Tag: Contingencies

Doctors Are Not Experts on Life Expectancy

Posted on By economica

by David Strauss, PhD, FASA and Robert Shavelle, PhD

This article was originally published in the summer 1998 issue of the Expert Witness.

In personal injury cases, courts have traditionally relied on doctors for opinions on plaintiffs’ remaining life expectancy. We show here that such questions are really beyond the expertise of physicians, and that their testimony is readily challenged.

The analogy with life insurance is helpful. When applying for a life insurance policy you are first examined by a doctor, who assesses various risk factors. The results are transferred to the insurance company’s actuaries, who use the risk profile to assess your survival prospects. Thus both medical and statistical/actuarial skills are needed. Only a physician is qualified to appraise the individual, and only a statistician or actuary is qualified to turn the appraisal into a life expectancy.

Most physicians readily agree that they are not expert in actuarial issues. Nevertheless, pediatricians are still routinely asked to testify on the life expectancy of children with birth defects, while therapists or other medical specialists are consulted regarding adult accident victims. Their testimony on what are really statistical issues is often unfortunate. The following examples, with some modification, are drawn from actual cases.

“As a gerontologist I work with elderly persons. All the persons with cerebral palsy that I examine are at least fifty years old. Therefore I believe that this child with cerebral palsy will probably live to at least 50.”

We pass over this in silence.

“I believe that this child will certainly live to age 40, although probably not to age 50.”

It is, of course, absurd to say that any child – even one in perfect health – will “certainly” live to any age. Further, the probability that the age at death will fall in a narrow range such as 40-50 is bound to be quite low. The statement seems to confuse the life expectancy, which can often be estimated with some precision, and the actual age at death. The latter can rarely be predicted with any accuracy.

The annual mortality rate for children like the plaintiff is 1%. After 50 years, therefore 50% [ = 50 x 1%] of such children would have died. The median survival time is thus 50 additional years.”

There are two mistakes here. First, the math is wrong: in fact, 99% of the current survivors will survive one additional year, and therefore the proportion surviving 50 years is 61% (=.9950), not 50%. Second, the analysis ignores the dramatic increase in human mortality with age. As a result it gives wildly unrealistic long-term estimates, predicting, for example, that 37% of the population will survive to age 100.

* * *

Witnesses lacking statistical or actuarial training are frequently unable to define life expectancy, compute it in a simple case, or distinguish it from the median survival time. This may be exposed with a simple illustration.* If the witness cannot even explain what a life expectancy is, the testimony will lack credibility.

A physician’s opinion will be based either on a reading of the research literature or “on the basis of my clinical experience.” In the former approach, the plaintiff is matched to some group of individuals whose survival has been studied and reported. There are, for example, several studies of long-term survival for persons with cerebral palsy, traumatic brain injury, and spinal cord injury. Unfortunately such studies provide at best a crude estimate of life expectancy. The attorney can establish that:

  • The studies generally follow a cohort of persons who initially were of a given age and in a given condition. If the plaintiff is older and currently in this condition, it would be necessary to assume that cohort members surviving to the plaintiff’s age are still in that same condition. This assumption may be quite unreasonable, especially for young children who may have fair prospects for improvement.
  • Most studies provide survival curves, giving the fraction of persons in the cohort who survive to a given age. This will provide a median survival time only if the mortality is so high that 50% of the subjects die within the study period, and it rarely will permit the computation of a life expectancy.
  • The cohorts studied in literature are necessarily based on coarse classifications of one or two risk factors. Ironically, the clinician’s strength – the ability to make fine judgements about numerous patient characteristics – does not come into play.

It must therefore be recognized that published articles provide at best a rough approximation to a given plaintiff’s life expectancy. Indeed, some of the articles include a warning to this effect, a point that the opposing attorney may wish to emphasize.

Clinicians who instead rely on their experience for opinions are even more vulnerable. The lack of a solid basis can be revealed with questions such as:

  • How many patients closely resembling the plaintiff have you examined? [The answer will be at most a few dozen.]
  • Did you follow up on the survival or death of all of these patients? Give the specifics of your procedure. In particular, how did you follow the patients who moved to a different town or even to a different state? How did you ascertain who died? Where and in what form did you keep your records of the children’s survival time? Did you periodically reassess their functional levels during the follow up?
  • If you have been practicing for 20 years (say), how could you have ever observed a child surviving more than an additional 20 years? Does this lack affect your opinion? Why or why not?
  • Are you aware of the literature on statistical methods for estimating survival probabilities? Which methods did you use?

Such questions should make the limitations of the doctor’s expertise very clear.

Footnotes

* As an example, if 1/3 of members of a population will live exactly 2 more years, 1/3 will live exactly 3 more years, and 1/3 will live exactly 10 more years, then the life expectancy is (2 + 3 + 10)/3 = 5 years and the median is 3 years (the middle value). [Back to text]

References

1. Hutton JL, Cooke T, Pharoah POD. Life expectancy in children with cerebral palsy. British Medical Journal 1994; 309:431-435.

2. Chrichton JU, Mackinnon M, White CP. The life expectancy of persons with cerebral palsy. Developmental Medicine and Child Neurology 1995; 37:567-576.

3. Evans PM, Evans SJW, Alberman E. Cerebral palsy: Why we must plan for survival. Archives of Disease in Childhood 1990; 65:1329-1333.

4. Strauss DJ, Shavelle RM, Anderson TW. Life expectancy of children with cerebral palsy. Pediatric Neurology 1998; 18:143-149.

5. Strauss DJ, Shavelle RM. Life expectancy of adults with cerebral palsy. Developmental Medicine and Child Neurology, in press.

6. Roberts, AH. Severe Accidental Head Injury. London: Macmillan, 1979.

7. Strauss DJ, Shavelle RM. Long-term survival of children and adolescents after traumatic brain injury. Archives of Physical Medicine and Rehabilitation, in press.

8. DeVivo MJ, Stover SL. Long-term survival and causes of death. In: SL Stover, JA DeLisa, GG Whiteneck (Eds.), Spinal Cord Injury, pp. 289-316. Gaithersburg MD: Aspen, 1995.

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David Strauss, PhD, is a Fellow of the American Statistical Association and Professor of Statistics at the University of California, Riverside. He has frequently provided expert testimony on life expectancy in Britain, Canada, and the United States. He is director of the UC Riverside Life Expectancy Project, which specializes in the survival and life expectancy of persons with disabilities such as cerebral palsy and traumatic brain or spinal cord injuries.

Robert Shavelle, PhD, is a Visiting Professor at UC Riverside and a member of the Life Expectancy Project.

The Effect of Alcoholism on Earning Capacity

Posted on By economica

by Nicole MacPherson

This article was originally published in the summer 1998 issue of the Expert Witness.

It seems common sense to argue that alcoholics will experience reduced earning capacity. Thus, all else being equal, alcoholics will be eligible for lower damage awards than will other plaintiffs. What is often not clear, however, is how severe the effects of alcoholism will be.

The purpose of this article is to summarise the statistical literature concerning the effects of alcohol consumption on earnings and employment. One of the most important findings of this literature is that alcoholism has both direct and indirect effects on earnings. That is, there is evidence that alcoholics’ earnings are depressed both because alcoholism causes reduced labour productivity and because it discourages investments in “human capital” (e.g., education). Problem drinking is also found to increase unemployment.

Direct Effects

Alcoholism is considered to be a disease, and affects earnings as such. The physical and mental health problems associated with problem drinking have direct effects on labour market productivity and reliability. That is, sickness, hangover, late arrivals, extended lunch breaks, and early departures are some work characteristics that lead to reduced reliability and productivity. This in turn leads to lessened earnings and fewer promotions and raises.

Alcoholism can have other direct effects on wages, namely, alcoholism can affect career choices and stability. It is possible that alcoholics self-select into jobs that are less demanding, and therefore lower paying. The further advanced the state of alcoholism, the less the alcoholic is concerned about his or her career. Therefore, alcoholics tend to gravitate towards jobs that are not strenuous or taxing.

Indirect Effects

An important way in which alcoholism can affect earnings is through its effect on human capital characteristics. If the disease is advanced in youth, the alcoholic may not have the stamina to complete schooling, post-secondary or otherwise. This possible lack of education could lead to lower wages and selection into “dead-end” jobs. It is important to note that alcoholics may select into such jobs because of choice (the direct effect) or because of a lack of education (the indirect effect).

It is likely that alcoholics will have difficulties maintaining employment due to their condition. The reduced reliability discussed above can lead to job losses and decreased employability. The subsequent lack of work experience can lead to lower wages and earnings.

A significant indirect effect arises from familial and relationship problems associated with alcoholism. Alcoholics have higher divorce rates than non-alcoholics. As well, there is a higher probability of an abusive home life among problem drinkers. The emotional and mental strains arising from these factors can be expected to have negative impacts on productivity, and therefore earnings.

Empirical Evidence

Alcoholism’s effect on earnings has been the subject of a number of recent scholarly articles, which attempt to estimate this impact empirically. These studies indicate that, when direct and indirect effects are combined, alcoholics earn approximately 40 percent less than non-alcoholics. When human capital characteristics are controlled for, alcoholism alone leads to an 18 percent reduction in wages. That is, almost one half of the effect of alcoholism on earnings is due to lower human capital characteristics, namely education and work experience. Conversely, this implies that an alcoholic will earn approximately 18 percent less than will others with similar education levels and work histories.

It is significant to note that alcoholics earn less not only because of the effect heavy drinking has on human capital, but also because of the nature of alcoholism. A recent study found that alcoholics are more likely to be unemployed than alcoholics, and earn less when they are employed, even after controlling for the effect of education and experience. As the disease progresses, the earnings potential of the alcoholic lessens.

Alcoholism and employment have a causal relationship. Alcohol abuse negatively affects employment, but lack of work also affects drinking habits. Depression and stress resulting from unemployment can lead to increased reliance on alcohol and other drugs. Alcoholics can enter a vicious circle in that the longer an individual is unemployed, the more advanced the state of alcoholism. As the disease becomes more debilitating, becoming employed is increasingly difficult.

Recent medical research has found that moderate alcohol use leads to health benefits such as reduced risk of cardiovascular disease. Since healthy employees are productive employees, it is not unreasonable to suggest that moderate drinking can lead to greater productivity, and therefore higher earnings. In fact, there is evidence to support the hypothesis that alcohol and earnings have a parabolic relationship. That is, teetotalers and heavy drinkers both earn less than moderate drinkers. In fact, studies show that non-drinkers earn between eight and ten percent less than moderate drinkers. It has been estimated that wages peak for individuals consuming an average of 2.40 drinks per day, which is consistent with the medical literature. Individuals who do not drink at all may miss out on the health benefits of moderate drinking, as well as on social opportunities and networking to further their careers. Conversely, alcoholism deteriorates one’s state of health. As well, alcoholics may endure public shame because of their condition, and this can decrease the opportunities to advance their careers at social functions.

It is vital to realize that a future alcoholic may currently display only minor symptoms of problem drinking. Alcoholism is a disease, and when left untreated can have ravaging effects on the individual’s physical and mental states. These effects can have significant negative impacts on employment, productivity, and earnings.

The lost productivity and lowered earnings of alcoholics are significant costs that have merited recent attention in the economic literature. The alcoholic and his or her family suffers from lowered earnings. Employers and co-workers suffer from the alcoholic’s lost productivity. In addition to the well-known costs of alcoholism, illnesses, automobile accidents, and crime, problem drinking leads to decreased productivity and therefore, lower wages and earnings.

References

Berger, M.C., and Leigh, J.P. “The effect of alcohol use on wages”, Applied Economics, 1988, 20, 1343-51.

—. “Schooling, Self-Selection, and Health”, Journal of Human Resources, 1989, 24 (3), 433-455.

Boffetta, P., and Garfinkel, L. “Alcohol drinking and mortality among men enrolled in an American Cancer Society prospective study”, Epidemiology, 1990, 1, 342-348.

French, M.T., and Zarkin, G.A. “Is moderate alcohol use related to wages? Evidence from four worksites”, Journal of Health Economics, 1995, 14, 319-344.

Hamilton, V., and Hamilton, B. “Alcohol and earnings: Does drinking yield a wage premium?”, Canadian Journal of Economics, 1997, 30 (1), 135-151.

Kenkel, D.S. “Health Behaviour, Health Knowledge, and Schooling”, Journal of Political Economy, 1991, 99 (2), 287-305.

Mullahy, J., and Sindelar, J. “Gender Differences in Labor Market Effects of Alcoholism”, American Economic Review 1991, 81 (Papers and Proceedings), 161-165.

— “Alcoholism, Work, and Income”, Journal of Labor Economics, 1993, 11 (3), 494-520.

— “Employment, unemployment, and problem drinking”, Journal of Health Economics, 1996, 15, 409-434.

Shahaheh, B. “Drug and alcohol abuse in the workplace: Consequences and countermeasures”, International Labour Review, 1985, 124 (2), 207-223.

Zarkin, et. al., “Alcohol use and wages: new results from the National Household Survey on Drug Abuse”, Journal of Health Economics, 1998, 17, 53-58.

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Nicole MacPherson was a Master of Arts student at the University of Calgary. She wrote a thesis on the topic of “Alcohol, Gender, and Labour Market Outcomes.”

Application of Contingencies in the Pre-trial Period

Posted on By economica

by Scott Beesley

This article first appeared in the winter 1996 issue of the Expert Witness.

There is an interesting discussion regarding pre-trial “work life expectancy” continuing among members of the National Association of Forensic Economics (NAFE). We mention here two issues: survival probabilities (i.e. life expectancy) and employment contingencies.

First, there is debate over whether or not survival probabilities should be applied to pre-accident income in the pre-trial period, when the plaintiff has in fact lived to the date of trial. It can be argued that the accident “changed the world” completely, and that the post-accident fact of survival does not guarantee the plaintiff would have lived, had the accident not occurred. While I believe this argument is correct, some writers have gleefully pointed out that the application of survival probability to reduce expected pre-accident income invites plaintiff’s counsel to say to a defense economist “So, you are suggesting that the injury to my client has helped to keep him alive, are you?” In fact, this debate is virtually meaningless in almost all cases, because survival probabilities are so close to one, even near retirement age, that approximating them as equal to one in the pre-trial period is accurate. This is Economica’s conventional approach.

The contingencies applied to reflect the pre-accident risk of unemployment and disability are much more significant in the calculation of pre-trial loss. Again, we usually view those “from the date of the accident” in the sense that, if the plaintiff has worked steadily since the accident, we still assume they might have become disabled or unemployed, had the accident not occurred. This is clearly correct when the plaintiff no longer works in the same field, or does not work at all. The only awkward circumstance is when the plaintiff works in the same job or field (presumably with lower hours and earnings). The argument then is that the fact of no (further) disability or unemployment between the date of the accident and the date of trial provides additional information which implies that those contingencies should not be applied to pre-accident income. I disagree with this argument as it applies to disability, believing that any injury significant enough to reduce a plaintiff’s income also changes their lifestyle, and in particular would tend to make them more risk-averse at home and at work. The argument has merit as it applies to unemployment, however, since the time path of unemployment for a given company or industry is known better 3 or 6 years later, and market-wide risk of unemployment is the same pre-or post-accident. If an industry had grown rapidly between the date of accident and date of trial, and unemployment in the plaintiff’s area had fallen from 12 to 6 percent, the use of a 12 percent contingency would seem incorrect.

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Scott Beesley is a consultant with Economica and has a Master of Arts degree (in economics) from the University of British Columbia.