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The Impact of Race and Poverty on American Tort Awards

I stumbled on a 2003 study titled “ Race Poverty, and American Tort Awards,” written by economists Alex Tabarrok of George Mason University in Virginia and Eric Helland of Claremont-McKenna College in California published in the Journal of Legal Studies offering some interesting observations on how race and poverty levels impact tort awards. According to the study’s findings, which used data from successful personal injury cases from 1988-1997, as the poverty rates of minority plaintiffs increase so does their average tort award. It is not a one size fits all trend, however, and there are different levels of change seen among the different minority groups. For example, an increase of just one percentage point in poverty for African-American plaintiff results in a 3 percent increase in jury awards whereas the same increase in poverty percentage yields a 7 percent award increase for a Hispanic plaintiff. Interestingly enough, the exact opposite trend occurs when examining the poverty level of white plaintiffs, whose mean awards decrease with an increase in poverty rate percentage.

Just as the results of the study vary on the race of the plaintiff, the amount awarded fluctuates depending on the type of case in question. An increase in plaintiff poverty rates from 15-20% to over 25% results in an award jumping from $2.5 million to $4 million for product liability cases and from $1.8 million to $4 million for medical malpractice torts. It appears, however, that plaintiffs in auto cases do not reap the same benefits. Not only are their awards consistently lower than those of product liability and medical malpractice cases (which is hardly a surprise), but the awards seem unchanged by fluctuations in poverty level.

There is one final but important caveat to this study. While race and poverty level are important factors in the amount awarded in a successful tort case, they seem to have no bearing on whether plaintiff prevails on liability?

This is the part of the blog post where I analyze what this all means. But I have no idea. Still, it is interesting data.

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