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Ronen Avraham and Kimberly Yuracko, Torts and Discrimination, Law and Economic Research Paper No. E570 (2017), available at SSRN.

When plaintiffs suffer actionable injury, courts in the United States attempt to repair the harm by awarding compensatory damages that put victims in the position they would have been in but for the wrongs that they have suffered. Courts calculate an individualized measure of compensatory damages for each plaintiff. The damage measure not only includes plaintiff’s actual past expenses, but also, a plaintiff’s lost earning capacity, future pain and suffering, and future medical costs.  As a starting point for juries’ projections, courts allow forensic economists to introduce three types of government-generated statistical tables—life expectancy tables, work-life expectancy tables and average-wage tables. (P. 17.) All of these tables come in blended and non-blended versions. The non-blended editions disaggregate data by race and gender. For example, a non-blended table might tell you that a “white” girl born in 2014 has a life expectancy of 81.2 years, while a “black or African American” boy has an expectancy of only 72.5 years.1 Similarly, a non-blended table might suggest that a 16-year old white male has a longer work-life expectancy than a black female. (P. 26.)

Courts frequently, perhaps “routinely,” permit the use of non-blended statistical tables as a foundation for damage awards in tort and other claims, including even Title VII discrimination cases. (Pp. 15, 59.) Furthermore, as Avraham and Yuracko document, legislatures have also adopted statutes or pattern jury instructions which permit gender-based, and sometimes race-based calculations. (P. 16.)

The problems with using race and gender in damage calculations are many. Building on the work of Martha Chamallas and Jennifer Wriggins in The Measure of Injury: Race, Gender and Tort Law (2010),  and earlier works, Avraham and Yuracko argue that using gender and race based tables may well result in disparate damage awards, and not only reflect historical inequities, but perpetuate them. (P. 106.) Furthermore, they argue that these race and gender disparities may themselves create discriminatory incentives for care. Moreover, they find the explicit distinctions based on gender and race to be an embarrassment, presumably along the line of expressive harm (that welfare maximization values some lives above others). They suggest that the use of differentiated tables might be inaccurate and inefficient to boot. (Pp. 74-93.) Ultimately, the authors argue that “Courts should immediately stop using non-blended tables.”

The conclusion seems sound and the issue both important and practical. Courts should repair victims within a framework that incorporates other important social values like gender equity. The authors’ engagement with norms of both equality and efficiency—an area in which few U.S. torts scholars dare to tread—is also admirable. Avraham and Yuracko are at their best when they provide real-world examples of systems that seem to function without differentiation. Apparently in projected future earnings of minors and young adults—cases in which individualized earnings histories are unavailable–Israel has decided not to differentiate earnings potential by race, gender, origin or religion. (P. 127.) Moreover, as the authors note, government regulation does not distinguish based on race and gender in regulatory models. (P. 108.) Nor do insurer rating formulas provide for such distinctions. (P. 109.) And of course some legislatures and judges have rejected the use of non-blended tables in civil cases. Other authorities could be added.2

For all of the strength of their thoughtful work, Tort and Discrimination never really goes for the jugular. Although Avraham and Yuracko suggest that using race- and gender-specific statistics raises constitutional concerns, they never fully articulate the constitutional argument that a court should consider. And while they label the use of race- and gender- based tables “discriminatory,” they don’t establish what is wrongful about these group-based distinctions, something they could perhaps do by reference to doctrines like redlining or stereotyping. In addition, while they raise many empirical reasons to suggest courts and legislatures should be concerned about non-blended statistical measures–“the damages black women receive for future losses caused by bodily injury or wrongful death are lower than the damages their white male counterparts would receive,” (P. 4) –they don’t fully develop empirical evidence to support their claims. Before the final ink is dry on their work, this distinguished pair might think more carefully about arguing to the judges and legislators who can enact the changes they seek, not primarily to law and economics scholars who, even if they agree, can do nothing to change the rules.

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  1. See U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, Health, United States, 2015: With Special Feature on Racial and Ethnic Health Disparities 95 (2016) at Table 15. []
  2. See Ellen Bublick, China’s New Tort Law: The Promise of Reasonable Care, 13 Asian-Pac. L. & Pol’y J. 36 (2011) (Chinese tort law generally awards the decedent’s beneficiaries twenty times the average earnings in the decedent’s locality). []
Cite as: Ellen Bublick, How Much is Your Injury Worth? First Tell Me Your Race and Gender, JOTWELL (July 6, 2017) (reviewing Ronen Avraham and Kimberly Yuracko, Torts and Discrimination, Law and Economic Research Paper No. E570 (2017), available at SSRN), https://torts.jotwell.com/how-much-is-your-injury-worth-first-tell-me-your-race-and-gender/.