Journal of Risk and Uncertainty

, Volume 45, Issue 2, pp 115–133 | Cite as

Losers and losers: Some demographics of medical malpractice tort reforms

Article

Abstract

Our research examines how recent reforms have affected a key aspect of patients’ implicit insurance present in medical malpractice torts. Specifically, we estimate how non-economic damages caps affected pre-trial settlement speed and settlement amounts. Maximum entropy (most likely) quantile regressions emphasize that the post-reform settlement effects most informative for policy evaluation differ greatly from OLS (mean) estimates and clarify the conclusion emerging. In particular, the effect of the tort reform here can best be thought of as a 25% tax on the asset value of settlements that exempts settlements involving infants. The social welfare effects of tort reform are less clear than the asset reduction effects due to likely health state dependent utility.

Keywords

Medical malpractice Tort reform Texas closed claims Damage caps Quantile regression Maximum entropy 

JEL classification

C21 I18 K13 

References

  1. Abraham, K. S. (2001). The trouble with negligence. Vanderbilt Law Review, 54(3), 1187–1224.Google Scholar
  2. American Medical Association. (2003). Summary of Texas HB 4. Advocacy Resource Center.Google Scholar
  3. Andersen, S., Harrison, G. W., Lau, M. I., & Rutström, E. E. (2008). Eliciting risk and time preferences. Econometrica, 76(3), 583–618.CrossRefGoogle Scholar
  4. Armstrong, R. D., Frome, E. L., & Kung, D. S. (1979). Algorithm 79–01: A revised simplex algorithm for the absolute curve fitting problem. Communications in Statistics, Simulation and Computation, 8, 175–190.Google Scholar
  5. Avraham, R. (2007). An empirical study of the impact of tort reforms on medical malpractice settlement payments. The Journal of Legal Studies, 36(S2), S183–S229.CrossRefGoogle Scholar
  6. Bera, A. K., Galvao Jr., A. F. Montes-Rojas, G. V., & Park, S. Y. (2010). Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression. University of Illinois Working Paper.Google Scholar
  7. Calabresi, G. (1961). Some thoughts on risk distribution and the law of torts. Yale Law Journal, 70(4), 499–553.CrossRefGoogle Scholar
  8. Cox, D. R. (1972). Regression models and life-tables (with discussion). Journal of the Royal Statistical Society, Series B, 34, 187–220.Google Scholar
  9. Crawford, V. P. (1982). Compulsory arbitration, arbitral risk and negotiated settlements: A case study in bargaining under imperfect information. The Review of Economic Studies, 49(1), 69–82.CrossRefGoogle Scholar
  10. Danzon, P. M. (1985). Medical malpractice. Cambridge: Harvard University Press.Google Scholar
  11. Danzon, P. M., Pauly, M. V., & Kington, R. S. (1990). The effects of malpractice litigation on physicians’ fees and incomes. American Economic Review Papers and Proceedings, 80, 122–127.Google Scholar
  12. Donohue, J. J., & Ho, D. E. (2007). The impact of damage caps on malpractice claims: Randomization inferences with difference-in-differences. Journal of Empirical Legal Studies, 4(1), 69–102.CrossRefGoogle Scholar
  13. Friedson, A. I. (2012). Medical malpractice damage caps and the price of medical procedures. Unpublished Manuscript.Google Scholar
  14. Golan, A. (2006). Information and entropy econometrics—a review and synthesis. Foundations and Trends in Econometrics, 2(1–2).Google Scholar
  15. Halek, M., & Eisenhauer, J. G. (2001). Demography of risk aversion. The Journal of Risk and Insurance, 68(1), 1–24.CrossRefGoogle Scholar
  16. Hersch, J., O’Connell, J., & Viscusi, W. K. (2007). An empirical assessment of early offer reform for medical malpractice. The Journal of Legal Studies, 36(S2), S231–S256.CrossRefGoogle Scholar
  17. Kessler, D. P. (2011). Evaluating the medical malpractice system and options for reform. Journal of Economic Perspectives, 25(2), 93–110.CrossRefGoogle Scholar
  18. Kniesner, T. J., Viscusi, W. K., & Ziliak, J. P. (2010). Policy relevant heterogeneity in the value of a statistical life: New evidence from panel data quantile regressions. Journal of Risk and Uncertainty, 40(1), 15–32.CrossRefGoogle Scholar
  19. Lakdawalla, D. N., & Seabury, S. A. (2009). The welfare effects of medical malpractice liability. National Bureau of Economic Research Working Paper 15383.Google Scholar
  20. Lin, D. Y., & Wei, L. J. (1989). The robust inference for the Cox proportional hazards model. Journal of the American Statistical Association, 84, 1074–1078.CrossRefGoogle Scholar
  21. Mello, M. M., Chandra, A., Gawande, A. A., & Studdert, D. M. (2010). National costs of the medical liability system. Health Affairs, 29(9), 1569–1577.CrossRefGoogle Scholar
  22. Shavell, S. (1978). Theoretical issues in medical malpractice. In S. Rottenberg (Ed.), The economics of medical malpractice. Washington, DC: American Enterprise Institute for Public Policy Research.Google Scholar
  23. Sloan, F. A., & Chepke, L. M. (2008). Medical malpractice. Cambridge: The MIT Press.Google Scholar
  24. Viscusi, W. K. (1988). Product liability litigation with risk aversion. The Journal of Legal Studies, 17(1), 101–121.CrossRefGoogle Scholar
  25. Viscusi, W. K., & Born, P. H. (2005). Damages caps, insurability, and the performance of medical malpractice insurance. Journal of Risk and Uncertainty, 72(1), 23–43.Google Scholar
  26. Viscusi, W. K., & Evans, W. N. (1990). Utility functions that depend on health status: Estimates and economic implications. American Economic Review, 80(3), 353–374.Google Scholar
  27. Zeckhauser, R., & Nichols, A. L. (1978). Lessons from the economics of safety. In S. Rottenberg (Ed.), The economics of medical malpractice. Washington, DC: American Enterprise Institute for Public Policy Research.Google Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of Colorado DenverDenverUSA
  2. 2.Center for Policy Research and Department of EconomicsSyracuse UniversitySyracuseUSA
  3. 3.Department of EconomicsClaremont Graduate UniversityClaremontUSA
  4. 4.IZABonnGermany
  5. 5.Maxwell School of Syracuse UniversitySyracuseUSA

Personalised recommendations