In a recent article Havrilesky (1993) argues against applying the hedonic damages concept to wrongful death and injury cases. The purpose of this paper is to critique his arguments. An examination of each of the seven points shows that none are appropriate. This analysis follows the same order and is under the same headings as Havrilesky's analysis. The conclusion section is added to summarize the paper.
Havrilesky argues in this section that since the estimated value of an anonymous or statistical person is not the same as the value that an individual places on his or her own life, the use of the value of an anonymous person in litigation is incorrect. The premise of the argument is true and not controversial. There is a difference between the estimated value of an anonymous person's life and the value that an individual places on his or her own life. The conclusion that the value of an anonymous person's life is not useful in litigation does not, however, necessarily follow from that premise.
Obviously, the interpretation of what the empirical value of life studies are estimating is crucial. Begin with the example provided by Havrilesky: a group of 1000 workers accept a job which carries an extra risk of one death in 1000 per year and receives a wage premium of $3000 per worker per year as a result. Havrilesky then states that
it is sometimes said that because the aggregate compensation for risk for the group of 1000 is $3 million, they value the loss of an anonymous one of their number at $3 million. (p.94)
The first task is to show that there is wide-spread agreement in the literature that the group in this example places a value of $3 million on the life of an anonymous member of the group. This agreement allows the removal of the qualifier "it is sometimes said."
The following statments by Viscusi (1990) are examples of how the estimates are interpreted:
In a competitive market, the extra wage premium that workers receive for risk will reflect their attitudes towards bearing risk. The observed risk-dollar tradeoff can then be used to calculate the implicit value oflife or injury.
The most recent evidence using the newly available data on death risks developed by the National Institute of Occupational Safety and Health indicates that the average blue-collar worker receives an extra $600 in wage compensation for bearing an average death risk of 1110,000. These results correspond to an implicit value per statistical death of $6 million. (p. 8)
Fisher, Violette and Chestnut (1989) provide a similar example,
the value of a statistical life represents what the whole group is willing to pay for reducing each member's risk by a small amount. For example, if each of 100,000 persons is willing to pay $20 for a reduction in risk from 3 deaths per 100,000 to 1 death per 100,000 the total WTP is $2,000,000 and the value per statistical life is $1 million (with 2 lives saved). (p. 89)
Havrilesky (1992) states
Since the aggregate compensation for risk for the group of 1000 is $3 million, they, as a community, value the loss of an anonymous one of their numbers at $3 million. (p. 2)
Miller (1990) states
Sixty-seven analyses have estimated the value of a statistical life, generally from estimates of how much people pay for small changes in their survival probabilities. (p. 17)
These statements reflect the consensus opinion that the studies estimate the value that society, or a group in society, places on an anonymous or statistical person.
Havrilesky then makes two points concerning the calculation of the aggregate compensation. The first point is that
this type of group evaluation of an anonymous life is not necessary in studies of the net benefits of actions which would alter the small risks imposed on a designated group of workers or consumers. (p. 94)
Technically this may be true. Consider an action which will affect 1000 workers, cost $3 million and will reduce the probability of death by 1110,000. The cost of implementation for each worker is $300. Then, if the benefit to each worker of the reduced probability to death by 1/10,000 is greater than $300 there is a net benefit. Thus, the "group evaluation of an anonymous life" is not calculated to test if there is a net benefit. However, this reasoning is equivalent to the reasoning that if the aggregate benefit to the workers is greater than $3 million there is a net benefit. So, although it is not necessary to calculate the "group evaluation of the value of an anonymous life" the reasoning is equivalent.
Dr. Gary R. Albrecht has more than 25 years of experience specializing in Economic Forecasting and Forensic Economics. The Director of Econometric Modeling at the University of Kansas, his research has been published in the Journal of Forensic Economics, Journal of Legal Economics, Trial Briefs, and The Earnings Analyst.
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