICs – and two of the measures of expected inflation – the standard version and core inflation – for 1997, 1998, 1999, and the first three quarters of 2000. (We do not report the Bank of Canada target rate of inflation, as it did not change over this period.)

Table 1

Table 2 reports the real rates of interest obtained, first, from the real return bonds and, second, from adjusting the two nominal interest rates by each of the three measures of expected inflation. This produces seven measures of the real rate of interest.

Table 2

What these figures suggest is, first, that the interest rate on real return bonds has been remarkably constant over the last three and a half years, rarely deviating very far from the 4.0 to 4.1 percent range until 2000, when it fell to approximately 3.7 percent.

Second, it is seen that the real rate of interest on 10-year government bonds has also fluctuated around 4.0 percent, but with far larger deviations than was seen with respect to the rate on real return bonds. Some of the wider of these deviations can easily be explained, however.

Note, for example, that the low real rates produced in 1998 and 1999 when the 2 percent inflation factor is used may have resulted because a long period of below-2 percent inflation had caused financial markets to believe that the Bank had lowered its target rate. (The conventional measure of inflation exceeded 2.0 percent only once between the first quarter of 1996 and the third quarter of 1999, when it was reported to be 2.1 percent in the first quarter of 1997.) If the markets had come to expect inflation rates of 1.5 percent in 1998 and 1999, for example, most of the real rates in those years would have been close to 4.0 percent.

The relatively high rates found in 2000 when long-run bond rates are discounted by core inflation, and the relatively low rates found in that year when they are discounted by the standard measure of inflation, could both be “explained” if it was found that financial markets had begun to accept the Bank of Canada’s statement that it was targeting a long-run inflation rate of 2 percent.

The consistently low rates found on GICs, however, are disconcerting. Over the entire period reported in Table 2, and for a number of years prior to that, the rates of return on GICs were significantly lower than those on government bonds. This suggests that plaintiffs would be extremely unwise to invest in GICs for the foreseeable future.

We conclude, therefore, that current estimates of the discount rate should be based on the rates observed on real return bonds and on long-term Government of Canada bonds. Arguably, these rates fluctuated around 4.0 percent for most of the last four years. They have, however, fallen slightly during 2000.

This raises the question of whether 2000 is an aberration, or whether the recent decline in real rates is the beginning of a long-term trend. Some evidence that the decline is expected to be short-lived comes from the Alberta government’s Budget 2000 documents. There, it is reported that nine respected forecasting agencies predicted an average interest rate on Government of Canada 10-year bonds of approximately 6.21 percent (over the years 2000-2003). As it is unlikely that those agencies would have forecast an inflation rate in excess of 2 percent, implicitly they have forecast a real rate of interest of approximately 4.1 percent.

In this light, we believe that a rate of 4.0 percent is the best, current estimate of long-run real interest rates. However, Economica will be monitoring movements in the interest rates on real return and 10-year Government bonds closely. If bond rates do not rise relative to the rate of inflation in the near future, we will be revising our real rate of interest forecast downward.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Scott Beesley is a consultant with Economica and has a Master of Arts degree (in economics) from the University of British Columbia.

Kelly Rathje is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Calgary.

Combining Occupational Options

by Christopher Bruce

This article was originally published in the Summer 2000 issue of the Expert Witness.

In many cases it is not clear at the time of trial what occupation the plaintiff would have entered had he or she not been injured, or what occupation he/she will now enter. In these cases, it is common for the vocational expert to offer a menu of possible occupations that are consistent with the plaintiff’s observed interests and aptitudes.

An issue that is crucial to the correct evaluation of damages in such cases, but which rarely receives the attention it deserves is: How should the incomes from the various occupations be “weighted” to determine an average, expected income for the plaintiff?

For example, assume that the vocational expert has concluded that, with appropriate upgrading, the plaintiff has the aptitude and skills to enter any one of three occupations – A, B, or C. Assume also that the following information is available about these occupations:

Annual incomes are:

A – $20,000
B – $25,000
C – $30,000

The number of employed workers in these occupations is:

A – 5,000
B – 1,000
C – 100

The unemployment rates in these occupations are:

A – 20%
B – 8%
C – 2%

The question is, how should the plaintiff’s expected income be calculated? I can think of four methods, each of which can easily be defended.

Simple Average

If the court has been provided with no information concerning which of these occupations the plaintiff will enter, it can be argued that, ex ante, there is an equal probability that he will enter each of them. Hence, each income should be weighted equally, producing an average of

($20,000 + $25,000 + $30,000)/3 = $25,000

Weight by Employment Opportunities

If it is assumed that the plaintiff will apply at random for jobs advertised in the newspaper, it is more likely that he will randomly “select” occupation A, with 5,000 jobs, than occupation B, with 1,000.

Alternatively, when the individual’s preferences are unknown, it can be argued that he is most likely to enter the occupations that other people have been observed to enter. Thus, as “most” individuals choose occupation A, it can be argued that it is more likely that the plaintiff will choose A than any other, all else being equal.

Recognising that there are 6,100 jobs in total, if income is weighted by employment opportunities, the average proves to be

[(5,000 x $20,000) + (1,000 x $25,000) + (100 x $30,000)]/6,100 = $20,984

Weight by Supply and Demand (Unemployment Rate)

If it is assumed that the plaintiff is more likely to be successful applying for jobs in which there are few applicants relative to the number of positions available, he is more likely to obtain a job at the occupations with the lowest unemployment rates. One method of allowing for this possibility is to weight the annual incomes by the inverse of their respective unemployment rates (that is by 1 minus the unemployment rate). These values are 80% for A, 92% for B, and 98% for C, with an average of 90%. Thus, relative to the average, the plaintiff is assumed to have a 0.889 (80/90) probability of finding a job at A, a 1.022 (92/90) probability of finding a job at B, and a 1.089 (98/90) probability of finding a job at C. In this case, the weighted average of the incomes in A, B, and C proves to be

(0.889 x $20,000 + 1.022 x $25,000 + 1.089 x $30,000)/3 = $25,333

Weight by Income

If it is assumed that the plaintiff is most likely to apply to the occupation with the highest income, the weightings change again. For example, if the probability that the individual will apply to each occupation is strictly proportional to the income earned in that occupation, the probability that he will apply to A is 80 percent of the probability that he will apply to B; and the probability that he will apply to C is 120 percent of the probability that he will apply to B. In this situation, the weighted average income will be

[(0.8 x $20,000) + (1.0 x $25,000) + (1.2 x $30,000)]/3 = $25,667

In the table below, I provide an example of these calculations drawn from a case in which Economica was involved recently. There it is seen that the vocational expert recommended eight possible occupations for the plaintiff. The average incomes for these occupations vary from $36,005 to $40,615, a difference of $4,610 per year, depending on which of the four averaging techniques is applied. If we assume that this individual was 25 years old at the time of the trial, an annual difference of $4,610 will alter the lifetime loss by approximately $100,000.

Clearly, it could prove crucial to determine which method is most appropriate. The first step is to speak to the vocational expert. Only if that expert indicated that the plaintiff was equally likely to enter each of the specified occupations would I consider it appropriate to employ the simple average method. If the expert has no opinion, my preference would be to weight the occupational incomes either by unemployment rate (to reflect supply and demand) or by numbers of employees (to reflect the likelihood that a plaintiff of known characteristics will choose a particular occupation). Weighting by income would only seem to be reasonable if the plaintiff was known to be particularly strongly motivated by financial considerations.

Table 1

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Impact of Disability on Earnings: Results of the Health and Activity Limitation Survey

by Christopher Bruce, Derek Aldridge, & Kris Aksomitis

This article was originally published in the Spring 2000 issue of the Expert Witness.

The 1991 Census of Canada contained two questions that asked whether respondents considered themselves to be “disabled.” Using the answers to this question (and the answers to a second, preliminary survey), Statistics Canada was able to create a file of approximately 34,000 individuals that it considered to be disabled. These individuals were then asked to complete a lengthy, detailed questionnaire, known as the Health and Activity Limitation Survey, or HALS. Another (approximately) 100,000 non-disabled individuals were asked to complete a less detailed questionnaire.

As the HALS questions concerned factors such as health, income, and education, it held great promise for use in personal injury litigation. Indeed, it is possibly the most extensive and reliable study of the disabled that has ever been conducted (not just in Canada, but worldwide). And one does see allusions to HALS data in many experts’ reports. But, for various statistical reasons, the data that have been released by Statistics Canada have proven to be less valuable than might have been hoped. As a result, to those of us working in the field of damage assessment, HALS has been a great disappointment.

Economica recently obtained a copy of the answers provided by each of the respondents to the HALS survey. From these data we have extracted a number of statistics that we believe will be of interest to the personal injury litigation community. Although we cannot hope to resolve all of the problems previously associated with HALS data in this short article, it is our expectation that the data presented here will, nevertheless, be of value.

Earnings

We have obtained earnings data for both males and females, divided into four age groups, four education levels, and four levels of severity of disability; that is, for 128 categories in total. (128 = 2 x 4 x 4 x 4). For each of these 128 categories we calculate three figures:

  • The average earnings of individuals in the category who had at least some earned income, as a percentage of the average earnings of non-disabled individuals in that age/sex/education category who had some earned income.
  • The percentage of individuals in the category who had some earned income.
  • The average earnings of all individuals in the category, as a percentage of the earnings of all non-disabled individuals in that age/sex/education category. (This category differs from the first because it includes individuals who reported no earnings.)

We present these data in Tables 1a & 1b (pages 5 & 6). Figures are shown for each of the four education levels: less than high school, high school, college or trade certificate, and university. As one would have expected, in each category earnings rise as one moves from non-disabled through mildly, moderately, and severely disabled. (We define “mild,” “moderate,” and “severe” disability in an Appendix to this article, thus allowing readers to determine to which of those categories individual plaintiffs belong.)

In virtually all categories, it is seen that the predicted effect that disability will have on earnings is lower if it is known that the individual will be working than if it is not known whether he or she will be able to work. That is, the earnings of the disabled are a higher percentage of the earnings of the non-disabled among the working population than they are among the total population. This is because a higher percentage of the disabled than the non-disabled earn no income.

For example, among males aged 35-44 with a high school education, those with a “moderate” disability earned 68 percent as much as the non-disabled if they earned anything at all. But 38 percent of the moderately disabled individuals in this age/sex/education group reported that they had no earnings, whereas only 6 percent of the non-disabled reported that they had no earnings. Thus, inclusion of those with zero earnings in the earnings figures had a much greater impact on the average earnings of the disabled group than similar inclusion had on the average earnings of the non-disabled. The result is that the earnings of all moderately disabled individuals in this group were only 45 percent of those of all non-disabled individuals.

Charts 1a & 1b (pages 7 & 8) offer a graphical depiction of the data shown in the tables – and allow the reader to more easily observe the overall trend implied by the data.

Education

The earnings data reported in Tables 1a & 1b may underreport the effect of disability on earnings. The reason for this is that the disabled have lower education levels than do the non-disabled. If these lower levels result from the disability, then disability will have two effects: reducing earnings at each education level (Tables 1a & 1b) and reducing education levels.

In Table 2 (page 9), we report the distribution of education levels among the four categories of disability. It is seen in that Table that there is a higher percentage of university graduates among the non-disabled than among the disabled in every category; and a lower percentage of individuals who have not completed high school among the non-disabled than among the disabled in most categories. An interesting result is that mildly disabled males are much more likely than non-disabled males to have a college education or trade certificate. (However, this could occur if individuals with this level of education had a high probability of incurring injuries that caused mild disabilities.)

Conclusion

The tables and charts presented in this article suggest that the incomes of the disabled are lower than those of the non-disabled for at least three reasons: the disabled earn less when they work, even if they have the same levels of education as the non-disabled; the disabled are less likely to earn any income than the non-disabled; and the disabled have lower levels of education than do the non-disabled.

However, although the data presented here may be of some interest to personal injury litigants, the level of aggregation is so great that it seems unlikely that these data will be able to provide more than background information to the litigation process.

Appendix: Determination of the Degree of Disability

The purpose of this Appendix is to allow readers to determine whether Statistics Canada would classify a particular plaintiff’s disabilities as “mild,” “moderate,” or “severe.”

Statistics Canada asked 25 questions (see below), grouped into four categories. In the first category, the respondent was allocated a “score” of 0 if he or she answered “no,” a 1 if he/she answered “yes, but able,” and a 2 if he/she answered “yes, unable.” For example, the individual was allocated a 1 if he/she had difficulty hearing what was said in a conversation with one other person; and a 2 if he/she was unable to hear what was being said in such a conversation.

In the second category, the individuals were allocated a score of 1 if they answered “yes” to the question. (For example, “do you have difficulty with your ability to remember?”)

In the third category, individuals were shown a list of activities. If they were limited in their ability to engage in one of the activities they were allocated a score of 1; if they were limited in more than one of the activities they were allocated a score of 2.

Finally, individuals who had been diagnosed as legally blind received a score of 2.

The scores for all 25 questions were summed and individuals were allocated to the relevant levels of disability on the basis of their total scores. The scales used were:

 

LEVEL RANGE
Mild 1-4
Moderate 5-10
Severe 11-43

 

It will be apparent that these are very imprecise categorisations. For example, using Statistics Canada’s scale, both an individual who was legally blind and an individual with a weak back would be categorised as “moderately” disabled, even though a reasonable a priori expectation is that those disabilities would affect individuals’ earning capacities quite differently. Similarly, both paraplegics and quadriplegics would be categorised as “severely” disabled, even though, again, we know that those disabilities have quite different effects on earnings.

I. In this category, individuals receive 1 each time they indicate that they have difficulty with the activity, but are able to undertake it (“yes, but able”); and 2 each time they indicate that they have difficulty with the activity and are unable to undertake that activity (“yes, unable”).

1. Do you have difficulty hearing what is said in a conversation with

1.1 One other person?

1.2 A group of at least three other people?

2. Do you have any difficulty seeing the following when you wear your ordinary glasses or contact lenses?

2.1 Newsprint?

2.2 The face of someone across a room?

3. Do you have any difficulty speaking and being understood?

4. Do you have any difficulty:

4.1 Walking 350 metres without resting?

4.2 Walking up and down a flight of stairs?

4.3 Carrying an object of 4.5 kg for 10 metres?

4.4 Moving from one room to another?

4.5 Standing for more than 20 minutes?

5. When standing, do you have any difficulty bending down and picking up an object from the floor (e.g. a shoe)?

6. Do you have any difficulty

6.1 Dressing and undressing yourself?

6.2 Getting in and out of bed?

6.3 Cutting your own toenails?

6.4 Using you fingers to grasp or handle (such as using scissors)?

6.5 Reaching in any direction (e.g. above your head)?

6.6 Cutting your own food?

II. In this category, the individual receives 1 if he or she responds “yes” and 0 if he/she responds “no.”

7. Are you unable to hear what is being said over the telephone?

8. Do you have ongoing difficulty with your ability to remember or learn?

9. Has a teacher or health professional ever told you or a family member that you have a learning disability?

10. In the past, persons who had some difficulty learning were often told they had a mental handicap or that they were developmentally delayed or mentally retarded. Has anyone ever used those words to describe you?

III. In this category, the individual receives 1 if he or she responds “yes” with respect to one of the categories; and 2 if he/she responds “yes” with respect to two or more categories.

11. Because of a long-term physical condition or health problem (i.e. one that is expected to last longer than 6 months) are you limited in the kind or amount of activity you can do

  • At home?
  • At school?
  • At work?
  • In other activities (e.g. travel)?

12. Because of a long-term emotional, psychological, nervous, or psychiatric condition, are you limited in the kind or amount of activity you can do

  • At home?
  • At school?
  • At work?
  • In other activities (e.g. travel)?

13. Do you feel limited by the fact that a health professional has labelled you with a specific mental health condition, whether you agree with this label or not?

  • At home?
  • At school?
  • At work?
  • In other activities (e.g. travel)?

IV. Finally, if the individual had been diagnosed as legally blind, he/she was given a score of 2.

14. Have you been diagnosed by a specialist as being legally blind?

Table 1a: Earnings of disabled individuals compared to earnings of non-disabled individuals

Table 1a

Note: A dash indicates that the category’s sample size is too small to report a statistically reliable estimate.

Table 1b: Earnings of disabled individuals compared to earnings of non-disabled individuals

Table 1b

Note: A dash indicates that the category’s sample size is too small to report a statistically reliable estimate.

Chart 1a: Earnings of disabled males compared to earnings of non-disabled males

Chart 1a

Note: This chart graphically depicts the data shown in Tables 1a and 1b. The top of each bar represents the earnings of disabled males who reported earnings as a percentage of non-disabled males who reported earnings. The bottom of each bar represents the earnings of all disabled males (whether they reported earnings or not) as a percentage of all non-disabled males (whether they reported earnings or not). Where no bar is shown indicates that the category’s sample size is too small to allow us to report an estimate (corresponding to the dash in Tables 1a and 1b).

Chart 1b: Earnings of disabled females compared to earnings of non-disabled females

Chart 1b

Note: This chart graphically depicts the data shown in Tables 1a and 1b. The top of each bar represents the earnings of disabled females who reported earnings as a percentage of non-disabled females who reported earnings. The bottom of each bar represents the earnings of all disabled females (whether they reported earnings or not) as a percentage of all non-disabled females (whether they reported earnings or not). Where no bar is shown indicates that the category’s sample size is too small to allow us to report an estimate (corresponding to the dash in Tables 1a and 1b).

Table 2: The distribution of education levels among the four categories of disability

Table 2

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Derek Aldridge is a consultant with Economica and has a Master of Arts degree (in economics) from the University of Victoria.

Kris Aksomitis was a research associate with Economica and an MA student in Economics at the University of Calgary.

Recent Canadian Court Decisions Concerning the Impacts of Child Sexual Abuse on Earnings

by Christopher Bruce and Matthew Foss

This article was originally published in the winter 1999 issue of the Expert Witness.

We reviewed approximately 35 Canadian tort cases involving sexual assault that had been decided in the last decade. In this section, we review the findings of those cases under three damage headings: loss of earnings, loss of opportunity to marry, and punitive damages.

No loss of earnings

In approximately one quarter of the cases we reviewed, the courts denied the plaintiff’s claim for loss of earnings (after sexual assault had been proven). In some, – for example, B(KL) v. B(KE), M(LN) v. Green, and H(JL) v. H(DH) – the courts concluded that the non-pecuniary damages were “adequate” and, hence, pecuniary damages were not necessary. In others, for example C(P) v. C(RJ) and A(T) v. K(R), it was concluded that the plaintiff had not offered sufficient evidence on which to base an award. Finally, in both Gray v. Reeves and S(T) v. P(JW), the court could find no difference between the income the plaintiff would have expected to earn had he or she not been assaulted and the income he/she was actually earning.

These cases strike us as being consistent with the academic literature, which found that many victims of sexual abuse had not suffered long-term effects, particularly on earnings. Hence, it is not unexpected that some plaintiffs would be denied damages on this ground, particularly if they had not provided strong evidence of long-term (significant) harm.

Loss of earnings

In approximately three quarters of the cases which proceeded to trial, the plaintiff was able to obtain damages for loss of earnings. This is a higher percentage than the literature would lead one to expect. However, it must be remembered that the cases that reach trial are not a random sample of all possible cases. Presumably, few individuals who suffered no loss of income would press a case to that point.

The most common basis for the calculation of loss of income was that the plaintiff had suffered a reduction in the level of educational attainment, or had suffered a delay in reaching his or her ultimate educational level. In A(C) v C(JW), for example, it was found that one of the plaintiffs would have become an automobile mechanic and would only do so now, if at all, after a significant delay. In C(PA) v. T(JC), it was found that the effect of the abuse had been to prevent the plaintiff from graduating from high school. In P(J) v. Sinclair, the plaintiff’s actual earnings were compared to those she would have made had she completed two years of post-secondary education. And in P(S) v. K(F), the court concluded that it was reasonable to assume that the plaintiff would have completed high school but would not now do so.

Alternatively, in many cases, the courts accepted the argument that the plaintiff had achieved the same level of education as she or he would have in the absence of the abuse, but that the plaintiff would now suffer from higher unemployment, increased part-time work, or reduced overtime work. In B(J) v. M(F), the abuse was so severe that the court concluded the plaintiff would now be unable to work at all. In C(H) v. C(GC), the court accepted the argument that the effect of the abuse would force the plaintiff to reduce working hours from full-time to part-time. And in J(A) v. D(W), the court found that the plaintiff had missed a considerable amount of time from work during the pre-trial period.

In many of the cases in which damages for loss of income were awarded, the court implicitly recognised the argument that the victim’s low income might be due not only to the sexual abuse, but also to a dysfunctional family background. In A(C) v. C(JW), for example, there were four plaintiffs. The court noted that four out of five of plaintiff LK’s siblings had criminal records, were drug abusers, or otherwise had exhibited “lack of vocational success.” It appears that the court reduced LK’s damages on this basis. In the same case, on the other hand, the court noted that all three of plaintiff CH’s brothers had been successful and it awarded substantially more to CH than it had to LK. Similarly, in K(W) v. Pornbacher, because the plaintiff had a pre-existing prognosis of attention deficit disorder, the court reduced the damages it would otherwise have awarded. And in T(KA) v. B(JH), the court reduced the past loss to take account of “other contingencies” that might have affected the plaintiff’s earning capacity.

A common thread running through many of the cases in which victims were awarded damages for loss of income was the expectation by the court that the victim would soon “recover” from the effects of the abuse. The incomes of individuals who had suffered abuse 10 or 20 years prior to the trial were expected to “catch up,” within a few years of the court’s decision, to the incomes of those who had never been abused. In D(PA) v. H(AE), for example, the court awarded damages for only two years future loss. In V(JL) v. H(P), the court accepted the contention that the plaintiff would fully catch up within 5 years. And in P(J) v. Sinclair, the court assumed that the loss would continue for only 10 years into the future.

Loss of opportunity to marry

In two cases, the plaintiff argued that the effects of the sexual abuse had impaired her ability to marry. In Gray v. Reeves, the court concluded that the plaintiff had failed to provide adequate evidence concerning this claim, and refused to award damages. In LMN v. M(MJ), however, the court accepted the claim. Unfortunately, the court awarded a single sum to cover both loss of income and loss of marital prospect. Hence, it is not possible to determine what the value of the award was for loss of marital prospect.

Punitive damages

We were able to identify six cases in which punitive damages were discussed. In three, M(TD) v. G(KS), N(JL) v. G(KS), and Glendale v. Drozdzik, the court refused to award punitive damages. In the latter, the British Columbia Court of Appeal quoted approvingly from Huff v. Price, to the effect that:

The award of punitive damages should not try to do again what has already been done by the compensatory damages, including the aggravated damages. … And, of course, if a criminal penalty has been imposed then that should be taken into consideration. (p. 300)

Nevertheless, the court in Glendale added that:

…the rule would be too absolute if it were that punitive damages cannot be awarded if there has been a criminal penalty. Sometimes the criminal penalty might be as little as a conditional discharge…

In none of the three cases in which punitive damages were awarded were the defendants jailed for their assaults on the plaintiffs. In B(JD) v. M(F), the defendant was charged criminally for offences against other children, but not for those against B(JD). In C(H) v. C(GC), no criminal charges were laid against either of two defendants. And in M(M) v. F(R), the defendant received only three years probation on the criminal charge. All three, therefore, appear to be consistent with the view that punitive damages should, generally, only be awarded when there have been no criminal penalties, or those penalties have not been severe.

Summary

To summarise, the courts have looked for evidence that the plaintiff’s past and future earnings were impeded by the sexual abuse. This involved examining factors such as the plaintiff’s likely education without the sexual abuse, work history, and foreseeable career path in the future. Other factors that were given weight in the decisions included the accomplishments of siblings and the environment that the plaintiff grew up in (excluding the sexual abuse). The courts have not, in general, been overly generous to plaintiffs in their awards for lost earnings.

References

A (C.) v. C. (J.W.), 1997, 36 C.C.L.T. (2d) 224, 35 B.C.L.R. (3d) 234 (BCSC)

A.(D.A.) v. B. (D.K.), 1995, 27 C.C.L.T. (2d) 256 (Ontario Court of Justice (General Division))

A (T.) v. K. (R.), 1995, 15 B.C.L.R. (3d) 274, [1996] 3 W.W.R. 720 (BCSC)

B. (J.D.) v. M. (F.) 1998, Docket: Bracebridge 233/96, (Ontario Court of Justice (General Division))

B. (K.L.) v. B. (K.E.), 1991, 7 C.C.L.T. (2d) 105, 71 Man. R. (2d) 265 (Man. Q.B.)

C. (H.) v. C. (G.C.) 1998, Docket: 101497/96, 101496/96, (Ontario Court of Justice (General Division))

C. (P.) v. C. (R.J.), 1994, 114 D.L.R. (4th) 151, (Ontario Court of Justice (General Division))

C. (P.A.) v. T. (J.C.), 1998, Docket: Courtenay S3229, (BCSC)

D. (P.A.) v. H. (A.E.), 1998, 49 B.C.L.R. (3d) 340, [1999] 2 W.W.R. 139, (BCSC)

Glendale v. Drozdzik, 1993, 77 B.C.L.R. (2d) 106, 101 D.L.R. (4th) 101, (B.C.C.A.)

Gray v. Reeves, 1992, 64 B.C.L.R. (2d) 275, 10 C.C.L.T. (2d) 32, [1992] 3 W.W.R. 393, 89 D.L.R. (4th) 315, (BCSC)

H. (J.L.) v. H. (D.H.), 1999, Docket: F/C/259/96 (NBQB)

H. (S.) v. L. (R.G.), 1993, 85 B.C.L.R. (2d) 232, [1994] 2 W.W.R. 276 (BCSC)

Huff v. Price, 1990, 51 B.C.L.R. (2d) 282 (B.C.C.A.)

J. (A.) v. D. (W.) 1999, 136 Man. R. (2d) 84 (Man. QB)

K. (W.) v. Pornbacher, 1997, 32 B.C.L.R. (3d) 360, 27 C.C.E.L. (2d) 315, 34 C.C.L.T. (2d) 174, [1998] 3 W.W.R. 149 (BCSC)

LMN v. M. (M.J.), 1998, Docket: New Westminster SO-41750 (BCSC)

M. (L N) v. Green Estate, 1996, Docket: Doc. Vancouver C932295, (BCSC)

M. (M.) v. F. (R.), 1996, 22 B.C.L.R. (3d) 18, [1996] 8 W.W.R. 704, (BCSC)

M. (T.D.) v. G. (K.S.) 1997, Docket: Vancouver C961248, (BCSC)

N. (J.L.) v. L. (A.M.),.[1989] 1 W.W.R. 438, 47 C.C.L.T. 65, 56 Man. R. (2d) 161 (Man. Q.B.)

P. (J.) v. Sinclair, 1999, Docket: Victoria 93/3581, (BCSC)

P. (S.) v. K. (F.), [1997] 3 W.W.R. 161, 1996, 150 Sask. R. 173, 32 C.C.L.T. (2d) 250, (Sask. QB)

P. v. F., 1996, 24 B.C.L.R. (3d) 105 (BCSC)

S. (J.E.) v. M. (P.D.) Estate, 1998, Docket: Victoria 97 2335, (BCSC)

S. (L.) v. R. (L.), 1996, Docket: Vancouver C942578 (BCSC)

S. (P.) v. S. (J.), 1996, Docket: Milton C12210/93, (Ontario Supreme Court General Division)

S. (T.) v. P. (J.W.), 1999, Docket: Victoria 98/1477, (BCSC)

T. (K.A.) v. B. (J.H.), 1998, 51 B.C.L.R. (3d) 259, (BCSC)

T. (L.) v. T. (R.W.), 1997, 36 C.C.L.T. (2d) 207, 36 B.C.L.R. (3d) 165, (BCSC)

V. (J.L.) v. H. (P.), 1997, 31 B.C.L.R. (3d) 155 (BCSC)

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Matthew Foss is an M.A. student in the Department of Economics, University of Calgary. This is a continuation of his article “The Calculation of Damages in Sexual Abuse Cases” which appeared in the previous issue of this newsletter.

The Current Status of Survival of Actions Act Claims

by Christopher Bruce

This article was originally published in the autumn 1999 issue of the Expert Witness.

In Duncan v. Baddeley, Alberta Court of Appeal ruled that claims for loss of earnings were to be permitted under the Survival of Actions Act. Since that time, two trial court decisions have commented on the method by which this claim is to be assessed – Duncan v. Baddeley (Justice Doreen Sulyma) and Brooks v. Stefura (Justice Paul Belzil). In this note, I will argue that, although these two decisions clarify many of the outstanding issues in this area, a number of crucial problems remain unresolved.

Issues Clarified

The Duncan and Brooks trial decisions provided clear signals concerning the elements of the Court of Appeal decision that would be given greatest weight. In particular, two paragraphs from the latter decision were quoted by both Sulyma, J. and Belzil, J.

[37] The flaw in the “lost saving” approach is that it is heir-centred, not victim-centred. It asks what the heirs lost, not what the victim lost. But the suit here is not for the loss to the estate, it is a suit by the victim for his loss, a claim that by operation of statute survives his death and can be made by his estate for him. Worse, it has the air about it of an attempt to undermine the statute. As a result of this flaw, the approach will fail to take into account what has been called “discretionary” spending, like holidays and entertainment and other “treats.” It will also fail to take into account gifts to children and spouses, and thereby underestimate even an heir-centred award.

[42] In sum, Ms. Taylor in her excellent submission persuades me to accept in large the “available surplus” approach accepted by the U.K. Court of Appeal in Harris v. Empress Motors; Cole v. Crown Poultry Packers, [1983] 3 All E.R. 561, and adopted by the British Columbia Court of Appeal in Semenoff et. al. v. Kokan et. al. (1991) 4 B.C.A.C. 191; 84 D.L.R. (4th) 76. But it seems to me that it follows that a further deduction should be for expected income tax…

Lost Savings

In Galand, the Court of Appeal had directed that in Survival of Actions Act cases the estate was to be compensated for the value of the deceased’s (after-tax) income net of “personal living expenses.” Following Galand, some defendants argued that, as all expenditures could be considered to be directed to personal living expenses, the only portion of an individual’s income that would remain after deduction of those expenses was savings. Hence, the Survival of Actions claim was simply for lost savings.

Both Belzil, J. and Sulyma, J. concluded that the Court of Appeal decision in Duncan v. Baddeley required that “personal living expenses” were to be something less than total expenditures on consumption; and that the Survival of Actions claim was to be for something more than “lost savings.”

Available Surplus

In particular, that “something more” was to be calculated by deducting the “available surplus,” as calculated in Harris, from total after-tax income.

Justice Sulyma clarified that the “available surplus” approach was to be employed in the following manner. First, determine the deceased’s expected marital status and expected number of children. Second, estimate the percentage of the after-tax income of the deceased that would have been spent on: items specific to the deceased; and the percentage that would have been spent on items common to all members of the family (often called “indivisibles.”) Third, divide the indivisibles figure by the number of individuals in the family. Finally, deduct the sum of that figure and the figure for the deceased’s expenditures on him or herself from after-tax income. The result is the “available surplus,” that is, the amount to be compensated.

As an example, assume that it has been determined that a deceased male would have married and had two children. Assume also that evidence has been led to indicate that, of his after-tax income, 20 percent would have been spent on items that benefited the deceased alone (for example, expenditures on food and clothing) and that 30 percent would have been devoted to indivisibles. One quarter of the latter, or 7.5 percent, would be attributed to the deceased. Hence, it would be concluded that 27.5 percent of the deceased’s after-tax income would have been devoted to his maintenance and the estate would be compensated for the remaining 72.5 (= 100 – 27.5) percent, (the available surplus).

Two Technical Issues

At least two “technical” issues remain unresolved. First, the court has not turned its mind to the question of how to vary the available surplus over the individual’s lifetime. For example, if it has been assumed that the deceased would have had two children, it would seem reasonable to reduce the available surplus once the children left home. The general assumption is that, for a couple without children, 30 percent of family income is devoted to items that benefit one partner alone and 40 percent is devoted to indivisibles. Hence, once a couple’s children have left home, the available surplus should be assumed to fall from 72.5 percent to 50 percent (= 30 + (0.50 x 40)).

Second, it might be argued that the appeal court’s ruling that the available surplus was to be more than “lost savings” implied that all of the deceased’s expected “savings” should be included in the award. As a significant portion of the indivisibles represents purchases of capital assets, such as the family home, it might be argued that expenditures on those purchases are “savings.” As such, they should not be deducted from the award. This issue has not been resolved.

Two Conceptual Issues

In addition, the Court of Appeal decision in Duncan raises two conceptual issues that have not, as yet, been dealt with satisfactorily. First, that decision concludes both that the award should be something more than lost savings and that the available surplus approach is to be used. But, in certain circumstances, the latter approach yields results that are identical to the lost savings approach.

In particular, assume that the deceased was not married and that evidence has been led to suggest that he or she would never have married. In that case, the available surplus approach requires that all of the individual’s expenditures on personal items, plus all of his or her expenditures on indivisibles, be deducted from after-tax income. But the residual from that calculation is simply the individual’s savings. Does the Court wish us to compensate this individual’s estate for his/her savings, after explicitly rejecting the lost savings approach? The answer is not clear.

Second, note that the Court of Appeal ruled that the lost saving approach was flawed, in large part, because it “… will fail to take into account what has been called ‘discretionary’ spending, like holidays and entertainment and other ‘treats,’ … [and because it] … will also fail to take into account gifts to children and spouses.” [para. 37]

The simplest interpretation that can be given to this wording is that expenditures on holidays, entertainment, and other “treats” are not to be deducted from the estate’s claim. That is, if the lost saving approach is flawed because holidays, entertainment, and other treats are excluded, it surely must follow that, in the non-flawed approach, those items are to be included.

But the available surplus approach excludes these expenditures from the claim. The percentage of income that is devoted to expenditures exclusively for the benefit of the deceased includes expenditures that the deceased would have made on holidays, entertainment, etc. And the available surplus approach explicitly deducts expenditures made for the sole benefit of the deceased. Again, the Court ruling is found to be internally inconsistent.

Conclusion

The long saga that was initiated with the Court of Appeal ruling in Galand continues. Although the recent trial court decisions in Duncan and Brooks provide some clarification concerning the manner in which Survival of Actions Act claims are to be calculated, many issues remain to be resolved. Further rulings, perhaps from the Court of Appeal, will be required before a clear picture emerges.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Role of Expert Evidence

by Christopher Bruce

This article was originally published in the summer 1999 issue of the Expert Witness.

The readers of this newsletter are familiar with the use of expert testimony in the Canadian court system. Nevertheless, most of us would be hard pressed to provide a clear definition of the difference between experts and lay witnesses. On a day-to-day basis, the best many of us could do would be to paraphrase the old saw, “an expert is what an expert does.” On occasion, however, it may behoove counsel to examine closely the witness being put forward by opposing counsel and ask “is that individual truly an expert?” In this article, I summarise some of the leading decisions concerning this question from both the Canadian and American courts.

The classic Canadian statement of the role of expert evidence is found in Kelliher (Village of) v. Smith, ([1931] S.C.R. 672), in which the Supreme Court of Canada, quoting from Bevan on Negligence, concluded that in order for testimony to be considered “expert”

[t]he subject matter of the inquiry must be such that ordinary people are unlikely to form a correct judgment about it, if unassisted by persons with special knowledge. (p. 684)

Recently, in R. v. Mohan, ([1994] 2 S.C.R. 9, at 23) the Supreme Court elaborated on this requirement. There, Sopinka JJ stated that expert evidence must be both necessary in assisting the trier of fact and relevant. (Emphasis added)

Under the heading of “necessity in assisting the trier of fact” the Court made it clear that expert evidence was not to be admitted if the subject of the testimony concerned an issue which was within the common knowledge of the trier of fact. In particular, Sopinka JJ quoted approvingly from R. v. Turner, ([1975] Q.B. 834, at 841) in which Lawton, LJ concluded

An expert’s opinion is admissible to furnish the court with scientific information which is likely to be outside the experience and knowledge of a judge or jury. If on the proven facts a judge or jury can form their own conclusions without help, then the opinion of an expert is unnecessary. (R. v. Mohan, at 24)

Similarly:

…the evidence must be necessary to enable the trier of fact to appreciate the matters in issue due to their technical nature. (p. 23)

The Court ruled that, prima facie, expert evidence was “relevant” if it was “…so related to a fact in issue that it tends to establish it.” (p. 20) However, that was not to be the only criterion. In particular,

Evidence that is otherwise logically relevant may be excluded … if it involves an inordinate amount of time which is not commensurate with its value or if it is misleading in the sense that its effect on the trier of fact, particularly a jury, is out of proportion to its reliability. (p. 21)

Furthermore, relevance was also to include a test to determine whether the evidence was “reliable” and “essential.”

[E]xpert evidence which advances a novel scientific theory or technique is subjected to special scrutiny to determine whether it meets a basic threshold of reliability and whether it is essential in the sense that the trier of fact will be unable to come to a satisfactory conclusion without the assistance of the expert. (p. 25)

In short, the hallmarks of expert evidence were (a) that it concern matters of such a technical nature that the judge or jury could not be expected to reach a “correct” conclusion without assistance; and (b) that it be able to withstand close scrutiny to determine whether it was “reliable.” But those with some experience with litigation will recognise that this decision left many issues unresolved. Most importantly, a number of the terms that were crucial to the application of the Court’s decision were not defined. Without definitions of terms such as “special knowledge,” “reliability,” “novel scientific theory,” and “technical matters,” the lower courts were provided with little direction concerning the characteristics of “expert” testimony.

Some insight into the issues which can arise, and how the courts might resolve them, may be obtained by reviewing the interpretation which the courts in United States have given to Rule 702 of their Federal Rules of Evidence:

Rule 702. Testimony by Experts

If scientific, technical, or other specialized knowledge will assist the trier of fact to understand the evidence or to determine a fact in issue, a witness qualified as an expert by knowledge, skill, experience, training, or education, may testify thereto in the form of an opinion or otherwise.

As the wording of this Rule reflects the wording chosen by the Supreme Court of Canada in R. v. Mohan, the issues faced by the courts in both countries are similar.

Two recent decisions of the United States Supreme Court – Daubert v. Merrell Dow Pharmaceuticals, Inc. ([1992] 509 U.S. 579) and Kumho Tire Co. v. Carmichael, ([1999] 131 F.3d 1433) have ruled on the interpretation of the terms “scientific, technical, or other specialized knowledge” contained in Rule 702. In Daubert the court set out four criteria for determining whether expert testimony met the requirement that it constitute “scientific knowledge.” These are:

  1. Whether the theory or technique “can be (and has been) tested.”
  2. Whether the “theory or technique has been subjected to peer review and publication.”
  3. In the case of a particular technique, what “the known or potential rate of error” is or has been.
  4. Whether the evidence has gained widespread acceptance within the scientific community.

All of these criteria appear valuable for determining the admissibility of “scientific” evidence, such as the testimony of medical researchers. (The issue in dispute in Daubert was whether the drug Bendectin, when taken by pregnant women, had caused birth defects.)

These tests can also be applied to economic and psychological testimony, with some modifications. For example, the test of an economist’s or psychologist’s prediction that a particular child will graduate from university is not the usual “scientific” test, of waiting to see whether child does, in fact, graduate. Rather, it is a reference to the numerous statistical studies which have shown that a child’s ultimate educational attainment is significantly influenced by traits inherited from his or her parents and by such socio-economic factors as the child’s sex and his/her parents’ income and religion.

The second and fourth criteria are also applicable to testimony that is based on the use of theoretical constructs. For example, the concept of “opportunity cost,” which is the basis for one of the methods of valuing household services, has been developed by economists. Although it would be difficult to find direct empirical “tests” of this hypothesis, and its “potential rate of error” is not known; it has been “subjected to peer review and publication” and has “gained widespread acceptance within the scientific community.”

Similarly, whereas there is, to my knowledge, no published theoretical support for the use of the cross dependency approach to valuing fatal accident claims, a number of refereed articles provide such support for the use of the sole dependency approach. Again, although no “scientific evidence” can be offered that the latter approach is superior to the former, those who employ the latter can point to evidence of “peer review and publication.”

The Daubert criteria proved less applicable to issues involving “technical” knowledge, such as that often proffered by engineers, however. Accordingly, the United States Supreme Court agreed to hear Kumho Tire. In that case, a number of passengers in the plaintiff’s vehicle were injured when a tire blew out. An expert in tire failure analysis relied in part on his own (extensive) experience to conclude that the blow out was caused by a defect and not by misuse on the part of the plaintiff. As the expert’s testimony did not meet any of the criteria set out in Daubert, the issue in Kumho was whether “technical and other specialized knowledge,” as defined in Rule 702, was to be subjected to the same criteria as was “scientific knowledge.” The Court ruled that it was not. Testimony about a technical matter could be considered to be “expert” if it

…. focuses upon specialized observations, the specialized translations of those observations into theory, a specialized theory itself, or the application of such a theory in a particular case.

The function of Rule 702 was not to restrict expert testimony to a narrow set of “scientific” disciplines, but to

… make certain that an expert, whether basing testimony upon professional studies or personal experience, employs in the courtroom the same level of intellectual rigor that characterizes the practice of an expert in the relevant field.

This requirement, that “intellectual rigor” be applied, offers one of the most important “gatekeepers” when evaluating the testimony of those who have been put forward as expert witnesses. Too often “experts” offer no justification at all for their choice of a particular approach; or they offer little more justification than that it has “always been done that way” or that “a number” of courts have employed that approach. This is not evidence of intellectual rigor; nor does it meet any of the criteria for reliability or relevance set out by the Canadian and American Supreme Courts.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

On “Format of Expert Evidence of Economic Loss of Damages”

by Christopher Bruce

This article was originally published in the spring 1999 issue of the Expert Witness.

The Issue

Justice M. Bielby has invited comment concerning a proposed set of guidelines which deal with the presentation of expert evidence at trial. These guidelines, which were drafted by the Civil Practice & Procedure Committee of the Court of Queen’s Bench, attempt to ensure that the court receives enough information to permit it to calculate general damages in those cases in which it rejects the assumptions made by both sides to the dispute. The purpose of this article is to provide comment on these guidelines – which the Committee entitled “Format of Expert Evidence of Economic Loss of Damages” – from the point of view of an economist.

In a memorandum dated January 20, 1999, Justice Bielby offered the extreme example in which the plaintiff’s expert has been instructed to assume that the accident had left the plaintiff unable to work again; whereas the defendant’s expert has been instructed to assume that the plaintiff would not have worked even if the accident had not occurred. Thus, the plaintiff’s expert, in good faith, testifies that the plaintiff has lost, say, $800,000 of potential earnings; whereas the defendant’s expert, in equally good faith, testifies that the plaintiff has lost nothing.

This type of conflicting evidence does not create concerns for the court if there is a finding of fact that one or the other of these two extremes is correct. In that case, the court has sufficient evidence on which to base its calculation of damages.

When the court determines that the facts lie somewhere between the extremes offered by the two parties, however, the court may be left with little expert evidence on which to base its decision.

Assume, for example, that the plaintiff’s expert had been instructed that counsel would show that the plaintiff would have become an oil rig worker had the accident not occurred. The court, however, accepts the defendant’s argument that pre-existing disabilities would have prevented the plaintiff from entering such a physically demanding occupation; but rejects the defendant’s argument that the plaintiff had been incapable of earning any income at all.

Now, the only evidence available to the court is that the plaintiff’s damages lie somewhere between $0 and $800,000. The court has little or no information concerning what occupation the plaintiff could have entered; and even if it had received such information, say from a vocational psychologist, it has no evidence concerning the income which could have been earned in that alternative occupation.

The Proposed Guidelines

The guidelines suggested by the Civil Practice & Procedure Committee are designed to avoid leaving the court in this awkward position. In summary, these guidelines are:

  1. The expert’s report must list each of the factors upon which findings of fact must be made; identify, for each such factor, the assumption which the expert has chosen to make concerning that factor; and provide the reasons for making each such assumption. (For example, if the expert suggests that it is important to determine what the plaintiff’s level of unemployment would have been, the expert must also report the assumption which has been made with respect to that level and must explain why that particular level has been chosen).
  2. In any rebuttal report, the expert must expressly identify all of the factors employed by the other expert with which he or she disagrees; and must provide reasons for that disagreement.
  3. If the testimony of the expert(s) is insufficient to allow the court to determine the set of damages, based on that court’s findings of fact, those findings may be remitted to any expert for calculation of the damages. (In such a case, all parties have the right to be heard concerning the accuracy of the expert’s calculations).

Commentary

The goal of the Procedure Committee appears to be to ensure that the court is provided with expert testimony which is sufficient to allow it to choose from any one of a number of possible combinations of findings of fact. If so, I believe that the proposed guidelines will not achieve their desired results.

The first proposal will not change experts’ testimonies for two reasons. First, it has been my experience, in well over 2,000 personal injury and fatal accident actions, that the actions “directed” by the first guideline are already followed by virtually all expert economists in Western Canada. Hence, the guideline simply directs experts to continue doing what they have been doing all along.

Second, even if an expert was to follow the first guideline, the Committee’s goal would not be achieved. In the example developed by the Committee, the differences between the experts did not arise from some disagreement between them concerning the “facts”. It arose from differences in the instructions which they were provided by counsel. For example, assume that one expert is told that plaintiff’s counsel will prove that the plaintiff would have worked on the oil rigs and the other is told that defendant’s counsel will prove that the plaintiff would not have worked at all. In that case, the first guideline proposed by the Committee will have no influence on the opinions and assumptions employed by either of them. Hence, the problem identified by the Committee will not be resolved.

Equally, the second guideline will simply result in the two experts reporting that they had been asked to employ mutually inconsistent assumptions. The experts, however, will be unable to resolve those inconsistencies. Hence, once again, the guidelines will offer them no incentive to provide evidence concerning “compromise” outcomes.

The third guideline encounters the drawback that it offers no incentive for the experts to modify their testimony in court. It is strictly a method for dealing with the problems contemplated by the Committee ex post. I think all would agree that it would be preferable to find some way of altering expert testimony at, or prior to trial. Not only would that simplify the court’s role in calculating damages, it would also increase the probability that cases would be settled before reaching the trial stage.

A Modest Proposal

It is my observation that most inconsistencies between economists arise from differences in the “facts” which have been presented to them. If this contention is accepted, then the solution is to find a method by which those differences can be resolved. I can think of two possibilities:

First, a pre-trial conference could be held to determine whether differences between the economists’ calculations were based on inconsistent understandings of the “facts”. If so, judicial mediation or a “mini trial” could be employed to resolve those inconsistencies.

Second, if it became apparent, at trial, that the parties disagreed concerning certain important facts, both economists could be asked to delay their testimony until the end of the trial. By that time, the testimony of the lay and medical witnesses will often have cast sufficient light on the unresolved factual issues that the economists will be able to make their calculations on the basis of largely similar assumptions.

Or, failing that, the court could, prior to the entering of the economists’ evidence, rule on the findings of fact. With perhaps a day or two delay, the economists could recalculate the losses bases on those findings and enter their calculations as “examinable” testimony, (rather than as written reports, as envisioned by the Committee).

Use of a “Multiplier”

An alternative approach would be to have the economists provide a sufficiently broad set of “multipliers” that most findings of fact could be accommodated within them. Multipliers arise in the following way: Assume that, for a given set of assumptions concerning the discount rate and the plaintiff’s starting salary, current age, rate of growth of earnings, and retirement age it is found that the present discounted value of his future earnings stream is $400,000. Assume also that the starting salary which has been assumed is $20,000. If all other assumptions could be held constant, it is readily seen that if the plaintiff’s starting salary was to increase by 50 percent, to $30,000, the present value of his lifetime earnings would also increase by 50 percent, to $600,000. Similarly, if the other assumptions were to remain unchanged, but his starting salary was to decrease by 25 percent, his lifetime earnings would also decrease by 25 percent.

An alternative method of representing this same set of facts would be to recognize that, in the case cited above, the present value of the plaintiff’s lifetime earnings was 20 times his salary. This figure is referred to as the “multiplier”. It is often provided to the court when the facts concerning rate of growth of earnings, discount rate, and age of retirement are not in dispute, but there is some disagreement concerning the plaintiff’s starting salary. If the court is told that the relevant multiplier is, say, 20, then, once the starting salary has been determined, the court can readily calculate the present value of the loss of earnings. For example, if the court in this case was to decide that the plaintiff’s starting salary would have been $25,000, it would be able to determine that the damages were $500,000 (= 20 x $25,000).

My suggestion is that the experts be asked to provide a different multiplier for each plausible set of assumptions concerning rates of growth of earnings, discount rate, and retirement age. Then, the only finding of fact which the court would have to make, before it could determine the appropriate level of damages, would be the plaintiff’s starting salary.

The determination of this set of multipliers will be less onerous than it may sound for two reasons. First, experts rarely differ significantly with respect to the discount rate or the plaintiff’s retirement age. Thus, multipliers would have to be provided only for a selection of growth rates of earnings.

Second, growth rates of earnings tend to be associated very closely to education level. A comprehensive set of multipliers can be provided simply by calculating a multiplier for each of four education levels: university, college or trade school, high school, and less than high school. In the table on page 13, I provide sample multipliers for each of these education levels, first for a 25 year old male and a second for a 45 year-old male. What is readily seen is that three such multipliers would generally be adequate to cover most possible scenarios for a 25 year-old: roughly 28.5 for non-high school graduates, 31.0 for high school and university graduates, and 37.0 for university graduates. Furthermore, because growth rates of earnings tend to approach zero for all groups in later years, one multiplier – approximately 12.5 – may be sufficient for most 45 year-olds. Only in unusual cases, such as those in which the plaintiff might have been able to obtain a post-graduate degree, would more than three multipliers be required.

Sample Multipliers

Table 1

This is not to say that provision of such a set of multipliers would resolve all of the problems contemplated by the Committee. Disputes may still occur with respect to the plaintiff’s starting salary, fringe benefit levels, labour force participation, retirement age, or unemployment rate; and disputes may also occur with respect to the discount rate.

Nevertheless, if a complete set of multipliers was provided, and if the courts were properly trained in the use of those multipliers, I believe that many of the Committee’s concerns could be mitigated.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Duty of Care

by Christopher Bruce

This article was originally published in the winter 1998 issue of the Expert Witness.

This is the third in a series of articles in which I examine the application of economic reasoning to questions of liability in torts. In the previous two articles, I argued that the principles of tort liability can best be understood if it is assumed that the goal of the courts has been to deter future inefficient behaviour – rather than to compensate victims for past harms.

One corollary of that analysis is that if the threat of tort damages is not the most effective means of preventing a particular type of harm, the courts should refuse to treat the case under the rubric of tort law. In short, one would expect that there would be a “gatekeeper” doctrine in law that would allow the courts to divide the cases appearing before them into two streams: “tort cases” and “not tort cases.”

Economists argue that “duty of care” rules act as this doctrine. That is, to say that a party owes a duty of care is tantamount to saying (i) that any (potentially) negligent behaviour in which the party engages could be deterred by threat of tort damages; and (ii) that tort law is the most efficient technique for deterring any such behaviour. The advantage of viewing duty of care as having this gatekeeping function is that it provides a relatively simple framework in which to understand one of the most complex and misunderstood areas of tort.

Foreseeability

In some cases, it is clear, even before the court has heard evidence concerning the actions of a party, that the threat of tort damages could not have induced that party to change his or her behaviour. The clearest instance of this situation is that in which the party in question could not have foreseen that its actions had the potential to cause an injury.

In the classic Canadian case of Nova Mink v. Trans-Canada Airlines [1951] 2 D.L.R. 241, a low-flying airplane so scared the animals in a commercial mink farm that they ate their young, causing the owner considerable harm. The airline was held to owe no duty of care to the mink farm and, therefore, was not required to pay damages.

This decision is consistent with the view that tort actions are to be allowed only when they can deter harmful behaviour. (And it is strongly inconsistent with the view that the function of tort law is to compensate “deserving” plaintiffs.)

To have ruled in favour of Nova Mink would have established a precedent to the effect that injurers owe a duty even when they cannot foresee the consequences of their actions. Yet when those consequences could not (reasonably) have been foreseen no precautions against such consequences could have been taken. Therefore, any court action in such a situation could have produced no change in the behaviour of the parties. It could only have resulted in a transfer of income from the defendant to the plaintiff, at a great cost (in terms of judicial expenses) to society.

The Misfeasance/Nonfeasance Distinction

Even if the defendant has foreseen the harmful event, he/she will often not be found to owe a duty of care if his/her failure to act is one of nonfeasance rather than misfeasance. If it is the actions of the defendant which create the circumstances in which a third party may be harmed, failure to take precautions to avert that harm is called misfeasance. In that circumstance, the defendant will be held to owe a duty of care. If, however, the defendant has merely observed that a third party may be harmed if a certain precaution is not taken, and has not taken that precaution, that failure to act is termed nonfeasance. In that circumstance, the defendant may be found to owe no duty of care (assuming that he/she did not create the circumstances – i.e. that he/she was not also a misfeasor).

For example, if A knocks down a stop sign and lack of that sign subsequently contributes to the injury of B at that intersection, A may be found to have owed a duty of care to B – and may be found negligent for having failed to report the initial accident. On the other hand, if, after A has knocked over the stop sign, C notes the absence of the sign and fails to report that fact, C will not be found to have owed a duty of care to B.

On economic grounds this distinction initially appears arbitrary. If it is efficient for a person who knocks over a stop sign to report that fact to the authorities, it must also be efficient for an individual who observes that a stop sign has been knocked over to report that fact. How, then, can the difference in legal duty between these two situations be reconciled?

The answer may lie in the relative difficulty of identifying potential defendants. When A has knocked over the stop sign it will be much simpler to identify him as the defendant, ex post, than it will be to so-identify “innocent” passerby C. Whereas there will be only one individual like A (or at least a very limited number of such individuals), who will generally leave evidence of their involvement; there may be a very large number of individuals like C. Furthermore, very few individuals like C will leave any evidence of their presence at the scene. And most, if identified as being present, will be able to deny plausibly any knowledge of the potential harm, or may be able to argue that they thought someone else was attending to the matter. Thus, whereas the pursuit of efficiency may require that the individual whose actions initiate a harmful situation owe a duty to those who are (potentially) harmed, that pursuit may require that some alternative mechanism be employed to induce third parties to offer their assistance.

One such alternative would be to offer third parties incentives to induce involvement, rather than deterrents to prevent non-involvement. That is, the common law might provide a means by which those who performed “good deeds” – benefactors – would be able to force those who benefited from those deeds – beneficiaries – to provide them with rewards. The advantage of this approach, in terms of the analysis of the preceding paragraph, is that the problem of identifying potential benefactors, ex post, would be avoided. Those who observe a (potentially) harmful situation and feel that the benefit of their actions will exceed the costs will present themselves as “rescuers”, that is, they will become involved in the attempt to rectify the harmful situation.

In fact, we observe that if the costs of identifying benefactors are low relative to the benefits of the rescue, the law does operate in this manner. Awards are provided to those who rescue salvage at sea; doctors can charge fees to individuals whom they have rescued from imminent danger; and individuals who have stored lost property can claim for their expenses.1

The preceding analysis also helps to explain why a duty of care is found in one class of (apparent) nonfeasance – that in which it is inexpensive to identify the potential benefactor, ex post. In particular, a duty is often owed in situations in which the nonfeasance occurs on the property of the potential benefactor and in cases in which the benefactor has a pre-existing legal and/or contractual relationship with the beneficiary. For example, a homeowner has a duty to visitors to keep his sidewalks clear of ice; a municipality may have a duty to the users of its roads to ensure that stop signs are erected (and maintained) at dangerous intersections2; and shopkeepers may have a duty to their customers to ensure the safety of their premises. In each case, there is a party who is clearly-identifiable, ex post, who could have acted to protect the plaintiff.

There is also an efficient exception to this exception. Various altruistic groups – usually governments and charities – offer free services that may be interpreted as the provision of warnings concerning potential “harms”. For example, a local government may offer to send out its engineers to check earthen banks to ensure that there is no danger of them becoming unstable.3 Failure to respond to a request to provide these services clearly constitutes a nonfeasance. Yet, although the nonfeasor is easily identified, no duty of care is found. The reason that this ruling may be considered to be efficient is that if the “altruist” is found liable for failing to provide a service, the response of the altruist can be expected to be to withdraw that service. Such an outcome cannot generally be considered to be in society’s best interest.

Conclusion

The economic analysis of torts leads to the suggestion that the function of duty of care rules is to act as a “gatekeeper,” separating tort cases from non-tort cases. If the harmful behaviour of either party could have been deterred through the threat of tort sanctions, (and if such sanctions are the most efficient method for altering that party’s behaviour), the case should be considered to fall within the rubric of tort law. Otherwise, the gatekeeper should redirect the case away from the tort system.

Footnotes

1. For an economic analysis of the laws concerning “rescue”, see W. Landes and R. Posner, “Salvors, Finders, Good Samaritans, and Other Rescuers….,” 7 Journal of Legal Studies (January 1978), pp. 83-128. [Back to text]

2. See Anderson v. County of Ponoka (1980) 12 A.L.R. 320. [Back to text]

3. See Windsor Building Supplies v. Art Harrison Ltd. (1980) 14 C.C.L.T. 129. [Back to text]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Economics of Negligence Rules

by Christopher Bruce

This article was originally published in the autumn 1998 issue of the Expert Witness.

In the summer 1998 issue of this newsletter, I introduced the academic discipline of “the economic analysis of tort law.” I argued in that issue that the traditional legal analysis of torts employs an ex post orientation. That is, legal scholars traditionally assume that the function of tort law is to compensate victims for harms that have already occurred. Economists, on the other hand, argue that the evolution of torts can better be understood if one uses an ex ante paradigm. In this paradigm, the courts behave as if they are less concerned with the resolution of the cases before them than they are with the establishment of precedents that will affect future behavior. In particular, economic analysis “predicts” that the courts will prefer those rules that encourage parties to select cost-minimising behaviors.

In the summer 1998 article, I provided examples of a number of situations in which the courts appeared to have made explicit use of ex ante reasoning. In this article, I will argue that the economic approach can also be used to cast light on the development of the tort rules of negligence.

Legal Versus Economic Analysis

If one adopts the proposition that the function of tort law is to compensate accident victims, it is difficult to rationalise the rules of negligence. Those rules require that the victim show that the defendant was negligent before compensation will be ordered. But as many defendants are not negligent, many victims are not compensated. Why would a body of law whose purpose was to compensate victims contain a major “escape clause” which would deny compensation to a large percentage of victims?

One could begin to answer this question by modifying the traditional argument. Perhaps tort law is not designed to compensate all accident victims, just those who are deemed “worthy.” But this begs the questions of who is worthy and why it is that the “worth” of the victim should be defined by the behavior of the defendant.

I will argue in this article, that negligence rules can better be understood if we view their purpose as being cost-minimisation. Under this approach, a party will only be found to have been negligent (and therefore potentially liable to pay damages) if he or she had failed to take some precaution for which the cost was less than the benefit (measured in terms of accident costs avoided). That is, I will argue that the function of the tort rules of negligence is to send signals to potential (future) “injurers” that if they fail to take appropriate precautions, they will be made to bear the costs that result.

Negligence Rules: an Economic Exposition

The economic model can best be understood using a numerical example. Assume the following “facts,” (based, loosely, on Anderson v. County of Ponoka [1980] 12 ALR 320):

  • One of the stop signs at the intersection of two country roads is knocked over sometime on Saturday evening.
  • The County responsible for those roads becomes aware of this on Sunday morning but decides to wait until Monday morning to replace the sign, in order to save $100 overtime pay to its road crew.
  • Sunday evening, Mr. A, unaware that the sign is missing, assumes that he has the right-of-way, enters the intersection without slowing, and collides with Ms. B’s car.
  • The two cars and their occupants suffer damages which total $25,000.
  • At trial, the court accepts the evidence of a traffic expert that the probability, per day, that such an accident will occur is 3/1,000 if there is no stop sign in place and 1/1,000 if there is a stop sign.

Was the county negligent? Economic analysis predicts that the court will say “no.” Why? Assume that rural stop signs are frequently knocked down on Saturday evenings. If the relevant highway departments wait until Monday to replace the stop signs, there will be three accidents every 1,000 times a sign is knocked down. Hence, there will be $75,000 damages for every 1,000 such occurrences. ($75,000 = 3 x $25,000.) If the counties replace the stop signs immediately, the number of accidents will fall to one in every 1,000 occurrences, reducing the accident costs to $25,000, a saving of $50,000. But, in order to obtain that “saving,” counties will have to send out 1,000 repair crews at an overtime cost of $100 each, or $100,000 in total. The $50,000 “saving” will have cost $100,000.

Put another way, the average cost of precautions, per event, will be $100 and the average benefit of those precautions (measured in terms of accident costs saved) will be (2/1,000) x $25,000, or $50. As the economic model predicts that the court will only encourage behaviour whose cost is less than the benefit, the economic prediction is that the court will not find the county to be negligent in this case.

It can be seen from this case that three factors are predicted to enter the court’s calculations:

  • the cost to the defendant of taking a precaution to avoid the accident, (C);
  • the probability that a precaution which could have been taken by the defendant would have prevented the accident, (P); and
  • the expected cost of the accident, (A).

In particular, it is predicted that the defendant will be found to have been negligent if there was some precaution, not taken by the defendant, whose cost was less than the cost of the accident multiplied by the decrease in the probability of an accident which would have occurred had that precaution been taken. In algebraic terms, the party is found negligent if C < (A x P).

Is the Law Consistent With the Economic Model?

In the U.S., this prediction was confirmed in one of the leading cases on negligence, U.S. v. Carroll Towing. In that case, Justice Learned Hand concluded that negligence was to be found only if the burden (cost) of precautions was less than the probability of the accident multiplied by the gravity (cost) of the accident — precisely the formulation which I derived above from the economic model.

In British/Canadian jurisprudence, confirmation of the prediction is less direct, but persuasive nevertheless — sufficiently persuasive that in recent editions of Canadian Tort Law Allen Linden has organised his discussion of the rules of negligence around the “Learned Hand rule.” In Wagon Mound No. 2, for example, the court concluded that a party could be found negligent even if the probability of an accident was low as long as the cost of the accident was high. Arguably, it was the court’s view that the cost of the accident multiplied by the probability that it could be avoided should be weighed against the cost of avoidance in order to determine negligence — again, precisely the prediction made by economic reasoning. Other leading cases which are consistent with the economic model include Bolton v. Stone, Priestman v. Colangelo, and Reibl v. Hughes.

Applying Economic Analysis to the Law

Many “day-to-day” cases also employ reasoning which is consistent with the economic approach to the determination of negligence. For example, in Hewson v. City of Red Deer (1977) 146 DLR (3d) 32 (Alta. CA), a City employee left the keys in the ignition of a bulldozer. Subsequently, the bulldozer was stolen and driven into the side of Hewson’s house. The City was found not to be negligent largely because (a) the bulldozer was left two blocks from Hewson’s house; (b) it was left at midnight; and (c) the operator was absent for only 25 minutes. All three of these factors suggest that the probability of an accident was quite low. And the first factor suggests that the average damages which might occur if the bulldozer was stolen were low (because the bulldozer would have to be driven a long distance before causing any harm.)

In Weaver v. Buckle (1982) 35 AR 97 (Alta. QB), Weaver (a child) ran out in front of Buckle’s car and was injured. The court implied that it would not normally have found Buckle to be negligent for causing this accident. However, as the road was narrow, it found that he should have been driving more slowly, to take account of the general conditions of that road. The court concluded that if he had been driving more slowly, the probability that this accident would have occurred would have been reduced substantially. Buckle was found 60 percent liable. In economic terms, this finding suggests that it is not simply this accident which determines the “costs of an accident” (A, in my terminology). Rather, it is all accidents which might have been prevented had the defendant taken additional precautions.

In Jordan v. Schofield (1996) 148 NSR (2d) 104 (NSSC), Schofield’s 7 year-old son played with a lighter and caused a fire in an apartment building belonging to Jordan. The court concluded that Schofield was not negligent. Although parents are responsible for taking “reasonable” precautions to watch their children and to put harmful things out of their way, at some point the costs of additional precautions become prohibitive. Parents will not be found negligent for failing to take precautions beyond that point. For example, parents will not be negligent for leaving children unattended around “ordinary” dangers (such as knives or scissors) for a few minutes. They may, however, be negligent for leaving their children unattended around such dangers for longer periods of time, or for leaving them for only a few minutes around more dangerous items (such as fires burning in fireplaces). In economic terms, the cost of taking additional precautions is to be weighed against the probability that an accident will occur if those precautions are not taken.

To conclude, given that no Canadian court has formally adopted the “Learned Hand rule” it would be difficult to base an argument before our courts on economic reasoning alone. Nevertheless, if one accepts that the three components of the “Learned Hand Rule” (C, P, and A) play an implicit role in the determination of negligence, an understanding of their function may help to clarify the legal analysis in difficult cases.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Applying Economic Analysis to Tort Law

by Christopher Bruce

This article was originally published in the summer 1998 issue of the Expert Witness.

Economists have made important contributions to the analysis of many areas of the law – particularly competition law, labour law, regulation, and international trade – during the last 200 years. It is only in the last quarter century, however, that economists – and legal scholars using economics – have turned their attention in a systematic way to the analysis of torts, contracts, and criminal law. In spite of the youth of the sub-discipline that investigates these branches of the law, it has quickly become a major force within U.S. and, to a lesser extent, Canadian and European law schools. All of the major U.S. law schools – Harvard, Yale, Princeton, Chicago, Stanford, and Berkeley among them – now offer courses in the Economic Analysis of Law and have professors with Ph.D.s in Economics on faculty. (Only the University of Toronto, among Canadian schools, has followed suit.)

Those reading this newsletter will be familiar with some elements of the economic analysis of personal injury damages – for example, through my textbook Assessment of Personal Injury Damages (Butterworths, 1992). But economics, being the imperialistic science that it is, has not stopped there. Economic models have been applied to virtually every aspect of tort law – negligence rules, causation, onus of proof, intentional torts, informed consent, volenti, to name only a few. I do not wish to claim that the economic analysis of these doctrines should supplant the traditional legal analysis. However, I do think that there may be situations in which practitioners may find it useful to consider some of these issues from a different angle.

In this article, and a number of others to follow it, I would like to provide some insight into one such angle – the economic analysis of torts. In this introductory article, I begin by identifying the primary characteristics that distinguish the economic approach from more traditional methods of legal analysis. I then use this approach to discuss collateral benefits and negligence rules.

Characterising the Economic Analysis of Torts

Two fundamental characteristics distinguish the “economic” analysis of torts from other approaches to the study of tort law.

First, economists take a “positive,” or “scientific” approach to the identification of legal doctrines. Instead of trying to determine what the law “should be,” economic analysts attempt to determine what the law “is.” That is, they use the deductive approach to derive hypotheses about the principles which underlie judges’ reasoning and then test those hypotheses by comparing their predictions against the decisions which judges have made. As a simple example, economic analysis can be used to “predict” that the courts will, under most circumstances, reject the defence of “custom.” That prediction can be “tested” by observing whether the courts do or do not accept that defence.

Second, all economic analysis of tort law begins from the working hypothesis that judges behave as if they were attempting to devise legal rules which would encourage individuals to maximise social benefits net of social costs. (For example, if there is some accident-avoiding behaviour whose cost is less than the resulting saving in accident costs, the courts are predicted to adopt rules which will encourage adoption of that behaviour.) It is not argued that judges consciously act in this way; simply that the doctrines that have been selected by the common law courts have developed as though this was the goal of the courts.

This view of the functioning of the courts suggests that the courts will behave as if they were employing an ex ante (or “forward-looking”) approach to decision-making. In this approach, the courts recognise that any decision they make in the current case may influence the behavior of parties in similar, future cases. Hence, it becomes important to set a precedent which will direct future parties to behave in the socially desirable manner.

This approach can be contrasted with the traditional view of the court’s decision-making process, which I call the ex post (or “backward-looking”) approach. In this approach the court is assumed to take the position that, as the tortious act has already occurred, that act cannot be undone. Rather, all the legal system can do is to ensure that the victims are restored, as well as possible, to the position they would have been in had the act not occurred. Contrary to the economic assumption, no thought is given to the impact which decisions will have on future behaviour.

The ex post view is common to most textbooks and was given its most famous expression by the Supreme Court of Canada in Ratych v. Bloomer. There, Justice McLachlan concluded that the function of damages in tort law was to “restore the plaintiff to his pre-accident position.” Further, she emphasised that

[t]he law of tort is intended to restore the individual to the position he enjoyed prior to the injury rather than to punish the tortfeasor whose only wrong may have been a moment of inadvertence. [Emphasis added]

That is, the Court has said that tort damages are intended strictly to compensate harms that occurred in the past, not to deter negligent behavior that might occur in the future.

The response which those who rely on “positive” analysis of the law make to this argument is that the most reliable way to determine what someone thinks is to observe what they do, not what they say. In short, the best way to identify the underlying principles of tort law is to review the courts’ decisions, not their arguments. What I propose to argue in the following sections is that the courts’ decisions can often be more easily understood if it is assumed that they are trying to influence future behavior than if it is assumed they are attempting to “right past wrongs.”

The Collateral Benefits Rule

A clear example of the courts saying one thing and doing another arises in their interpretation of the “collateral benefits rule.” On the one hand, the Supreme Court has made it clear that it prefers the ex post approach. On the other hand, the trial courts have consistently adopted the ex ante approach.

1. Orphaned Children: Consider for example the situation in which orphaned children have been taken into the care of relatives.* Although Ratych would appear to suggest that the children’s claim for loss of dependency was thereby extinguished, most of the decided cases have rejected this view. The trial courts have recognised that the plaintiffs would be “double compensated” but have argued that to deny compensation would be to establish a dangerous precedent for future cases.

The leading statements of the latter view appear in Tompkins (Guardian ad litem of) v. Byspalko (1993) 16 C.C.L.T. (2d) 179 and Ratansi v. Abery [1995] 5 B.C.L.R. (3d) 88. In both cases, the trial judges argued that if Ratych was followed, the risk would be created that

… in some cases, family members who would otherwise take orphaned children into their care may decline to do so until or unless an award has been made in the children’s favour.

And in Tompkins, Spencer, J. went further, arguing that “… a surviving parent may refrain from remarriage, advantageous from the children’s point of view, because the presence of a new spouse who replaces services to the children may reduce their award”

2. Charitable Donations: Similarly, the rationale that is commonly given for the “charity exception” is that to deny a plaintiff compensatory damages because he or she had received a charitable donation would discourage individuals from making those donations. A clear example of this principle was stated in the Northern Ireland case of Redpath v. County Down Railway [1947] N.I.L.R. 167 where Andrews L.C.J. noted that if

the proposition contended by the defendants is sound the inevitable consequence in the case of future disasters of similar character would be that the springs of private charity would be found to be largely if not entirely dried up.

Surprisingly, further confirmation of this view comes from the author of Ratych, Madam Justice McLachlan. In her dissent in Cunningham v. Wheeler (1994) 113 D.L.R. (4th) 1 she argued that “… people should not be discouraged from aiding those in trouble.”

3. Implications: The common thread running through all of these decisions, I would argue, is that the courts will often consider the impact that their current rulings can be expected to have on individuals’ future behavior. In this view, the function of torts is not merely to compensate particular plaintiffs for past wrongs, but is also to protect potential plaintiffs from future harmful behavior. Children whose parents have been killed are to be protected against the possibility that their relatives may delay the adoption process; and victims of catastrophic events are to be protected against the possibility that donors may be discouraged from providing assistance.

This view opens a number of interesting possibilities for argument in similar future cases. For example, the practice has been to assume that a widow(er)’s loss of dependency comes to an end once she (he) remarries (assuming that the new spouse has a similar income to the first spouse). It could be argued, however, that this rule may encourage widow(er)s to postpone any relationships with the opposite sex until after the fatal accident case has been settled. As it cannot be in the public interest to discourage dating and marriage, a legal rule which has the effect of providing that discouragement may well be contrary to public policy.

In each case, economic analysts of the law would argue that the courts were behaving as if their goals were to encourage (socially) desirable behaviour and to discourage (socially) undesirable behaviour. In the next section, I will argue that it is rules of negligence which distinguish desirable from undesirable behaviour.

Negligence Rules

Assume the following facts:

  • One of the stop signs at the intersection of two country roads is knocked over sometime on Saturday evening.
  • The County responsible for those roads becomes aware of this on Sunday morning but decides to wait until Monday morning to replace the sign, in order to save $1,500 overtime pay to its road crew.
  • Sunday evening, Mr. A, unaware that the sign is missing, assumes that he has the right-of-way, enters the intersection without slowing, and collides with Ms. B’s car.
  • The two cars and their occupants suffer damages which total $5,000.
  • At trial, the court accepts the evidence of a traffic expert that the probability, per day, that such an accident will occur is 3/10 if there is no stop sign in place and 1/10 if there is a stop sign.

Was the county negligent? Traditional, ex post legal analysis has difficulty answering this question definitively. On the one hand, ex post analysis holds that the function of tort law is to compensate “worthy” victims, creating a presumption that the county should be found responsible. On the other hand, that analysis also argues that a defendant should only be found liable if he or she failed to take those actions that would have been taken by a “reasonable” person. But what actions would have been reasonable in this case? I will argue that the answer the courts will usually give to this question is consistent with the ex ante, or economic, analysis of the law.

In particular, if the function of the law is to encourage behaviour that maximises social benefits minus social costs (the economic prediction), a “reasonable” action will be one for which the benefits exceed the costs. That is, economic analysis predicts that the county will be found negligent only if the cost of ensuring that the stop sign was re-erected exceeded the benefit of doing so. In this section, I will show that the factors that enter the determination of those costs and benefits are the same as those that the courts usually take into account when determining negligence.

Assume that rural stop signs are frequently knocked down on Saturday evenings. If the relevant counties wait until Monday to replace their stop signs, there will be three accidents every 10 times a sign is knocked down. Hence, there will be $15,000 damages for every 10 such occurrences. ($15,000 = 3 x $5,000.) If the counties replace the stop signs immediately, the number of accidents will fall to one in every 10 occurrences, reducing the accident costs to $5,000, a saving of $10,000. But, in order to obtain that “saving,” counties will have to send out 10 repair crews at an overtime cost of $1,500 each, or $15,000 in total. The $10,000 “saving” will have cost $15,000. Put another way, the average cost of precautions per event (knocked over stop sign) will be $1,500 and the average benefit of those precautions (measured in terms of accident costs saved) will be (2/10) x $5,000, or $1,000. (Note: the reduction in the probability of an accident, when the county sends out a repair crew, is only 2/10 because the crew does not reduce the probability of an accident to zero.) As the economic model predicts that the court will only encourage behaviour whose cost is less than the benefit, the economic prediction is that the court will not find the county to be negligent in this case.

It can be seen from this example that three factors were predicted to enter the court’s calculations:

  • the cost to the defendant of taking an additional precaution to avoid the accident, (here, $1,500);
  • the probability that an additional precaution would have prevented the accident, (here 2/10); and
  • the expected cost of the accident, (here, $5,000).

In the U.S., this prediction was confirmed in one of the leading cases on negligence, U.S. v. Carroll Towing. In that case, Justice Learned Hand concluded that negligence was to be found only if the burden (cost) of precautions was less than the probability of the accident multiplied by the gravity (cost) of the accident – precisely the formulation which was derived from the economic model.

In British/Canadian jurisprudence, confirmation of the prediction is less direct, but persuasive nevertheless – sufficiently persuasive that in recent editions of Canadian Tort Law Allen Linden has organised his discussion of the rules of negligence around the “Learned Hand rule.” In Wagon Mound No. 2, for example, the court concluded that a party could be found negligent even if the probability of an accident was low as long as the cost of the accident was high. Arguably, it was the court’s view that the cost of the accident multiplied by the probability that it could be avoided should be weighed against the cost of avoidance in order to determine negligence – again, precisely the prediction made by economic reasoning. Other leading cases which are consistent with the economic model include Bolton v. Stone, Priestman v. Colangelo, and Reibl v. Hughes.

Conclusion

Economists often define their discipline to be the analysis of “the allocation of scarce resources among competing ends.” When this approach is applied to common law, it suggests that one of the functions of torts might be to establish rules that encourage individuals to use resources effectively. Common law precedents should not discourage relatives from adopting orphans, for example. Nor should they find defendants to be liable if they have taken all precautions for which the benefits (of those precautions) exceed the costs.

In this article, I have argued that this “law and economics” method of analysing the common law predicts that

  • the courts will employ the ex ante approach when resolving tort disputes; and
  • they will base the determination of negligence on: the probability of an accident occuring, the costs of the accident, and the costs of avoiding the accident.

I have also provided evidence that, at least in some cases, the Canadian courts have followed this approach.

I do not wish to conclude from this that the courts should follow the economic approach, nor that they will always adopt it. I merely offer it as another tool for those who are looking for an underlying rationale to the courts’ behaviour. Perhaps in some cases, the advocate and the court will find it of value to think explicitly in terms of the signal which the decision in the current case will send to others in situations similar to those in which the plaintiff and defendant found themselves. In future articles in this series I will discuss the economic analysis of such doctrines as custom, causation, duty of care, volenti, and restitutio in integrum.

Footnotes

* The foregoing analysis is based on an article that I wrote for The Lawyers Weekly (April 24, 1998). This article is also available, as “Duty to Care for Orphaned Minors,” on this website. [back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The Role of the Expert Witness in Developing “New” Law

by Christopher Bruce

This article was originally published in the spring 1998 issue of the Expert Witness.

One of the most exciting aspects of working in civil litigation is that participants in the legal system have the opportunity to influence the evolution of the law. Although some changes in tort law are imposed by legislatures, most developments are litigation-driven.

This raises a question which I have not seen asked anywhere else: Should arguments about changes in the direction of the common law be left to those trained in the law – judges and lawyers – or is there a role in this process for the testimony of “expert witnesses?”

I raise this issue as a result of my experiences with the evolution of two principles in damage assessment: the calculation of the dependancy rate in fatal accident actions and the calculation of the lost years deduction in serious personal injury claims.

Briefly, the two issues are these: In the case of the calculation of the dependancy rate, it is commonly accepted that the surviving spouse would have benefitted from approximately 70 percent of the (after-tax) incomes of each of the deceased and the survivor – with the remaining 30 percent having benefitted the deceased alone. What is not agreed, however, is whether the 30 percent of the survivor’s income which would previously have benefitted the deceased should now be deducted from the survivor’s loss of dependancy. (When this deduction is made, it is said that a “cross dependancy” approach has been used; whereas when the deduction is not made, it is said that a “sole dependancy” approach has been used.)

In the case of the calculation of the lost years deduction, the argument is that a plaintiff whose life expectancy has been shortened will not need to be compensated for the full value of the income lost during the years which he/she will not now live. Numerous theories have been put forward for the determination of the deduction which should be made – ranging from the deduction of only those components of income absolutely necessary to the maintenance of life to the deduction of the entire value of the plaintiff’s projected expenditure on consumption (i.e. deduction of the entire value of income except savings).

My purpose here is not to argue in favour of one or the other of the approaches to each of these issues. I have done that at length elsewhere*. Rather, my purpose is to ask what the role of economists – and other financial experts, such as accountants and actuaries – should be in the presentation of these issues to the court.

The Role of the Expert: Two Approaches

At least two contrasting approaches to the role of the expert can be defended. The first, which I will call “constructive” (but which others might call “interventionist”), recognises that legal arguments are often informed by developments in other disciplines – notably, philosophy, sociology, accounting, psychology, and economics. Where the arguments being made rely on sophisticated applications of these other disciplines, therefore, there may be a role for experts from those disciplines to testify concerning recent developments in the relevant literatures.

Some proponents of the constructive approach would go so far as to argue that such experts should be allowed to testify concerning what the law “should be.” A more appropriate role, I would argue, is that experts would merely be allowed to explain how the tools of their disciplines could be used to cast light on the issue facing the court.

The second approach, which I will call the “passive” approach, suggests that it is only those with formal training in the law who should be allowed to present arguments concerning potential changes in, or interpretations of, the common law. Hence, the opinions of non-legal experts should not be heard in court. The expert’s only role is to apply the existing law as best as he or she can.

The Constructive Approach

The primary advantage of the constructive approach, as I indicated above, is that theoretical and statistical developments in other disciplines will often be of value to the court in making its decisions. If extensive knowledge of these disciplines is required in order to fully understand the nature of the arguments, it may be preferable to have the presentation made in court by experts.

With respect to the lost years deduction, for example, economists, sociologists, and statisticians have considerable expertise with respect to both the definition and measurement of concepts such as “consumption” and “basic necessities.” And with respect to the measurement of dependancy rates, economists, sociologists, and psychologists have all written extensively about interpersonal relationships between spouses within marriage.

The primary danger associated with the constructive approach is that the expert will be tempted to stray beyond his or her area of expertise and begin to comment on matters requiring legal training. The first step in avoiding this problem is for the lawyer who has retained the expert to recognise that certain types of expert testimony can be construed as legal argument. Much of the testimony of experts in Canada concerning dependancy rates and lost years calculations, for example, has implicitly represented an argument concerning what the law “should be” – not because the expert saw that as his or her role but because the expert (and the retaining lawyers) had not recognised that that was what the expert’s testimony implied.

The Passive Approach

There are two advantages to the passive approach. First, it avoids the problem that the expert will stray outside the boundaries of his or her discipline. Second, if the law is well established, the expert will be able to avoid unnecessary testimony concerning possible alternative scenarios which have previously been ruled to be irrelevant. (For example, no Canadian economist would consider “wasting” the court’s time arguing that a tax gross up should be allowed on a loss of income claim, as the Supreme Court has clearly ruled that such a gross up will not be allowed.)

On the other hand, if the law is still evolving, the passive approach encounters two debilitating problems. First, any attempt to extract a straightforward rule from the decided cases is virtually doomed to failure. This is clear in the cases of both the dependancy and the lost years calculations. In both cases, there have been virtually as many different rulings as there have been judicial decisions. For anyone, lawyer or expert witness, to suggest that they can identify what “the” law is on either issue is presumptuous, if not preposterous. Nor would it be useful simply to adopt a “median” position. In issues like the dependancy rate there is no median position; and in issues like the lost years deduction there is no compelling reason to assume, ex ante, that the median position will prove to be the “correct” one.

Second, as a review of the decided cases on both dependancy rates and lost years deductions will reveal, when litigants first attempt to convince the courts to adopt a new legal principle, they often do not concern themselves with the finer details of those principles.

It is clear in the decided cases with respect to lost years, for example, that litigants and the courts have focussed primarily on the questions of whether such a deduction is required and, if so, whether it is “necessities” or the “costs of living” which should be deducted. Virtually no consideration has been given to the deeper issues of what the terms “necessities” and “costs of living” mean, nor of how one might measure those concepts. In the path-breaking Supreme Court case of Toneguzzo-Norvell v. Burnaby Hospital, the only evidence given by the plaintiff’s expert was as follows:

Q. …But would you agree that your average person … would spend something between 50 to 75 percent of their income on necessities…

A. Surely

No attempt was made to define the word “necessities” for the expert, nor was the expert asked to undertake any statistical research into the issue. Similarly, in another case which is widely quoted, the judge indicated that he had based his decision (concerning the lost years deduction) on the testimony of an expert economist. But when I contacted the economist in question he informed me that his entire testimony on that issue consisted of a brief response to a question put to him in cross-examination – a question to which he had not turned his mind prior to that time.

In the early stages of the development of new legal doctrines, it is common for “loose ends” to be left in this way. It would be inappropriate in my view for subsequent courts to rely too heavily on the “precedents” thereby established. Only when it can be shown that a superior court has turned its mind specifically to an issue, and ruled on it, would it be advisable for lower courts to rely on previously-made decisions in a developing area of law.

Furthermore, until the law has been clearly enunciated, it would seem inadvisable to insist that the expert rely strictly on “precedent” if that expert’s discipline has developed tools which would be of value to the court. Provided the expert testimony is presented as an aid to the court, rather than as an exposition of how the court “should” rule, that testimony may have a legitimate role to play.

Conclusion

It is not uncommon to find areas in the common law in which no clear precedent has yet been established. In some situations, like that of the argument concerning cross versus sole dependancy, this is because very few cases have been taken to court. In others, it is because the issues are so complex that the courts simply have not been able to turn their minds to all of the possible nuances. In these situations, I would argue that it would be irresponsible for an expert to argue that she or he had based a damage assessment on the “decided cases.”

At the same time, the expert must also recognise that his or her role in court is not to identify what the law “should be.” Rather, the expert must restrict her or his role to the presentation of theories or facts drawn from her/his disipline which can be expected to assist the court in making an equitable decision.

Footnotes

*On cross- versus sole-dependency, see Assessment of Personal Injury Damages, 2nd Edition (Butterworths, 1992); “Calculation of the Dependancy Rate in Fatal Accident ActionsExpert Witness, Winter 1996; and “Determination of Personal Consumption Expenditures in Fatal Accident Actions: A Note” Journal of Forensic Economics, 10[3], 1998.

On the lost years deduction, see “Shortened Life Expectancy: The ‘Lost Years’ Calculation“, Expert Witness, Spring 1996; “The ‘Lost Years’ DeductionThe Barrister, December 1996 issue (number 42); and “The ‘Lost Years’ Decuction” Lawyers Weekly, March 28,1997. [back to text of article]

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Outstanding Issues in the Valuation of Household Services

By Therese Brown and Christopher Bruce

This article was originally published in the spring 1998 issue of the Expert Witness.

In this, the final in a series of articles on the estimation of the loss of household services we discuss a number of issues which have received relatively little attention from the courts. These include:

  • the estimation of loss when the plaintiff can complete all necessary household chores, but these tasks take longer to complete than before the accident;
  • determining the age at which the loss of household services should be presumed to end; and
  • the effect of retirement on the number of hours of household services.

The Efficiency Issue

A common problem is that the injured plaintiff is sometimes still able to complete all the household chores that he or she performed prior to injury, but these tasks now take longer to complete. For instance, a female plaintiff may be able to continue with meal preparation and washing up, but whereas she had previously required 10 hours a week for this task, she finds that it now takes her approximately 15 hours a week.

One approach would be to argue that, as the plaintiff is able to “produce” the same number of household services as before her injury, she has lost nothing. However, this ignores the fact that she has lost the use of five hours per week in some other activity. Those hours may have come, for example, from hours worked or from leisure time. If it is the former, her damages could be valued using her wage rate. More commonly, however, it is leisure time that suffers, and only very rough estimates of the value of this use of time are available

A third approach, which we prefer, proceeds in two steps. First, we determine how many hours of household chores would remain to be completed if the plaintiff was to work the same number of hours in the home as she would have before the accident. Second, the cost of hiring replacement workers to perform those “missing” hours is calculated.

In the example cited above, assume that the plaintiff was to perform 10 hours of meal preparation after the accident. As she is working at only 10/15ths the speed that she had been working before the accident, she will complete in those hours, 10/15ths as much as she would have prior to the accident. That is, she will complete as many chores as she would have previously in 6.67 hours. This implies that 3.33 hours worth of chores remain to be done. It is the cost of hiring a housekeeper for this number of hours that we suggest should be used to represent the plaintiff’s loss.

At What Age Does the Loss End?

Two alternative approaches have been suggested to determine the age at which individuals would normally cease to engage in household production. The first such approach simply assumes that individuals cease to provide household services after their retirement ages. This approach is generally unsatisfactory, however, as the evidence suggests that the vast majority of seniors, some of whom may exhibit mild to moderate disability, do not require assistance with activities such as shopping or housework, the instrumental activities of daily living. Eric Moore et al, in their publication Growing Old in Canada, point to Statistics Canada data which indicates that 90.4% of men and 84.5% of women from 65 to 74 years old are in this category. Neena Chappell, in her book Social Support and Aging, argues that, while the existence of chronic health conditions is not uncommon in seniors, such conditions often do not lead to functional disability or limitations in activity.

A second commonly used approach is to continue the loss of household services only to age 80. There is considerable evidence to support this type of approach. Reference to statistical information about the living arrangements of today’s seniors, as well as their participation in household activities, makes it apparent that increasing numbers of seniors live independently to this age, requiring little or no assistance.

Herbert C. Northcott, in Aging in Alberta, makes evident the growing trend for seniors to remain in private households. While 13.4% of seniors in 1976 were institutionalised, this proportion dropped to 9.0% in 1991. Possible reasons for this decline include the increasing ability and desire of seniors to continue to live independently, as well as the shortage of institutional beds. At any rate, there is reason to suggest that the trend toward decreasing institutionalisation will continue.

Many seniors living at home do not require help with household work. The Statistics Canada publication A Portrait of Seniors in Canada makes this apparent. Of those 65 and older living at home in 1991, only 36% required assistance with housework. Fewer still required assistance with grocery shopping and yard work (31.5% and 30.0% respectively). Only 26% of this group required help with meal preparation. By far the greatest proportion of this assistance (68%) came from the individual’s spouse.

Much of the research would indicate, therefore, that not only are most seniors remaining in their own homes, but also most of them are managing to do so with little or no assistance. For this reason, it would seem prudent to recognise the extent to which most seniors are able to continue with productive contributions in the area of household services.

After age 75, however, an increasing number seniors suffer from chronic health conditions which limit their activity. An example of such an indicator is reported in the Statistics Canada Publication A Portrait of Seniors in Canada. While only 36% of 65 to 74 year-old non-institutionalised seniors reported activity restricting health problems, 46% of their counterparts aged 75 and older reported such restrictions. In addition the rate of institutionalisation does increase with advancing age. Herbert Northcott reports that in 1991, in Alberta, the rate of institutionalisation was only 2.8% for those aged 65 to but rose to 18.3% for those 75 years of age or older.

For these reasons, our approach is to seek a middle ground. It would appear that to assume that household productivity or participation in household services will decline significantly at 65 or 70 years of age would be to discount the contribution that many seniors are willing and able to make long past that arbitrarily assumed time. On the other hand, to continue the loss of household services to life expectancy would ignore the evidence that seniors in later years do increasingly face the risk of institutionalisation and activity-limiting disability. We find the statistical evidence supports the continuation of the loss of household services until approximately age 80.

Does a Change Occur in Household Services Contribution at Retirement?

Intuition suggests that the number of hours devoted to household work will decrease at retirement. This, however, is not what the statistics suggest. In fact, the contribution to household activities tends to increase significantly at retirement. An excellent source of information concerning the number of hours thus contributed is available from the Statistics Canada publication, As Time Goes By…Time Use of Canadians. For example, a married, retired male’s contribution at age 65 (3.1 hours per day) is almost double that of the married, full-time employed male’s contribution at age 45 to 64 years of age (1.7 hours per day). These available statistics can be readily used to forecast the future household contributions of the plaintiff at retirement. Our approach is to consider the number of hours that the plaintiff contributed prior to the accident and then increase them by the same percentage that the average individual’s contribution would increase, as indicated by this resource.

There may be concern expressed about this type of approach, for the reason previously mentioned, that an increase in household services at retirement may not be intuitively obvious. In our view, the approach we take – to adjust the individual’s contribution to reflect what actually occurs with individuals of the plaintiff’s ilk – is the only responsible approach to take in the interests of accuracy.

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From 1996 through February 1998, Therese Brown was a consultant at Economica.

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

BOOK REVIEW: The Expert: A Practitioner’s Guide, (Carswell) 1997

Edited by Mr. Justice K. Matthews, J. E. Pink, A. D. Tupper, and A. E. Wells

Reviewed by Christopher Bruce

This article was originally published in the spring 1998 issue of the Expert Witness.

The Expert is a collection of 27 essays concerning expert testimony, each essay having been written by one or more experts in the relevant discipline. The purpose of the book, according to the foreword, is to provide trial lawyers with a basic understanding of both “… the role of the expert in the legal process … [and] … the fundamental concepts of the discipline within which the expert operates.”

Measured against this goal, the book must be considered to be a success. Although the chapters are of extremely variable quality, anyone wishing to obtain an introduction to the role, and basic methods of analysis, of disciplines as widely diverse as forensic psychology, accounting, engineering, toxicology, and photography will find this book of value. I was fascinated, for example, by the scientific description of how a fire spreads (Chapter 24, “Forensic Fire Investigation”) and by the differences between the expert’s “model” of memory and that of the layman (Chapter 11, “Eyewitness Evidence Identification and Testimony”).

Nevertheless, the book suffers from two major weaknesses. First, from the point of view of civil litigation lawyers, the book focuses too narrowly on the experts who appear in criminal trials. Although one can imagine uses in civil trials for drug experts, pathologists, DNA experts, fire investigators, and handwriting analysts, their fields of specialty are not the everyday stuff of litigation. Furthermore, while concentrating on experts such as these, the book excludes many of the experts commonly found in civil litigation, particularly vocational psychologists, economists, therapists, and cost of care experts.

Second, in my view, the editors misunderstand what it is that lawyers would find useful in such a book. It is clear that each author has been asked to provide a 10 to 15 page summary of the role which an expert in his or her discipline can play in court, along with a brief outline of the basis of the scientific approach which characterises that discipline.

But consider: how often is it that a lawyer will not know what type of expertise is required for a particular circumstance? If photographic evidence is in dispute, it is not necessary to read a book on experts to know that it might be useful to hire a photographic expert. And if a claim has been made that an individual was abused as a child, most legal practitioners are knowledgeable enough to realise that they should seek out a psychologist with some expertise in “recovered memory.” Even if the field of expertise was sufficiently arcane that most lawyers would be unfamiliar with it, (forensic odontology is covered in Chapter 7), a single chapter listing the various disciplines and providing a one or two page summary of their areas of expertise would have been sufficient.

Furthermore, when an expert has been hired, one of the functions of that individual will be to educate the lawyer concerning the methodologies used by the expert’s discipline. It is not necessary to provide detailed descriptions of these methodologies in a book such as this.

Rather, it is my view that the primary function of a book on experts should be to provide two types of information:

  • a discussion of the law concerning expert witnesses; and
  • a critical analysis of the weaknesses of the methodologies employed by the various disciplines – in order to help you to avoid flaws in your own case and to find flaws in your opponent’s case.

With respect to the former goal, the first two chapters in this book – Mr. Justice Sopinka’s “The Use of Experts” and Richard Scott’s “Judges Instructions Re: Experts” – provide useful introductions. Justice Sopinka’s discussion of hearsay evidence will be particularly valuable to most litigators.

With respect to the identification of weaknesses in expert testimony, the book was disappointing. Only two chapters were of real value. The first of these was Earl Cherniak’s chapter on “Examination of the Expert Witness” which contains a number of useful tips from one of Canada’s foremost litigators.

I also found Dr. Reginald Yabsley’s chapter, “The Medical Expert,” to be refreshing. All of the other experts in this book merely described the fundamental methodologies employed by their disciplines and provided examples of testimony. At virtually no point did they turn a critical eye on their areas of expertise. Most of these chapters were little more than advertisements for their various disciplines. Dr. Yabsley, on the other hand, added two important elements to his chapter. He identified a number of weaknesses that are often found in medical testimony and he provided detailed analyses of two expert medical reports. Hence, unlike the other chapters in this book, his chapter provides a considerable amount of assistance to the cross-examiner.

In short, I would recommend this book only to those law firms with large practices in both civil litigation and criminal law. Until the editors restructure the book to provide a more balanced, critical review of each discipline, it is only the first four chapters which most litigators will find of value.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

D’Amato v. Badger – Complications Arising when the Plaintiff is a Business Partner

by Christopher Bruce and Scott Beesley

This article first appeared in the winter 1997 issue of the Expert Witness.

Some of the issues arising when an injured party had been a partner in a small business were recently discussed by the Supreme Court of Canada in D’Amato v. Badger, [1996] 8 W.W.R. 390 (S.C.C.). In that case, D’Amato had been one of two partners in an autobody repair shop. As a result of injuries suffered in an automobile accident, D’Amato’s ability to contribute to the operation of the business was severely and permanently restricted. D’Amato continued to provide some managerial services, but his primary services, as a skilled autobody repairman, had to be replaced with hired workers.

Nevertheless, between the time of D’Amato’s injury, in August 1987, and the trial, in March 1993, D’Amato’s partner, Namura, continued to pay D’Amato his pre-accident salary of $55,000 per year. Although the company recouped some of this payment from the services of replacement workers, the court found that the company’s profits were significantly lower during the pre-trial period than they would have been had D’Amato been healthy.

In this article, we wish to add to the analysis of the D’Amato decision by providing an economist’s perspective on the issues which were raised there. We do not, however, represent ourselves as experts on the legal doctrines which were discussed, in some detail, by the court.

Can a Company Claim When a Partner Is Injured?

Although the trial judge in D’Amato, Mr. Justice Vickers, awarded damages to D’Amato’s company, Arbor Auto Body, the Court of Appeal and the Supreme Court, ruled that the claim had to be made on behalf only of the injured partner. There was some suggestion from both of these courts that, as a public policy goal, claims from shareholders resulting from employee injuries should be discouraged (in order to encourage companies to insure themselves against such losses, and prevent frivolous claims). From an economist’s perspective, the critical factor in deciding whether or not a corporation (or partnership) suffers a loss when an employee is injured is simply whether or not that person’s labour can be replaced at constant cost. If the company can easily hire a replacement, or combination of replacements, who can produce identical business results at identical cost, then the company has suffered no loss at all. As this is almost always the case, few shareholder loss claims, for lost market share or profit, would succeed.

In practice, however, the business may incur additional costs associated with hiring and training and either lower quality or reduced productivity of replacement help. The loss claimed by Arbor (in particular the half of it claimed by Mr. D’Amato’s partner) was simply an attempt to recover an overpayment of salary relative to work provided, not an attempt to claim that the business was seriously impaired by Mr. D’Amato’s limitations.

In general, for medium-sized and larger companies, the employer’s loss in this type of case would be small, and the cost of putting forth a claim could be considerable, thereby limiting the number of claims. For a smaller business, however, any potential claim related to a loss of business volume would be greater, in a relative sense. It is quite plausible that the loss of a skilled technician like Mr. D’Amato could result in a loss of business, or that the added costs imposed on the company to find, train, and supervise replacement workers could be significant. As long as courts demand that the company in question provide firm evidence of any loss of business, or additional costs, then there would be no overcompensation. An additional factor which would create a tendency to modest awards is the short-term nature of this loss: Reputations can be re-established, training takes only so long, and hiring costs are a one-time item in most cases.

Should a Business Partner be Altruistic?

A complicating factor in D’Amato, which does not appear to have been considered explicitly by the Supreme Court, was that D’Amato’s partner continued to pay D’Amato his pre-injury salary after the injury, even though D’Amato’s productivity had been reduced significantly. According to Mr. Justice Vickers’ decision, D’Amato’s post-injury value to the company was only 25 percent of the salary which was paid to him. Had D’Amato been paid the actual value of his work, his pre-trial claim would have been roughly 75 percent of $55,000, or $41,250, per year. The business’ only losses, if any existed, would be from loss of volume, since customers would know Mr. D’Amato was not doing the work, or from the additional costs of hiring and training discussed above.

But Namura/Arbor did continue to pay D’Amato his pre-injury income. Hence, although the total loss which was incurred was the same as if Namura/Arbor had paid D’Amato only according to his post-accident productivity, the nexus of the loss was shifted – from D’Amato to Namura and Arbor. In spite of the fact that the total value of the loss was unaffected by this shift, the Court, by refusing to compensate Arbor for its overpayments to D’Amato, allowed the defendants to benefit from an altruistic act on the part of Namura.

From an economist’s perspective, if an injured employee’s compensation exceeds the value of his work in the open market, then restitutio requires that the excess amount paid will be claimable from the person who caused the injury. The difficulty is not in the principle, but in the details: it may not be instantly clear what the amount of the “overpayment” is. Replacement cost is one simple way to address the issue since, if the injured party is receiving his/her full prior salary, the cost of replacements represents the value of the services which the injured can no longer perform. Evaluation of replacement cost generally provides a reliable estimate of the employee’s decline in market value. When this overpayment has occurred, the correct redress is quite clear: the employer receives the amount by which the employee was overpaid, and the employee receives the amount they lost relative to his/her pre-accident level (so he/she receives nothing if the company continued to pay his/her full income).

An alternative view of the situation is that the overpayment provided by a partner (or any well-meaning employer) could be considered to be a gift or charitable donation and, hence, a form of collateral benefit, as receipt of the “gift” would not reduce the injured party’s claim. In that case, the replacement cost method should still be used to estimate the injured person’s true loss of income. Note that if a court judged annual pre-trial losses to be small, because the injured person received such benevolent overpayments, and based a future loss estimate on those artificially low figures, then the plaintiff’s loss could be seriously under-estimated, as the partner or employer is very unlikely to continue to overcompensate the plaintiff indefinitely. (This did not occur in Mr. D’Amato’s case, however, as the Court in that case implicitly assumed that Namura would cease to make overpayments after the trial.).

Furthermore, a finding by the Court that the plaintiff could be denied recovery if he had been “compensated” by his partner would send a strong signal to partners that they should refrain from assisting their colleagues when the latter had been injured. It does not seem likely to us that this is the signal which the Supreme Court intended to send, yet this is undeniably the signal which savvy partners will receive.

Two Examples

Two examples, based on D’Amato, will hopefully clarify these points. In both, we assume that, pre-accident, a partner in a business received compensation of $55,000 from the company for his physical and managerial labour, as full and fair compensation for those services. (The individual was also entitled to 1/2 of any business profit, as his return on capital. However, we ignore this as we assume that it is not affected by the injury.) After the accident, the injured party is able to contribute only the managerial component of the previous position, the market value of which contribution would approximate 25% of the pre-accident salary, or $13,750. In both cases, the total loss, $41,250, is identical. In both cases, as well, it is assumed that the business’ additional costs are limited to the cost of hiring replacement labour. Thus, the potential for a loss to the company, based on additional costs for hiring or training replacement labour, or decreased business volume due to loss of reputation, is not considered. The main point of difference between these cases concerns the post-accident compensation to the injured party, which results in different distributions of the total loss. If we assume that there are no other costs associated with hiring and training, and no loss of business due to loss of reputation, etc., then the financial position of the company is unchanged.

Case 1: Assume that the company pays the injured party only fair market value for his work, and that the balance of pre-accident salary of $41,250 (equivalent to $55,000 – $13,750) is paid to a replacement worker. Since other additional costs are not being considered here, it can be assumed that the financial position of the company remains unchanged. The injured person claims an annual loss of $41,250, from the dependant continuing into the future if the annual loss of income is not expected to change. Both the partner’s income and the injured person’s partnership income are also the same as prior to the injury.

Case 2: Assume the facts are as in Case 1, with one exception: the company continues to pay the full $55,000 per year to the injured employee, and therefore they are paying $41,250 “too much,” in order to assist the injured. The replacement labour must still, of course, be hired. The injured person can claim no loss there, unless, as discussed above, the excess payment is viewed as a collateral benefit. Company profit will fall by $41,250, the additional labour expense which has been incurred. Each of the partners bears half of the total loss of profit of $41,250 per year, and the economic analysis suggests that the business should be able to claim that amount from the defendant. The “overpayment” of salary to the injured party, of $41,250, is mitigating income which, in our analysis, represents a loan which required compensation. Should the court find that this overpayment is not compensable, the company would incur a loss of $41,250 per annum – a loss which it could have avoided by refusing to compensate the injured party.

Some Additional Complications

The above examples only discuss one form of loss, the physical inability to work. The situation is more complex at times. For instance, the injured person’s skills may be unique and, hence, irreplaceable. All business profit earned on the activity in question is now lost, in addition to the person’s own income as an employee. If other revenue is contingent on the presence of the injured party (e.g. painting after autobody work), then losses could in principle occur on all of that revenue also. Yet this would be a rather unrealistic extreme, since few if any of us are virtually irreplaceable. It is more realistic to imagine that the loss of a senior and extremely skilled person, who has a reputation for superior work, would indeed cause some loss of business volume, in addition to a proportional loss in an associated field within the business. In Mr. D’Amato’s case, it is not hard to imagine that most senior technicians who could work at his level already would own their own shops, in partnerships or otherwise. They might not be enticed to work for Arbor by anything less than Mr. D’Amato’s base employee income and a profit share, if they would move at all.

Correct determination of loss in such a case would require accurately estimating the loss of volume and profit which has resulted from the absence of the injured person. This may be uncertain, given that other changes in the operating climate occur at the same time, but if industry statistics suggest the company did indeed lose revenue in relative terms, then the difference between predicted and actual revenue may in turn have caused a loss of profit. We still suggest that the entire loss should be recoverable, by both the injured party and all other shareholders. If the partner’s employee income falls, that should in principle be recoverable as well (though that loss would be much smaller, since it would be mitigated by the fact that the partner can still work at something, even if his/her most lucrative opportunity is foreclosed by the absence of the injured person).

A further difficulty with D’Amato, in all three judgments, is that there was no discussion of the components of the company’s estimated pre-trial loss of $73,299. This figure may be interpreted primarily as replacement costs, in which event the analysis in the two cases discussed above applies, and the loss is really just D’Amato’s loss mitigated by a loan from Namura. Or is a significant part of that figure the result of decreases in business volume? The suggestion, that the loss reflects replacement expenses, is never confirmed. The denial of 50 percent of the pre-trial award to Namura suggests that in either case, the BCCA believed the company could not recover its loss. We disagree, particularly in the first instance, since it seems quite unfair to artificially lower a loss estimate because the partner or employer provided assistance in the form of a loan after the injury. In the loss of profit situation, we would still argue that both loss of labour income (suffered by the partner), and net business profits (suffered by the injured and the partner) should be recoverable.

Finally, we note that the judgments in D’Amato remain puzzling numerically. The trial justice and the Supreme Court each concluded that Mr. D’Amato’s future loss was best valued at 3/4 of $55,000 per year, or $41,250. There was no suggestion of any significant worsening of his condition on or about the time of the initial trial. That suggests that his pre-trial loss was also approximately the same annual amount, yet the plaintiff’s accountant reached a total pre-trial loss of $73,299, or only about $13,000 per year (over roughly 5.5 years). Even assuming that all of the $73,299 is actually Mr. D’Amato’s loss of value of work, the gap between pre-trial and post-trial is very large. Assuming no major changes occurred in Mr. D’Amato’s condition, then either the pre-trial loss was seriously underestimated, the future loss overestimated, or some combination of the two. A more exact determination of the value of Mr. D’Amato’s post-accident labour would be required to reach the correct figures, and similarly an estimate of business volume lost, or other costs imposed, would be needed to deduce the loss suffered by the business, in addition to “losses” which are actually just loans to a partner.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Scott Beesley is a consultant with Economica and has a Master of Arts degree (in economics) from the University of British Columbia.

Implications of Duncan v. Baddeley

by Christopher Bruce

This article first appeared in the summer 1997 issue of the Expert Witness.

The recent decision in Duncan v. Baddeley (Alberta Appeal #9503-0408-AC), provides important direction for both fatal accident and “lost years” claims. In this article, I review a number of the implications of this decision for the assessment of tort damages. The first part of the article deals with fatal accident claims. The remainder discusses “lost years” claims.

Fatal Accident Claims

Justice Kerans ruled that, regardless of whether the deceased had any dependants,

. . . in Alberta a claim for loss of future earnings does survive the death of the victim. And, with two important qualifications, that claim should be assessed as would any claim for loss of future earnings (Duncan, at 2).

The two qualifications to which he referred are that deductions are to be made from the deceased’s projected annual income for (i) income taxes and (ii) the “cost of personal living expenses.”

The purpose of this section is to assess the impact of the Duncan decision on the calculation of damages in fatal accident cases. This assessment is conducted in three parts. In the first of these, I review the calculation of the two deductions. In the second, I consider the arguments concerning a “tax gross up” in calculations based on Duncan. Finally, in the third, I identify whether there are any cases in which dependants, who are eligible to sue under the Fatal Accidents Act, might find it advantageous to base their claim on Duncan (that is, on the Survival of Actions Act).

Method of Calculation

Justice Kerans ruled that the income taxes which would have been paid by the deceased must be deducted from gross income when calculating the loss to the estate. Although he appears to believe that the deceased would have paid “. . . taxes in the area of 30 to 40 percent of his income,” Statistics Canada data suggest that the average Canadian household pays only 20 percent of its income as income taxes — with a range from about 10 percent to 30 percent.

Second, an amount is to be deducted from after-tax income for the “costs of personal living expenses.” After canvassing a number of alternative methods for calculating this deduction, Justice Kerans settled on an approach which he attributed to Constance Taylor, the plaintiff’s counsel. This method, which Justice Kerans refers to as the “available surplus” approach, was first enunciated in the U.K. Court of Appeal in Harris v. Empress Motors (1983) 3 All E.R. 561 and later adopted in one of the first Canadian cases concerning the “lost years deduction,” Semenoff v. Kokan (1991) 84 D.L.R. (4th) 76. In the latter case, the court concluded that the “conventional deduction” was 33 percent of income.

Kemp and Kemp on the Quantum of Damages explains how the available surplus approach is to be applied, using an example similar to the following: assume that a deceased male would have married and had two children. Of the family’s after-tax income, approximately 22 percent would have been spent on items which benefitted the deceased alone. In addition, approximately 40 percent of family income would have benefitted all members of the family equally. Thus, if one-fourth of that portion of income, or 10 percent, is allocated to the deceased, the total fraction of family income which would have benefitted the deceased is approximately 32 percent.

Two points need to be made with respect to the available surplus approach. First, it should be noted that if this approach was to be applied to an individual who had no reasonable prospect of being married over the period of her or his loss, the value of the damages which would be calculated would equal those calculated using the “lost savings” approach. That is, as all of a non-married individual’s expenditures are spent on him or herself, once personal expenditures have been deducted from after-tax income it is only savings which will remain. As Justice Kerans was highly critical of the lost savings approach, it appears that the available surplus approach may not stand up to scrutiny. Indeed, although Justice Kerans indicated that it was the plaintiffs who had argued for the available surplus approach in Duncan, a review of their submissions suggests that it is the “conventional approach” which they preferred. (See the discussion of “lost years,” below.)

Further, as Scott Beesley argued in “Shortened Life Expectancy: The ‘Lost Years’ Calculation” (Vol. 1(1) of The Expert Witness), it is difficult to argue that wealthy individuals spend as much as 32 percent of their incomes on the “costs of personal living expenses.” Rather, as incomes rise, an increasing portion of expenditures is devoted to items which could only be categorized as “luxury”. Thus, at least for high income earners, one would assume that the appropriate deduction would be less than 32 percent — and for low income earners it would be greater than 32 percent.

Income Tax “Gross Up”

Whereas an income tax “gross up” is allowed in most fatal accident cases, it is not allowed in personal injury claims for lost earnings. The usual rationale which is offered for this is that the effect of basing (personal injury) damages on gross (before-tax) income is to produce an award which is approximately equal to that which would have been obtained by “grossing up” a lump sum award based on after-tax income.

In Duncan, even though income tax was deducted, as in other fatal accident cases, no allowance was made for a tax gross up. It is my view that no gross up will be allowed in cases brought under a Duncan type of claim. The reason for this is that the tax gross up is only required if the plaintiff is expected to invest her or his award in order to replace a future stream of lost income. In Duncan claims, however, there is no presumption that the estate will invest the award in such a way as to replace the deceased’s income stream on a year-by-year basis. Hence, it appears that no gross up will be necessary.

Distinction Between the “Fatal Accidents Act” and the “Survival of Actions Act”

It appears from Justice Coté’s concurring decision in Duncan that overlap between Fatal Accidents Act and Survival of Actions Act claims will be possible in only extremely exceptional circumstances. Hence, it will be important to determine which of these Acts will yield the higher award to the plaintiffs in those cases in which they are eligible to select between those two causes of action — that is, in cases in which the plaintiffs are also dependants of the deceased.

It appears that in most circumstances dependants would receive a higher award under the Fatal Accidents Act than under the Survival of Actions Act. There are three reasons for this. First, whereas it is only that portion of family income which the deceased spent directly on him or herself which is deducted in a traditional fatal accident claim, in a Duncan type of claim, it is this amount plus the deceased’s share of common family expenses which is to be deducted. Second, no claim for loss of household services can be made in a Duncan claim. Finally, it appears that no tax gross up will be allowed in the latter claim.

There are, however, two factors which might make it advantageous for dependants to file their claim under the Survival of Actions Act. First, if the Alberta courts should decide that it is the cross dependency approach which is to be employed when calculating losses under the Fatal Accidents Act, a deduction will be made for the portion of the survivors’ incomes which was spent on the deceased. No such deduction was contemplated in Duncan. As this deduction can be very substantial — particularly when the survivors earn more than the deceased — high income survivors may be able to make a larger claim under the Survival of Actions Act than under the Fatal Accidents Act. (It should be noted, however, that many experts recommend use of the sole dependency approach. See, for example, my article, “Calculation of the Dependency Rate in Fatal Accident Actions” [Vol. 1(4) of The Expert Witness].)

Second, damages in fatal accident claims are reduced for the possibility that the surviving spouse may remarry. In cases in which this possibility is very high — usually those involving individuals less than 35 years old — the survivor may find it advantageous to claim under the Survival of Actions Act.

Alternatively, it has recently been suggested to me that it may be possible to add together a “standard” claim under the Fatal Accidents Act and some portions of the deceased’s income which cannot be claimed by dependants under the Fatal Accidents Act but which are permissible under the Survival of Actions Act. One such portion might be the “non-necessary” element of the deceased’s expenditures on him or herself. This portion would be deducted in a standard fatal accident claim but might be claimable under the Survival of Actions Act.

“Lost Years” Actions

Duncan also has important implications for the assessment of damages in “lost years” claims; that is, in personal injury claims in which the plaintiff’s life expectancy has been shortened significantly. In these cases, the courts have ruled that a deduction for the cost of necessities is to be made from the income which the plaintiff would have earned during his/her lost years.

Although Justice Kerans appeared to accept the “available surplus” approach to the calculation of this deduction, this approach necessarily becomes identical to the “lost savings” approach when the deceased could have been expected to remain single — and Justice Kerans had explicitly rejected the latter approach. With respect, I suggest that Justice Kerans’ discussion in Duncan is more consistent with the application of what is known as the “conventional deduction” approach than it is with the “available surplus” approach.

First, Justice Kerans expressed his approval of the B.C. Court of Appeal’s reasoning in Semenoff v. Kokan, in which the court appeared to have had in mind the “conventional deduction” approach. Second, the 20-30 percent deduction recommended by Justice Keran in Duncan was consistent with the 33 percent deduction adopted only two months earlier in the Alberta trial division decision: Brown and Fogh v. University of Alberta Hospital. In that decision, Justice Marceau explicitly adopted the “conventional deduction” approach.

Together, it appears that Semenoff, Brown, and Duncan signal a preference for a conventional deduction of approximately 30 percent in both fatal accident and lost years actions.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

The “Lost Years” Deduction

by Christopher Bruce

This article first appeared in the spring 1997 issue of the Expert Witness.

In a series of recent cases, defendants have argued that if an injury has shortened the plaintiff’s expected work life, full compensation should not be paid for the earnings forgone during the “lost years.”

Resolution of this issue has forced a re-examination of the legal foundations of personal injury damage assessment. At one extreme, restitution has been invoked to support the position that the plaintiff should be compensated for the full value of the income which would have been earned. In Andrews v. Grand & Toy (1978), 83 D.L.R. 452, for example, Dickson J. ruled that compensation must be awarded for “… the loss of that capacity which existed before the accident.” (at 469) This also appears to be the ruling in most American jurisdictions.

At the other extreme, McLachlin J., in Toneguzzo-Norvell v. Burnaby Hospital (1994) 1 S.C.R. 114, expressed concern that the plaintiff’s estate not be unjustly enriched. Her position was that, as the plaintiff would be adequately cared for from other heads of damage (e.g. the cost of care award), any funds paid in compensation for lost earnings would simply benefit the plaintiff’s heirs. Such enrichment may be sufficiently contrary to public policy that it would override the principal of restitution and justify the denial of compensation for lost earnings.

Legal decisions can be found to support virtually every position on the spectrum between these two extremes. Only two that I have been able to identify adopt Madame Justice McLachlin’s reasoning. In both Granger v. Ottawa General Hospital (June 14, 1996, Doc. 18473/90, Ont. Gen., Div.) and Marchand v. The Public General Hospital, ([1993] O.J. No. 561 (Ont. Ct. – Gen. Div.)), the plaintiffs were awarded only that portion of their incomes which would have been devoted to savings – apparently on the view that it was only that portion which would be lost by the plaintiffs’ heirs. (In Granger, savings were held to amount to 30 percent of earnings, whereas in Marchand 15 percent was assumed.)

Nevertheless, most experts testifying in Canadian cases have relied on the principle which underlay Justice Dickson’s decision in Andrews – that the plaintiff is to be compensated for the pleasure which will be forgone during the lost years. In particular, at least since Semenoff v. Kochan, (1991), 59 B.C.L.R. (2d) 195 (B.C.C.A.), there appears to have been agreement that the plaintiff should be compensated for that portion of his/her income which remains after deduction of “personal living expenses” or “necessities.” In principle, the pleasure which consumption of this residual would have provided during the years which have been lost can be replaced by consumption during the plaintiff’s now-shortened lifetime.

Where the experts disagree is with respect to the measurement of “personal living expenses.” First, although most of the reported cases assume that all expenditures on food, shelter, clothing, transportation, and health care are “necessary,” two alternative views have been proposed concerning the size of the family on which to base the calculations.

In both Semenoff, and Sigouin v. Wong, (1991) 10 C.C.L.T. 236 (B.C.S.C.), it was assumed that the plaintiff would have married and, therefore, it was only that portion of family income which would have been spent on the plaintiff which should be deducted. On that basis, the plaintiff was awarded 67 percent of the income which would have been earned during the lost years.

In subsequent cases – including Toneguzzo (where Madame Justice McLachlin did not apply her own argument concerning unjust enrichment), Pittman v. Bain, (1994) 112 D.L.R. (4th) 482 (B.C.S.C.), and Webster v. Chapman [1996] M.J. No. 384 (Man. Q.B.) – the courts have based their awards on the percentage of personal income which would have been devoted to necessities. This has led to awards lying between 50 and 60 percent of the lost years income.

A second source of disagreement concerns whether income taxes should be included as personal expenses. In a number of recent cases, the defendants have argued that taxes should be considered in this way. Should the courts agree, awards would fall to approximately 25 percent of the lost years income.

Finally, it has been argued that it is inappropriate to assume that all expenditures on broad categories, such as food and shelter, are “necessary.” According to this view, for example, only a small fraction of the expenditures which individuals devote to transportation could be considered to be necessary. Whereas individuals with incomes of $50,000 commonly spend $8,000 to $10,000 per year on automobiles and travel, they could meet their “necessary” travel needs by spending $500 to $1,000 on public transit.

All expenditures above the latter minimum could be considered to have provided pleasure. Hence, on the doctrine of restitution, they should be recoverable. When this approach is applied, it is found that it is only 15 to 30 percent of income which is devoted to necessities, leaving the remaining 70 to 85 percent to be compensated in damages. (This issue is discussed in greater detail in an earlier “Lost Years” Deduction article)

It is not yet clear what the resolution of these issues will be. All that can be said with certainty is that they have not yet received a full airing in the courts. My expectation is that in cases in which the plaintiff is not severely brain damaged, between 25 and 50 percent will be deducted for necessities during the lost years. In cases of severe brain damage, in which the plaintiff may not be able to benefit from an award for the lost years income, it is possible that the courts will follow Granger and Marchand and award only 15 to 30 percent of that income.

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Note: This article has been reprinted with permission from The Lawyers Weekly (March 28, 1997).

Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

BOOK REVIEW: John Barnes, Sports and the Law in Canada, 3rd Edition (Butterworths: Toronto) 1996

Reviewed by Christopher Bruce

This article was originally published in the spring 1997 issue of the Expert Witness.

John Barnes, B.A., B.C.L. (Oxon.) barrister, is co-director of the Sports Law Project at the University of Western Ontario. He has drawn on 20 years of experience studying sports law on three continents to write an intensively-researched yet eminently readable account of the state of sports law in Canada.

The first nine chapters of the book deal primarily with issues of contract and labour law in major league sports. For the sports junkies among us, this makes fascinating bedtime reading. But it offers little to those whose primary vocational interest is personal injury litigation.

Where the book should justify its purchase price to civil litigators is in Chapter 10, “Sports Injuries: Criminal and Civil Liability.” The 50-page section on civil liability contains over 350 footnotes – many of which list numerous references to books, articles, and cases. Analyses are provided of: intentional torts; assumption of risk; liability of participants (player sues player and spectator sues player); liability of facility operators (occupier’s liability to both participants and spectators; and owner’s liability in negligence); liability of schools, coaches, officials, and parents; liability of such organisations as amateur associations and professional teams; and medical negligence.

In each case the coverage is thorough and informative. Particularly commendable, in my view, is the index which not only provides the usual headings, such as “contracts” and “negligence,” but also allows the reader to search by sport – golf, hockey, rugby, football, gymnastics, etc. – and by type of injury.

My only complaint is that there is no discussion of the issues involved in the calculation of damages in sporting cases. This is only a minor complaint because there is, in my experience, only a small number of situations in which sports injuries raise unique concerns. Nevertheless, some recognition of these situations would have been useful.

One such case occurs when the plaintiff is a minor who claims that the injury has prevented him/her from becoming a professional athlete. As those with only a passing interest in sports will know, it is rare for even the number one draft pick to have a successful career in the NHL. How then to deal with the sixteen year-old who is third in scoring on a low-ranked junior A or university hockey team? Or the twenty year-old who is ranked twentieth among NCAA golfers? This is an issue which the courts have not faced clearly.

This minor quibble aside, I recommend Barnes’ book highly to anyone who is called upon to litigate a sports-related personal injury action.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Calculation of the Dependency Rate in Fatal Accident Actions

by Christopher Bruce

This article first appeared in the winter 1996 issue of the Expert Witness.

In a fatal accident action, the surviving spouse is entitled to claim for any loss of pecuniary advantage which would have been derived from the deceased. There is considerable uncertainty, however, concerning the manner in which this loss of dependency is to be calculated. The purpose of this paper is to discuss three alternative approaches to the calculation of the dependency and to argue that selection among them depends upon the nature of the couple’s marriage. The three approaches are defined in the first part of the paper. In the second, three types of marriage are defined and each type is matched with an associated method of calculating the dependency.

Theoretical Approaches to Calculation of Dependency

Assume that the husband of a childless couple has been killed. The husband was earning $30,000 per year (after taxes) and the wife $20,000 per year. Assume also that the wife’s dependency on family income has been found to be 70 percent – composed of 30 percent of family income spent on items which benefitted the wife alone and 40 percent spent on items which benefitted the husband and wife equally. Three different approaches to the calculation of the wife’s loss can be identified.

a) The sole dependency method

In this approach, the wife receives 70 percent of her husband’s projected income.

b) The “traditional” cross-dependency method

In this approach, the wife receives 70 percent of the family’s income net of her earnings:

(0.70 x $50,000) – $20,000 = $15,000 (2)

The source of the difference between these approaches can readily be seen if the cross-dependency equation is rewritten in a form which makes it equivalent to that used in the sole dependency method. In doing this, it is first necessary to recognise that the family income figure, here $50,000, is composed of the sum of the wife’s and husband’s incomes, that is, $30,000 + $20,000. Thus, the equation for the wife’s dependency in the cross-dependency approach, (equation (2)), may be rewritten:

0.70 x ($30,000 + $20,000) – $20,000 = $15,000 (3)

Furthermore, with rearrangement, equation (3) can be represented as:

(0.70 x $30,000) + (0.70 x $20,000 – $20,000) = $15,000 (4)

or as:

(0.70 x $30,000) – (0.30 x $20,000) = $15,000 (5)

That is, the difference between the sole dependency approach and the cross-dependency approach is that in the latter, the element (0.30 x $20,000), which is the portion of the wife’s income which had previously been devoted to the husband, is deducted from her loss of dependency.

c) A “revised” cross-dependency method

In this approach, the wife receives the husband’s total income net of the total amount devoted to his personal expenditures. Thus, as it has been assumed that the husband’s personal expenditures accounted for 30 percent of family income (and family income is $50,000), the wife would receive:

$30,000 – (0.30 x $50,000) = $15,000 (6)

Recognising, again, that the $50,000 family income figure in this equation is the sum of the husband’s and wife’s incomes, equation (6) can be rewritten:

$30,000 – (0.30 x ($30,000 + $20,000)) = $15,000 (7)

or:

$30,000 – (0.30 x $30,000) – (0.30 x $20,000) = $15,000 (8)

which, with simplification, becomes:

(0.70 x $30,000) – (0.30 x $20,000) = $15,000 (9)

Equation (9), however, can be seen to be identical to equation (5), the method for calculating a “traditional” cross-dependency. Hence, although the rationale for using equation (9) is different from that for equation (5), the two approaches yield the same result. It is for this reason that I used the term “revised” cross-dependency to describe the approach which was used to derive equation (9)

Three Types of Marriages

In this section, I discuss three types, or “styles,” of marriage and identify the appropriate dependency approach associated with each.

a) The idealised marriage. In what might be called an “idealised view of marriage”, the couple marries for love and shares all family income (approximately) equally. That 30 percent of family income is spent on items which benefit the husband alone implies that 30 percent of each of the husband’s and wife’s income is devoted to those expenditures. (And, conversely, 30 percent of each spouse’s income is devoted to items which benefit the wife alone.) The wife is assumed to spend 30 percent of her income on her husband because she loves him and, hence, derives pleasure from expenditures which benefit him.

In such a marriage, the pecuniary impact of the husband’s death is as follows: First, the wife has lost the 70 percent of the husband’s income (0.70 x $30,000 = $21,000) which he had spent on joint, family expenditures and on her personal consumption. Second, the wife now “saves” the 30 percent of her income, here $6,000 (= 0.30 x $20,000), which she had previously been spending on her husband’s personal consumption. However, it is not correct to say that she is “better off” by that $6,000. In the “idealised” marriage, her “gift” of $6,000 to her husband was voluntarily made because that use of her money gave her greater pleasure than any other use available to her. Thus, when the death of her husband “freed” her to spend the $6,000 on herself, she was not made better off. The “freeing” of the $6,000 forces her to purchase something – goods and services for herself – which she values less than the items she was purchasing before – goods and services for her husband.

A less emotion-laden example might help to explain this point. Assume that individual A has been leasing a car for $500 per month. The tortious intervention of individual B has destroyed the car and $1,500 of contents belonging to A. Although two months had remained on the lease, A has been excused from further payment (perhaps on the ground that the contract was frustrated). B admits that he owes $1,500 to A, to compensate him for the loss of his personal belongings, but argues that this should be offset in part by the $1,000 A has “saved” because he no longer has to make two months of lease payments. B’s argument is wrong. Although A now has $1,000 which he did not have before; he has been deprived of the use of a car, a use on which he had placed a value of at least $1,000. Instead of being made better off by the “gain” of that $1,000, he will actually be made worse off by the difference between the value of the car and the value of the “next best” set of goods and services which he can now purchase. Similarly, the wife who was previously devoting some of her income to her husband is not better off when she is prevented, by the tortious action of some third party, from spending that money. Rather, like the individual deprived of his car, she is worse off. Hence, in the idealised form of marriage, it is the sole dependency approach which is justified.

b) The marriage of convenience. The couple may not have married for reasons of love, but for reasons of financial gain. From a purely financial perspective, the marriage described above cost the wife $6,000 – the amount which she spent on items which benefitted her husband alone. In return, however, she received the benefit of the expenditures her husband made on her – 70 percent of his income, or $21,000. That is, she may be thought of as having “paid” $6,000 in order to receive $21,000. In such a marriage of convenience, the wife loses only the difference between these two figures – $15,000 – when her husband dies. (Note: the husband has also gained from this marriage, as he has “paid” 30 percent of his income, or $9,000, in order to obtain the benefit of 70 percent of his wife’s income, $14,000.)

In such a marriage, it is the “traditional” cross-dependency approach which is justified – subject to the following caveat: The 30 percent of the wife’s income which benefitted the husband alone must have been less than the 70 percent of the husband’s income which benefitted the wife, (and vice versa), otherwise the marriage would not have provided a financial gain to the wife. For example, if the wife’s income had been $50,000 and the husband’s $20,000, the wife would have spent (0.30 x $50,000 =) $15,000 on the husband in return for only (0.70 x $20,000 =) $14,000. Such an outcome would have been possible in an “idealised” marriage, but not in one which had been entered for financial gain.

c) A marital partnership. Although the couple may have married for love, they may have agreed to maintain separate bank accounts, with each spouse paying for those items which benefitted him/her alone. In this case, it is only that portion of the deceased’s income which was spent on joint household expenditures which the surviving spouse will have lost. In the example developed above, the husband was assumed to have earned $30,000 and the wife $20,000. Thirty percent of total family income, or (0.30 x $50,000 =) $15,000, was for the husband’s benefit alone. In the “marital partnership” model, the husband is assumed to have paid for all of the latter expenditures. What remained of his $30,000 income, after deduction of this figure, was the husband’s expenditure on items which benefitted the couple jointly. That amount is also $15,000 (= $30,000 – $15,000). It is the “revised” cross-dependency approach which would compensate the wife for the loss of this amount.

It will be noted that the loss of dependency calculated on this basis, $15,000, is identical to that calculated according to the “traditional” cross-dependency approach. This is not a coincidence. Mathematically, the two can be shown to be identical to one another. Hence, the use of the cross-dependency approach can be justified on the basis of either the “marriage of convenience” or the “marital partnership” model. It should be cautioned that both suffer from the reductio ad absurdum that individuals earning relatively high incomes will be found to be “better off” when their spouses are killed.

Conclusion

It is now seen that there is not a unique approach which can be applied to all marriages. Rather, one must consider the nature of the relationship which had been shared between the deceased and the plaintiff. Two types of evidence can be led: subjective and objective.

a) Subjective evidence. Subjective evidence concerns the nature of the personal relationship which had existed between the husband and wife. If evidence is led to indicate that the marriage in question had been based on love and mutual respect, a prima facie case would appear to have been made for use of the sole dependency approach. Only if it could be shown that the marriage was one of “convenience” would it be appropriate to employ the traditional cross-dependency approach.

b) Objective evidence. Objective evidence concerns the extent to which the couple had intermingled their incomes and paid for personal and household items jointly. Even when the court is reluctant to rule on the basis of the presence or absence of a “loving” relationship, use of the sole dependency approach can be justified on the pragmatic ground that many couples combine their incomes in a single pool, within which it is impossible to distinguish one individual’s contribution from the other’s. Hence, if 30 percent of the (family) income in this pool is spent on the husband, for example, it would not make sense to argue that 30 percent came entirely from his income. Rather, the more reasonable conclusion would have to be that 30 percent derived from his contributions to family income and 30 percent from his wife’s contributions – that is, that the sole dependency approach should be employed.

On the other hand, if the couple had carefully kept their accounts separate from one another, a strong presumption would appear to have been made for use of the “revised” cross-dependency approach – unless the individuals had markedly different incomes. (If the wife’s income was $10,000 per year and her husband’s $50,000, for example, it would be extremely unusual to find that the husband had spent 60 percent of “his” $50,000 income on items specific to himself; while only 60 percent of the wife’s $10,000 income had been spent on items specific to her.)

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Selecting the Discount Rate

by Christopher Bruce

This article first appeared in the autumn 1996 issue of the Expert Witness.

The discount rate is the interest rate at which it is assumed plaintiffs will invest their awards in order to replace their future streams of losses. As was explained in the first issue of this newsletter, it is the “real” rate of interest – or observed rate of interest net of the expected rate of inflation – which most financial experts prefer to use for this purpose.

In six provinces, the discount rate has been set by regulation. In the remaining four, including Alberta, however, the expert must provide evidence concerning the forecasted value of the real interest/discount rate. The purpose of this article will be to review a number of techniques for obtaining such a forecast and to provide an estimate of the real rate of interest based on the most reliable of these techniques.

The article will be divided into three sections. In the first, I list the rates in the six provinces which mandate a discount rate. In the second section, I summarise three methods which have been used to forecast real interest (discount) rates and identify the strengths and weaknesses of each of those methods. Finally, I select one method and use it to select a discount rate for use in Alberta.

Mandated Discount Rates

Mandated discounted rates in Canada
Province Discount Rate
British Columbia 3.5% (cost of care)
2.5% (loss of income)
Saskatchewan 3.0%
Manitoba 3.0%
Ontario 2.5%
New Brunswick 2.5%
Nova Scotia 2.5%
Prince Edward Island 2.5%

The discount rates shown in the previous table have been mandated in Canada.

Three Methods for Determining Discount Rates

1. The historical approach: The approach which, implicitly, has been favoured by those provinces which have mandated their discount rates is to assume that the average rate which has been observed in the past will continue into the future. Typically, those who use this approach rely on the real interest rates which have been reported over the entire post-World War II period. What analysis of these rates indicates is that real rates were fairly stable over the period 1950-1970, at approximately 3 percent. During the oil crisis, of the early 1970s, real interest rates fell, sometimes becoming negative. Towards the end of that decade, however, they began to rise again and it appeared that they would return to their historical level. But the rise continued beyond 3 percent and since 1983 real interest rates have consistently remained above that level. Indeed, real interest rates have remained above 4 percent for so long that it is now difficult to justify the use of a rate lower than that. At the very least, any expert who attempted to rely on the historical 3 percent average to forecast future rates of interest would have to explain why the 1980s and 1990s were such an anomaly.

2. Forecasting agencies: There is a small number of consulting firms in Canada which provide forecasts of such economic variables as GNP, the unemployment rate, and inflation. They will also forecast other variables, including the real rate of interest. Extreme caution must be used when employing these firms’ long-term forecasts, however. First, the mathematical models which they employ were built specifically to make short- term forecasts. Second, long-term forecasts cannot be made without imposing assumptions about many factors which are outside the mathematical models developed by these agencies, such as foreign interest rates, exchange rates, and government monetary and fiscal policy. Finally, private forecasters have little incentive to produce accurate long-term forecasts. A consulting firm’s reputation will not hinge in any way on the accuracy of its current forecasts concerning, say, the level of unemployment in 2020. The forecasts which customers use to evaluate the agencies’ accuracy are those which have been made into the near future, not the distant future. Hence, it is forecasts of one or two years on which consulting firms concentrate their resources. The real rate of interest, on the other hand, must commonly be forecast twenty or thirty years into the future.

3. Market rates: The third source of information concerning future real rates of interest is the money market. When an investment firm which believes that inflation will average 2 percent per year purchases 20 year bonds paying 6 percent, it is revealing that it expects the real rate of interest will average 4 percent over those 20 years. (The real rate of interest is the 6 percent observed, or “nominal,” rate of interest net of the 2 percent inflation.) Thus, if we knew the rate of inflation which investors were forecasting, that forecast could be used to deflate the nominal rates of interest observed in the market in order to obtain the implicit, underlying real rates. At the moment, such forecasts can be obtained with some accuracy. Not only do surveys of investors conclude that there is considerable agreement among them with respect to their forecasts of inflation – generally between 2 and 3 percent – but we know that the government is strongly committed to maintaining a long-run inflation rate below 3 percent. Thus, we can be confident that investors predict real rates of interest which are no less than the observed, nominal rates less 3 percent. (For information concerning the long-run expected rate of inflation, see Bank of Canada, Monetary Policy Report, May 1996.)

Alternatively, the Canadian government has for some time issued bonds which are denominated in terms of real interest rates, (real rate of interest bonds, or RRBs). By observing the rates of return at which these bonds sell, the real rate of interest which investors believe will prevail over the future can easily be determined. There are two drawbacks to the use of market interest rates to forecast future real rates of interest. First, the rate which is obtained from this method has not been stable, but has generally fluctuated between 4 and 6 percent since 1983. Hence, no definitive conclusion can be drawn. Second, as very few RRBs have been issued, the rates of return which they have obtained may not accurately reflect the rates in the market as a whole.

Forecasting the Discount Rate

Of the three techniques for forecasting real interest rates discussed in the previous section, the least satisfactory is the first one, based on historical rates. As those rates have varied so widely since the early 1970s, they convey little reliable information concerning the future. Of the remaining two, most economists prefer the market-based technique. A simple analogy will explain why.

Imagine that you wished to determine the average price which potential purchasers were willing to pay for twenty-year old, three bedroom bungalows in Edmonton. One approach would be to conduct a telephone survey of Edmontonians, asking them what they would be willing to pay for such homes. A second approach would be to observe the actual prices at which such homes sold in Edmonton. Clearly, the second approach is preferable. Why? Because rather than asking individuals how they think they will behave in some hypothetical situation, it observes how individuals actually behave when they have to commit large sums of money to their decisions.

Similarly, economists who are asked to forecast long-term interest rates recognise that little is at stake should those forecasts be in error. Whereas those who are involved in purchasing long-term bonds recognise that the smallest error can result in losses of tens of thousands, even millions of dollars. For this reason, Economica prefers to rely on the interest rates observed in the money market, rather than on surveys of economic consultants, to determine the long-run discount rate.

The following table summarises money market estimates of the long-run real rate of interest for three series: the rate of return on trust company five year guaranteed investment certificates, the interest rate on Government of Canada 10-year bonds, and the rate of return on RRBs. In each case, the figure represents the average of the rates reported in the second quarter (April-June) of 1996, net of the forecast rate of inflation. Two alternative real rates have been calculated for the GICs and the 10-year bonds: the first uses a forecasted rate of inflation of 2 percent and the second a rate of 3 percent. (The figure for RRBs is the same in both scenarios as the observed, market rate is already net of the rate of inflation.)

Real Rates of Return on Selected Long-term Investments: Canada 1996
Investment 2% Rate of Inflation 3% Rate of Inflation
Trust Company 5-year GICs 4.5% 3.5%
Government of Canada 10-year bonds 5.6 4.6
Real rate of return bonds 4.7 4.7

The figures in this table suggest that investors currently anticipate that the real rate of interest will fall somewhere between 3.5 and 5.0 percent. At Economica, we employ the mid-point of this range: 4.25 percent.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Damage Calculations in Fatal Accident Actions After Galand

by Christopher Bruce

This article first appeared in the autumn 1996 issue of the Expert Witness.

In an article published in the summer 1996 issue of this newsletter, I reviewed the theoretical arguments raised by Coté, J. A. in Galand Estate v. Stewart (1992), 6 Alta. L. R. (3d) 399 (Alta. C.A.). What Justice Coté concluded in his decision was that, in certain circumstances, the estate of a deceased could rely on the Survival of Actions Act to make a claim for loss of earnings. What was less clear in Galand were the types of cases in which such claims would be allowed; and the methods by which damages were to be calculated. The purpose of this article is to identify some of the issues which can be expected to influence the decisions concerning these two issues.

Cases in which Claims will be Allowed

There are at least four types of cases for which it appears that claims will be allowed. First, it appears that an estate will be able to claim under survival of actions legislation when a plaintiff dies after a personal injury trial but before legal proceedings have been completed. In the British case of Pickett v. British Rail Engineering Ltd. (1980), A.C. 136 (H.L.), for example, the plaintiff died after a personal injury trial but during the appeal process; and in the Canadian case of Hubert v. De Camillis (1963), 41 D.L.R. (2d) 495 (B.C.S.C.), the plaintiff died after trial but before the decision had been rendered. In both cases, the estate was successful.

Second, in Galand, Justice Coté noted that

…by the date of trial some of the wage loss of a deceased person may well be past and already incurred and exactly quantified…. So even on the respondent’s view of the law, this cause of action may exist and survive (at 405).

Third, Justice Coté also argued that in a case in which a beneficiary of the deceased was not a dependent and

…the premature death of the deceased clearly deprived the beneficiary of part of his inevitable inheritance… [t]here is a plain financial loss (at 406).

Finally, two of Justice Coté’s examples pointed to the conclusion that he would have been willing to award damages under the Survival of Actions Act in a case in which the deceased had a “…completely secure salary and employment … at the time of his injury or death” (at 403). He referred specifically to the case of a tenured university professor (at 403) and to Wayne Gretzky when he was single (at 406).

The only Alberta case to award damages for lost income under the Survival of Actions Act since Galand is McFetridge Estate v. Olds Aviation Ltd. (unreported, Edmonton, April 12, 1996). In that case, the deceased had been a successful businessman whose future income stream Justice Lee found to be easily quantifiable. That is, it appeared to have fallen into the fourth of the categories identified above.

What is not yet known is how the Appeal Court will deal with cases of a more speculative nature, such as those involving the loss of lifetime income of an individual who was a minor at the time of his or her death. This issue may be decided later this year when the appeal is heard in Duncan Estate v. Bradley (1994), 161 A.R. 357 (Alta. S.C.).

Assessment of Damages

Section 5 of Alberta’s Survival of Actions Act states only that:

5. If a cause of action survives under section 2, only those damages that resulted in actual financial loss to the deceased or his estate are recoverable… (emphasis added)

What is not indicated is how the courts are to assess “actual financial loss” to an estate. Nor does the decision in Galand offer a great deal of assistance as the court was asked only to consider the issue of whether a cause of action survived a plaintiff’s death – not what that “action” might be.

Nevertheless, the courts have provided some information concerning the approaches which they prefer. Three of these will be considered here.

The loss of inheritance approach: In Toneguzzo-Norvell v. Burnaby Hospital, [1994] 1 S.C.R. 114, Madame Justice McLachlin (at 127-128) cited approvingly from Cooper-Stephenson and Saunders (Personal Injury Damages in Canada (1981) at 244) who argued that:

…the award of damages to a very young child for prospective loss of earnings during the lost years should reflect only that portion of the entire lifetime earnings which the court estimates would have been saved by the child for his estate, at the end of his pre-accident life expectancy (emphasis added).

The rationale which Cooper-Stephenson and Saunders offered for this position was that “…the prime purpose of the award during the lost years is to make provision for [the deceased’s] dependants” (at 243). In short, as the purpose of tort damages is to compensate the plaintiffs, an award based on a more liberal approach would result in a “windfall” for the dependants.

In Alberta, there is a number of weaknesses to this approach. First, the “windfall” argument has already been rejected by the majority in Galand. Second, as will be noted below, there is reason to believe that Galand sets a precedent for use of the “lost years” approach.

Also, Section 5 of the Act states that “…damages that resulted in actual financial loss to the deceased or his estate are recoverable” (emphasis added). On a plain reading, “loss to the deceased” would appear to imply something more than “loss of inheritance.” Finally, in Galand Justice Coté cited Pickett as precedent for the view that an estate should be able to “…recover for tortious loss of earnings or earning capacity of the deceased” (at 407, emphasis added).

The lost years approach: Assume that the plaintiff’s injuries have reduced her life expectancy from 40 years to 10 years. During the 30 years which have been “lost,” the plaintiff would have received income which would have been offset, to a certain extent, by expenditures on “necessities.” The theory behind the “lost years approach” is that, during those 30 years, the plaintiff has lost the pleasure associated with the difference between her income and her living expenses. (This issue was discussed in greater detail in the first issue of this newsletter.) During the remaining 10 years, she will be entitled to her full loss of earnings (as she will have to incur her full living expenses during those years).

Now assume that, instead of having a reduced life expectancy of 10 years, the plaintiff’s life expectancy has been reduced to two years. In a personal injury action, she would be entitled to damages equal to her income during those two years plus the difference between her income and her expenses in the remaining 38 “lost” years.

By simple extrapolation, it is seen that if the plaintiff’s life expectancy has been reduced to one year, or one month, or one week, a similar calculation can be made. And if we take the argument to its logical conclusion, if the plaintiff’s life “expectancy” has been reduced to one second, the “lost years” approach would suggest that damages should equal the difference between her projected lifetime earnings and her projected lifetime expenses in the 40 years which have been “lost.”

Both the Pickett and Hubert cases discussed above offered support for use of the lost years approach. If the estate of a plaintiff who has died soon after a trial is to be awarded damages based on the lost years approach, it would seem to be difficult to justify a different approach in the case of a plaintiff who has died soon before (or during) a trial. Furthermore, both Justice Coté’s approval of Pickett and his comment that “…the deceased had a cause of action for loss of future earnings because life expectancy was shortened.” (Galand at 404, emphasis added) seem to suggest that the Alberta Court of Appeal is prepared to employ the lost years approach.

Nevertheless, an inconsistency arises when the lost years approach is extrapolated from personal injury cases to fatal accident cases. One rationale for the lost years approach in the former is that the plaintiff could, in principle, replace the pleasure foregone during the lost years by spending her award during her remaining years. That is, the award in such a case can be seen as compensatory to the plaintiff. This rationale is missing in fatal accident cases (although it is also missing in personal injury cases involving plaintiffs who have become “vegetables”).

Loss of a capital asset: In a leading Supreme Court of Canada case, The Queen v. Jennings ((1966), 57 D.L.R. (2d) 644), Judson, J. concluded that if a plaintiff “…has been deprived of his capacity to earn income… [i]t is the value of that capital asset which has to be assessed” (at 656, emphasis added). Further, in Andrews v. Grand & Toy (1978) D.L.R. (3d) 452 (S.C.C.), Mr. Justice Dickson argued that this asset should be assessed at the value which it possessed before the injury; that is, unreduced for the lost years.

The controversial question then arises whether the capitalization of future earning capacity should be based on the expected working life span prior to the accident, or the shortened life expectancy…. When viewed as the loss of a capital asset consisting of income-earning capacity rather than a loss of income, the answer is apparent: it must be the loss of that capacity which existed prior to the accident (at 469-70).

But if one’s future earning capacity is to be treated as a capital asset, how is that asset to be valued? Two possibilities present themselves. First, as Mr. Justice Dickson implies, one could simply capitalize the future stream of income into a commuted value.

Alternatively, however, one could recognise that the value of a physical asset is not the capitalized value of its future stream of total earnings, but the value of those earnings net of the expenses of operation and maintenance. In that case, the loss of the capital asset, “future earning capacity”, would be found by capitalizing the individual’s future stream of earnings net of expenditures on necessities. That is, the capital asset approach may produce a result similar to that obtained using the lost years approach. Interestingly, this rationale for the lost years method does not encounter the objection raised above – that it assumes the plaintiff will live long enough to consume the award.

Implicitly, Justice Lee accepted the capital asset approach in McFetridge. There, the estate was awarded damages equal to the reduction in the value of the deceased’s businesses.

Comment

If the Court of Appeal does not reverse the Galand decision entirely when it hears the Duncan appeal, I believe that the law will develop as follows: First, the arguments made in the preceding section seem to suggest that it is the lost years approach which will be used to value damages, although the court may couch its decision in terms of the capital asset approach.

Second, over time, I believe that the courts will apply survival of actions legislation to all types of cases, including those involving minors. The reason for this is that once the courts allow actions in cases involving plaintiffs with “well-established” career patterns, such as tenured university professors, they will encounter difficulty distinguishing those situations from cases in which the deceased was “secure” in his or her career, such as a 35 year-old mechanic or engineer. This will give the courts difficulty distinguishing the latter from recent university or technical school graduates, graduates from high school students, and high school students from infants. Eventually, therefore, the estates of all fatal accident victims will be able to claim under the Survival of Actions Act.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Fatal Accident Cases After Galand

by Christopher Bruce

This article first appeared in the summer 1996 issue of the Expert Witness.

The Alberta Court of Appeal decision in Galand Estate v. Stewart (1992), 6 Alta. L. R. (3d) 399 opened the possibility that the estate in a fatal accident action could claim for the deceased’s loss of earning capacity (both past and future). Subsequently, two trial decisions – Duncan Estate v. Bradley (1994), 161 A.R. 357; and McFetridge Estate v. Olds Aviation Ltd. (unreported, Edmonton, April 12, 1996) – have been rendered which offer interpretations of the Galand decision.

In this, the first of two articles on the Galand decision, the arguments raised in these three decisions are summarised. A second article, to be published in the next edition of this newsletter, will discuss the implications of these decisions for the calculation of damages in fatal accident actions.

Galand Estate v. Stewart

In Galand, the estate of the deceased based a claim for the “…value of the present capital loss of earning capacity of the deceased…” on sections 2 and 5 of Alberta’s Survival of Actions Act:

2. A cause of action vested in a person who dies after January 1, 1979, survives for the benefit of the estate….

5. If a cause of action survives under section 2, only those damages that resulted in actual financial loss to the deceased or his estate are recoverable… (emphasis added)

The defendants raised two substantive arguments against the existence of the plaintiff’s cause of action. First, they argued that a loss of earnings could not constitute an “actual financial loss,” as required under section 5; and, second, they questioned the policy of providing a “windfall” to persons who are not dependents, on the ground that such a provision was not consistent with tort law’s fundamental goal of compensation.

Actual Financial Loss

In Galand, Coté J.A. (with Belzil J.A. concurring) considered and rejected three versions of the defendant’s position concerning actual financial loss. First, he did not accept the argument that a loss of future earnings was not “actual” because it was necessarily “speculative” or “contingent.” He countered with the example of a fatal accident victim with no dependents who had a completely secure salary and employment, such as a tenured university professor. Second, he rejected the proposition that “actual” and “real” necessarily implied “present,” not “future.” Finally, he did not agree that s. 5 barred claims for “general damages,” such as losses of future earnings. In his words, “[h]ad the Legislature meant ‘special damages’, it would have said so” (at 407).

Hembroff J. made it clear in Duncan that he did not agree with the majority reasoning in Galand. In particular, he quoted Black’s Law Dictionary as defining “actual” to mean

“… having a valid objective existence, opposed to that which is merely theoretical or plausible; opposed to hypothetical or nominal…”

[Randolph Langley, in a paper entitled Wrongful Death Claims, prepared for the Legal Education Society of Alberta, notes, however, that Black’s definition of “Damages: actual damages” includes:

“… Synonymous with “compensatory damages” and with “general damages” (emphasis added, Black’s 6th Edition, at 390).]

Windfall Gain

Coté J.A. also rejected the argument that actions for loss of future earnings should be denied because they represented a windfall to the beneficiaries of the estate rather than compensation. First, he noted that in some circumstances an individual who was the beneficiary of an estate might not be a dependent under the Fatal Accidents Act. Such an individual would be deprived of part of his inheritance from the deceased if he could not make a claim based on the Survival of Actions Act. Second, he noted that if the deceased had lost an income-producing machine at the moment of death, there would have been no doubt that his estate was entitled to claim full compensation for destruction of that machine. Yet such compensation might also represent a windfall to his estate.

Again, Hembroff J. dissented, citing Madam Justice McLachlin’s argument, in a case involving a young girl who had a severely shortened life expectancy, (Toneguzzo-Norvell v. Burnaby Hospital [1994] 1 S.C.R. 114), that

“… the award for lost earning capacity will serve but one purpose: to enrich her heirs” (at 127, emphasis added).

Similarly, Hembroff J. concluded that the “..tragic loss of a son should not be the notional income producing machine that puts money, ‘windfall or otherwise’ into the hands of his parents” (at 83).

Comment

Justice Hembroff’s objections notwithstanding, Justice Coté’s decision concerning “actual financial loss” was enunciated sufficiently clearly that most lower courts will find they are forced to conclude that estates do have a cause of action for general damages – it is only the measure of damages (to be discussed in the next issue of this newsletter) which remains uncertain.

A similar conclusion must be reached with respect to the treatment of beneficiaries of the estate of a deceased who are not also dependents. Here, Justice Coté was also clear, that the estate’s claim is to survive.

The decision in Galand with respect to “windfall gains” was stated much less clearly, however. The only assistance which Justice Coté provided to the trial courts derived from his analogy between the earning capacity of Wayne Gretzky and that of an “income-producing machine;” and from his decision that a loss of earning capacity could be considered to be an actual financial loss.

Two conclusions seem possible from this ruling. The first is that compensation is to be awarded only in those cases in which the deceased had a well-established earnings stream. The second is that compensation is to be awarded in all cases in which it can be shown, on balance of probabilities, that the deceased would have been a productive member of society. (Justice Coté’s decision concerning actual financial damages would appear to preclude the conclusion that damages are never to be awarded.)

Of these possible interpretations, Justice Coté appears to prefer the former. The examples which he provides in support of his conclusion that a loss of earnings is an actual financial loss all concern situations in which the individual’s earning capacity was well established – see his examples concerning tenured professors and Wayne Gretzky. Furthermore, his apparent reluctance to award damages “…in the case of the death of young children without a job or other source of income…” (at 407) could reasonably be interpreted to result from the difficulty of calculating such damages.

To conclude, it appears that the estate will be able to claim damages for loss of earnings when the deceased had a well-established earnings stream. It is not yet known, however, where the line will be drawn between these cases and those in which no clear earnings pattern has been established. The Court will have an opportunity to clarify this issue later this year when it is scheduled to hear an appeal of Duncan.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

What is a “Discount Rate”?

by Christopher Bruce

This article first appeared in the spring 1996 issue of the Expert Witness.

Alberta is one of only four provinces in which the discount rate is not mandated. As I argued in Ontario’s 2 1/2% Solution (Canadian Bar Review, December 1982) this means that we are able to react much more flexibly to changes in the economic situation than are the six provinces whose rates are set by a central authority. Indeed, the superiority of Alberta’s approach is seen in the fact that whereas interest rates have varied significantly over the last 15 years, not one of the provinces with mandated rates has adjusted that rate.

Nevertheless, the lack of a mandated rate does carry the drawback that an onus is placed both on financial expert witnesses and on counsel to understand how the discount rate is determined and to identify whether economic forces have changed in such a way as to make previous assumptions about that rate obsolete. The purpose of this article will be to provide a basic explanation of what the discount rate is and of how it works. In a second article, I identify a number of alternative methods of forecasting the discount rate and use what is generally considered to be the preferred method to identify such a rate for Alberta.

Assume that a plaintiff will require dental work one year from now. If that work was carried out today, it would cost $1,040. The question which faces the legal system is: “How much does the plaintiff have to be compensated today, in order to ensure that he/she will have enough money to pay for this procedure one year from now?” The answer to this question depends, first, upon the effect of the rate of inflation on the cost of the procedure; and, second, upon the rate of interest at which the plaintiff can invest his/her award.

The effect of the rate of inflation is relatively straight forward. If, for example, the cost of dental procedures is expected to increase by 2.5 percent in the next year, this plaintiff will need $1,040 increased by 2.5 percent one year from now. That is, the amount required will be:

$1,040 + (2.5% x $1,040)
= (1.00 x $1,040) + (0.025 x $1,040)
= (1.00 + 0.025) x $1,040
= 1.025 x $1,040
= $1,066

In short, to find the inflated value one year from now, the current value (here, $1,040) is multiplied by 1 plus the rate of inflation (here, 1.025).

The second step is to determine how much has to be paid to the plaintiff today in order to ensure that he /she will have $1,066 one year from now. Assume for this purpose that the rate of interest which plaintiffs can expect to receive on secure investments is 6.6 percent per annum. It is intuitively clear that $1,000 invested at this rate will yield $1,066 (the desired amount) one year from now. Formally, this $1,000 figure, which is called the present discounted value or commuted value of $1,066, can be derived in the following way: Call the present discounted value $P. When $P is invested at 6.6 percent interest, we want it to yield $1,066. Hence,

$P + (6.6% x $P) = (1.00 x $P) + (0.066 x $P)
= (1.00 + 0.066) x $P
= 1.066 x $P
= $1,066

That is, we know that

1.066 x $P = $1,066

Therefore, to find $P, we need only divide both sides of this equation by 1.066, to obtain

$P = ($1,066 / 1.066)
= $1,000

Remembering that the $1,066 figure in this equation was found by increasing the current cost of the dental procedure, $1,040, by the rate of inflation, 2.5 percent, it is now seen that amount which must be paid to the plaintiff today, $P, may be obtained from the formula:

$P = $1040 x (1.025 / 1.066)
= $1,040 x (1.00 / 1.04)
= $1,000

What this set of calculations is intended to show is, first, that $P can be found by multiplying the current cost of the expense to be compensated, here $1,040, by (1 + inflation), here 1.025, divided by (1 + interest), here 1.066. Second, (1.025 divided by 1.066) can be replaced by (1.00 divided by 1.04). This 1.04 figure is known by economists as the real rate of interest or the discount rate. This is the figure which expert witnesses use to determine the present, or lump sum value of a future cost. It is called the real rate of interest because it was calculated by dividing 1.066 by 1.025; that is, (1.025/1.066) = 1.00/(1.066/1.025) = (1.00/1.04). Dividing (1 + interest) by (1 + inflation) in this way has the effect of “netting out” the impact of inflation from the observed, or nominal, interest rate, leaving only that element of interest payments which is independent of inflation – the “real” rate of interest.

Economists and other financial experts have used the real rate of interest to discount future losses because it has been less volatile than the nominal rate of interest. (The nominal rate increases and decreases with the rate of inflation while the underlying real rate remains stable.) Recently, however, the real rate has been almost as variable as the nominal rate. Nevertheless, because the courts have become accustomed to the use of the real rate, the Expert Witness will follow that convention.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Do Sons Follow their Fathers?

by Christopher Bruce

This article first appeared in the spring 1996 issue of the Expert Witness.

The forecasting of lost earning capacity becomes particularly difficult when it is a child who has been injured. In the absence of clear evidence to the contrary, the courts will generally assume that the child would have followed a course similar to that of his or her parents. A recent study provides evidence concerning the validity of this assumption.

Corak and Heisz (in Canadian Business Economics, Fall 1995) showed that the incomes of fathers were only weakly correlated with the incomes of their sons. For example, males whose fathers’ incomes were in the middle third of the income distribution were only slightly more likely to be in the middle third themselves than they were to be in the top or bottom third.

Nevertheless, having a father in the top 20 percent of the income distribution did impart an appreciable advantage. Thirty percent of the sons whose fathers were in that portion of the income distribution rose to that level themselves; whereas only 12 percent of the sons whose fathers were in the bottom 20 percent of the distribution rose to the top 20 percent.

On average, having a father in the top 20 percent of the income distribution increased a son’s income by 15 percent compared to sons whose fathers were in the middle of the distribution; and having a father in the middle 20 percent of the income distribution increased a son’s income by 15 percent compared to sons whose fathers were in the bottom 20 percent of the distribution.

In short, his father’s income appeared to have a significant influence on a boy’s income only if the father was either rich or poor. This finding is consistent with the observation from other Statistics Canada studies that there is a strong correlation between the educational levels of children and of their parents. The reason for this is that incomes do not vary strongly among educational levels except at high and low educational levels. For the majority of individuals, education has only a weak effect on income. It is only when education falls into the lowest levels that income drops significantly; and it is only when education rises to the university level that income rises significantly.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).

Loss of Earnings for Wrongful Confinement and Wrongful Sterilization: The Case of Leilani Muir

by Christopher Bruce

This article first appeared in the spring 1996 issue of the Expert Witness.

In Muir v. Alberta damages were awarded to the plaintiff on two grounds: first, that she was wrongfully confined, at the age of 10, in a home for the mentally defective; and, second, that while so confined, she was wrongfully sterilized. On the first of these claims, she was awarded $250,000 plus $115,500 interest for pain and suffering but was denied both aggravated damages and damages for loss of income. On the second claim, she was awarded $250,280 for pain and suffering and $125,000 for aggravated damages but was denied punitive damages.

Madam Justice Veit denied the claim for loss of earnings primarily on the ground that Ms. Muir had come from a dysfunctional family, leading her to suffer from severe emotional problems prior to her wrongful confinement. The confinement itself was found not to have exacerbated these problems.

Does this imply that all individuals in Ms. Muir’s situation will be denied damages for loss of earnings? We think not. Three sources of claims for lost earnings appear to have survived the decision in Muir.

  • First, if the plaintiff did not come from a dysfunctional family, a claim for loss of earnings could arise from the wrongful confinement.
  • Second, it might be argued that, had the plaintiff been placed in a foster home or group home for the care of emotionally disturbed children (possibilities which were canvassed by Madam Justice Veit), she would have overcome the effects of her dysfunctional upbringing. Hence, a loss of earnings would have arisen from the government’s failure to take advantage of one of these alternatives.
  • Finally, it is possible that a claim for loss of earnings could arise from the action for wrongful sterilization. Madam Justice Veit concluded that the “…sterilization had a catastrophic impact on Ms. Muir.” (Emphasis added, p. 59) She also accepted a psychologist’s opinion that sterilization can have “profound detrimental effects on … education…” (p. 46) and a psychiatrist’s testimony that the impact of sterilization on “…a young woman … would be hard to over-estimate.” (p. 38) On these bases, it could be argued that a wrongful sterilization had impaired the capacity to earn income.

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Christopher Bruce is the President of Economica and a Professor of Economics at the University of Calgary. He is also the author of Assessment of Personal Injury Damages (Butterworths, 2004).