The Impact of Using a Race-Neutral Model to Predict the Educational Attainment and Income of a Child in Personal Injury Litigation

Lawrence M. Spizman et al.

Journal of Forensic Economics2022https://doi.org/10.5085/jfe-485article
ABDC C
Weight
0.37

What the paper says

Abstract This paper examines the impact of using a model that excludes race and ethnicity on predicted educational attainment and income of a child in a personal injury legal matter. We use the updated ordered probit models with and without race and ethnic variables from Spizman and Kane (2020) and compare the earning capacity losses of a minor child based on each one. We perform this calculation for more than 3,000 combinations of the right-hand side variables for males and females separately, with more than 1,000 combinations each for White, Black, and Hispanic individuals. We find wide variation within each racial and ethnic group, with some subgroups benefiting and others being adversely impacted. The results of our analyses provide guidance to policymakers who might be interested in the real-world outcomes associated with legislation requiring that race and ethnicity not be considered when estimating damages in personal injury cases.

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https://doi.org/https://doi.org/10.5085/jfe-485

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@article{lawrence2022,
  title        = {{The Impact of Using a Race-Neutral Model to Predict the Educational Attainment and Income of a Child in Personal Injury Litigation}},
  author       = {Lawrence M. Spizman et al.},
  journal      = {Journal of Forensic Economics},
  year         = {2022},
  doi          = {https://doi.org/https://doi.org/10.5085/jfe-485},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.06 × 0.4 = 0.02
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.