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Evaluating Permanent Disability Ratings Using Empirical Data on Earnings Losses

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  • Jayanta Bhattacharya
  • Frank Neuhauser
  • Robert T. Reville
  • Seth A. Seabury

Abstract

Workers' compensation systems are typically designed to assign higher permanent disability benefits to workers with more severe disabilities. However, little or no scientific work exists to guide the design of ratings systems to properly account for the amount of earnings power lost due to disability. In this article, we examine the effectiveness of disability ratings using matched administrative data on ratings and earnings for a large, representative sample of permanent disability claimants in California. We find that while workers with higher ratings do experience larger earnings losses on average, there are large and persistent differences in average earnings losses for similarly rated impairments in different parts of the body. We then explore how adjusting permanent disability ratings to reflect cross‐impairment differences in earnings losses can affect the equity of permanent disability benefits. Adjusting disability ratings to account for typical earnings losses reduces cross‐impairment differences substantially. The adjusted ratings result in a more equitable distribution of disability benefits across workers with different impairments.

Suggested Citation

  • Jayanta Bhattacharya & Frank Neuhauser & Robert T. Reville & Seth A. Seabury, 2010. "Evaluating Permanent Disability Ratings Using Empirical Data on Earnings Losses," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(1), pages 231-260, March.
  • Handle: RePEc:bla:jrinsu:v:77:y:2010:i:1:p:231-260
    DOI: 10.1111/j.1539-6975.2009.01343.x
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    References listed on IDEAS

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    1. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    2. Boden, Leslie I, 1992. "Dispute Resolution in Workers' Compensation," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 493-502, August.
    3. Krueger, Alan B., 1990. "Incentive effects of workers' compensation insurance," Journal of Public Economics, Elsevier, vol. 41(1), pages 73-99, February.
    4. Robert T. Reville & Robert F. Schoeni, 2001. "Disability from Injuries at Work: The Effects on Earnings and Employment," Working Papers 01-08, RAND Corporation.
    5. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
    6. Guido W. Imbens & Donald B. Rubin & Bruce I. Sacerdote, 2001. "Estimating the Effect of Unearned Income on Labor Earnings, Savings, and Consumption: Evidence from a Survey of Lottery Players," American Economic Review, American Economic Association, vol. 91(4), pages 778-794, September.
    7. Robert T. Reville & Robert F. Schoeni, 2001. "Disability from Injuries at Work The Effects on Earnings and Employment," Working Papers DRU-2554, RAND Corporation.
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