This article first appeared in the summer 1996 issue of the Expert Witness.
In its recent decision in Pallos v. Insurance Corporation of British Columbia (1995, B.C.J. No. 2), the British Columbia Court of Appeal awarded $40,000 for “loss of earning capacity” to a plaintiff who had no “loss of earnings.” The basis of the claim was that, although the plaintiff had returned to his previous employment, at a salary commensurate with that earned prior to the accident, the injury had diminished his future job prospects.
Pallos raises an important issue which is often given less attention than it deserves in personal injury actions: how should the court deal with uncertainty concerning the course of the plaintiff’s future earnings stream? In Pallos the uncertainty was of an extreme form, as it was unclear whether the plaintiff would have sought alternative employment had he not been injured nor was it certain what effect the injury would have on the post-accident probability that he would be able to keep his job or to find another one.
Other cases present the courts with varying degrees of uncertainty. In this article, I consider four types of uncertainty, in increasing order of complexity. The fourth case represents the situation which was dealt with in Pallos.
At the lowest level of complexity, the court has determined what career path the plaintiff will follow (or would have followed) but is uncertain concerning factors specific to that career, such as the rate of growth of earnings, the level of fringe benefits to be paid, the probability of unemployment, or the age of retirement. This common form of uncertainty can be, and is usually, dealt with simply by using averages. Although different automobile mechanics may experience different rates of growth of earnings, for example, it is generally appropriate to assume that the plaintiff’s income would have experienced the average rate of growth of earnings, for mechanics with characteristics similar to those of the plaintiff (such as education, specialisation, and work experience).
At the second level of complexity, there is a dispute concerning the plaintiff’s career choice. Commonly, for example, the defendant will argue that an injured automobile mechanic should return to his previous employment (perhaps at a reduced capacity), whereas the plaintiff will argue that the plaintiff should retrain as a partsman. Often, this type of dispute can be resolved on the basis of an appeal to the facts. That is, it is often open to the court to argue that the facts indicate that one of the two (or more) courses of action is much more reasonable than the other. (The court might find, for example, that the plaintiff’s back injury is so severe that it is highly unlikely that he could resume his career as a mechanic.)
In the third situation, there are (or were) two or more careers open to the plaintiff, each of which is (or would have been) plausible. For example, it may be unclear whether the plaintiff would have taken a drafting diploma at a technical school or an engineering degree at university had she not been injured. The present, or lump-sum, value of the former would have been $700,000, whereas that of the latter would have been $1,100,000.
The court could employ the second approach identified above, and make a finding of fact concerning which of these streams the plaintiff would have followed. But the better course, I would suggest, is to weight each possibility by the probability that it would have occurred. This provides what is commonly referred to as a “weighted average” (or, technically, an “expected value”). For example, if it was felt that pre-accident there was a slightly higher probability that the plaintiff would have become a draftsperson than an engineer, the court might conclude that the probability of the former was 60 percent and that of the latter 40 percent. In this case, the weighted average of the two possible income streams would be:
Weighted average (pre)
= (0.60 x $700,000) + (0.40 x $1,100,000)
= $420,000 + $440,000
= $860,000
It is from this figure that the lump sum value of the post-accident income stream would be deducted in order to obtain the lump sum loss of future earnings.
The weighted average calculation, also referred to as the use of “simple probability,” has a long history of acceptance in Canadian courts. An early example is Bradenburg v. Ottawa Electric Railway (1909), 19 O.L.R. 34 at 36 (C.A.). Subsequent cases include MacDonell v. Maple Leaf Mills Ltd. (1972), 26 D.L.R. (3d) 106 at 109 (Alta. C.A.), Schrump v. Koot (1978), 18 O.R. (2d) 337 (C.A.) and Janiak v. Ippolito (1985), 16 D.L.R. (4th) 1 at 20 (S.C.C.). In the latter case the Supreme Court noted that “In assessing damages the court determines… what would have happened by estimating the chance of the relevant event occurring, which chance is then to be directly reflected in the amount of damages” (emphasis added).
Recent cases which apply this principle include Graham v. Rourke (1991), 74 D.L.R. (4th) 1 at 12-13 (Ont. C.A.) and Steenblok v. Funk (1990), 46 B.C.L.R. (2d) 133 (C.A.). Many other references, and a detailed discussion of related issues, can be found in Ken Cooper-Stephenson’s book Personal Injury Damages in Canada (2nd ed., Carswell, 1996), and I would like to acknowledge that the above citations were found in this text.
Use of the weighted average approach avoids a common problem in personal injury litigation – that the plaintiff may appear to be “better off” following the accident than before. For example, assume in the case above that the effect of the accident has been to increase the probability that the plaintiff will become a draftsperson from 60 percent to 80 percent – and decrease the probability that she will become an engineer from 40 percent to 20 percent. The defendant could argue that the plaintiff might have become a draftsperson before the accident and will now become an engineer after the accident, leaving her better off by ($1,100,000 – $700,000 =) $400,000.
The answer to this is that the defendant has ignored both the probability that the plaintiff would have become an engineer had the accident not occurred and the probability that she will become a draftsperson now that the accident has occurred. The best way to deal with this issue, we suggest, is for the court to weight each of the career opportunities by the probability that it would (will) occur and then to deduct the weighted average of the post-accident figures from that of the pre-accident. We already know in the case discussed above that the weighted average of the pre-accident earnings was $860,000. The comparable figure for the post-accident stream is:
Weighted average (post)
= (0.80 x $700,000) + (0.20 x $1,100,000)
= $560,000 + $220,000
= $780,000
Hence, the loss becomes ($860,000 – $780,000 =) $80,000. [Note: this calculation can readily be extended to cases in which there are three or four possible streams and to cases in which the numbers of streams pre- and post-accident are different.]
The final situation is that in which it is extremely difficult to attach probabilities to the possible future outcomes. This is the situation which was encountered in Pallos. There, the plaintiff had returned to his pre- accident employment, at an income which was similar to that which he had been earning prior to the accident. The court found that the nature of the plaintiff’s injuries was such that he would now have much greater difficulty obtaining employment with an alternative firm than he would have prior to the accident. What was unclear, however, were the probabilities that he would have sought alternative employment prior to the accident or that the firm would now lay him off, forcing him to seek alternative employment post- accident.
It might be possible to resolve this conundrum employing the weighted average approach; but the difficulties of obtaining appropriate probabilities make such a solution problematic. Implicitly, the two alternatives considered by the court were (i) to make no award; and (ii) to make a “fair assessment.” The B.C.C.A. chose the latter; Finch J.A. awarded $40,000 for what he called “loss of earning capacity.”
Although we sympathise with the approach taken by Mr. Justice Finch, we submit that it may be inferior to the weighted average approach. Given Mr. Pallos’ education and work experience, the number of opportunities realistically open to him had he left his current employer was limited. (Technically, the number may be unlimited, but most of his alternatives would have provided similar income levels.) Hence, the primary uncertainty to be resolved was the probability that he would have sought alternative employment. This is a probability which the courts in general could select, based upon the facts of the case. Similarly, the probability that a plaintiff like Mr. Pallos will be laid off from (or otherwise) leave his employer, post- accident, could also have been selected by the court. Although the selection of these probabilities may have to be based on subjective factors, I would suggest that the process of that selection would make the decision much more transparent and easier to translate to other cases.
This difficulty of translation has already become apparent. In Nelson v. Kanusa Construction et al. (1995, B.C.J. No. 958), a B.C. trial decision which followed Pallos, the plaintiff was awarded $50,000, also for “loss of earning capacity,” even though the award given to Ms. Nelson for loss of earnings appeared to have compensated her adequately.
Nevertheless, a substantial subset of cases may remain in which the plaintiff’s prospects are so uncertain that it is extremely difficult either to identify them all or to attach probabilities to them. In these cases, the Pallos approach – of providing a lump-sum to compensate the plaintiff for a loss of earning capacity – may be appropriate.
