Wednesday, September 18, 2013
Herbert M. Kritzer, Guangya Liu, and Neil Vidmar have posted on SSRN their article An Exploration of Non-Economic Damages In Civil Jury Awards. This article is forthcoming in William & Mary Law Review.
Using three primary data sources plus three supplemental sources discussed in an appendix, this paper examines how well non-economic damages could be predicted by economic damages and at how the ratio of non-economic damages to economic damages changed as the magnitude of the economic damages awarded by juries increased. We found a mixture of consistent and inconsistent patterns across our various datasets. One fairly consistent pattern was the tendency for the ratio of non-economic to economic damages to decline as the amount of economic damages increased. Moreover, the variability of the ratio also tended to decline as the amount of economic damages increased. We found less consistency in our simple regression models where we predicted the log of noneconomic damages from the log of economic damages. In all of those models, the slopes of the fitted line were positive, but the slopes and the measures of fit (r2) varied from dataset to dataset, and among type of case within those datasets with multiple case types. Also, where we had the same type of case across datasets, we found variation in the fit and slope. With two of the datasets we were able to extend our regression models with regard to medical malpractice cases. Using the RAND jury study from 1995-99 we were able to separate out California’s medical malpractice cases which were governed by the MICRA cap on noneconomic damages from the cases coming from five other states included in the study. We found that MICRA dampened the relationship between economic and non-economic damages. Using the data we coded from on Cook County, Illinois jury verdicts, we were able to expand our regression model to include the NAIC severity index plus the gender and age of the plaintiff. We found no evidence that the two demographic variables systematically influenced the amount of non-economic damages, but the severity of injury did make a difference. Most importantly, we found that the severity of the injury conditioned the relationship between economic and non-economic damages.