Journal of Risk and Uncertainty

, Volume 40, Issue 1, pp 15–31 | Cite as

Policy relevant heterogeneity in the value of statistical life: New evidence from panel data quantile regressions

  • Thomas J. KniesnerEmail author
  • W. Kip Viscusi
  • James P. Ziliak


We examine differences in the value of statistical life (VSL) across potential wage levels in panel data using quantile regressions with intercept heterogeneity. Latent heterogeneity is econometrically important and affects the estimated VSL. Our findings indicate that a reasonable average cost per expected life saved cut-off for health and safety regulations is $7 million to $8 million per life saved, but the VSL varies considerably across the labor force. Our results reconcile the previous discrepancies between hedonic VSL estimates and the values implied by theories linked to the coefficient of relative risk aversion. Because the VSL varies elastically with income, regulatory agencies should regularly update the VSL used in benefit assessments, increasing the VSL proportionally with changes in income over time.


Value of statistical life VSL Quantile regression Panel data Fixed effects PSID Fatality risk CFOI 
JEL Classification C23 I10 J17 J28 K00 


  1. Aldy, J. E. & Viscusi, W. K. (2008). Adjusting the value of a statistical life for age and cohort effects. Review of Economics and Statistics, 90(3), 573–581.CrossRefGoogle Scholar
  2. Baker, R., Chilton, S., Jones-Lee, M., & Metcalf, H. (2008). Valuing lives equally: Defensible premise or unwarranted compromise? Journal of Risk and Uncertainty, 36(2), 125–138.CrossRefGoogle Scholar
  3. Black, D. A. & Kniesner, T. J. (2003). On the measurement of job risk in hedonic wage models. Journal of Risk and Uncertainty, 27(3), 205–220.CrossRefGoogle Scholar
  4. Chetty, R. (2006). A new method of estimating risk aversion. The American Economic Review, 96(5), 1821–1834.CrossRefGoogle Scholar
  5. Chetty, R. (2009). The simple economics of salience and taxation. National Bureau of Economic Research Working Paper Series, No. 15246.Google Scholar
  6. Dorsey, S. & Walzer, N. (1983). Workers’ compensation, job hazards, and wages. Industrial and Labor Relations Review, 36(4), 642–654.CrossRefGoogle Scholar
  7. Eeckhoudt, L. R. & Hammitt, J. K. (2001). Background risks and the value of a statistical life. Journal of Risk and Uncertainty, 23(3), 261–279.CrossRefGoogle Scholar
  8. Evans, M. F., & Smith, V. K. (2010). Measuring how risk tradeoffs adjust with income. Journal of Risk and Uncertainty, 40(1).Google Scholar
  9. Graham, J. D. (2008). Saving lives through administrative law and economics. University of Pennsylvania Law Review, 157(2), 395–540.Google Scholar
  10. Harris, J. E. (1979). Pricing rules for hospitals. The Bell Journal of Economics, 10(1), 224–243.CrossRefGoogle Scholar
  11. Kaplow, L. (2005). The value of a statistical life and the coefficient of relative risk aversion. Journal of Risk and Uncertainty, 31(1), 23–34.CrossRefGoogle Scholar
  12. Kniesner, T. J. & Ziliak, J. P. (2002). Tax reform and automatic stabilization. The American Economic Review, 92(3), 590–612.Google Scholar
  13. Kniesner, T. J., Viscusi, W. K., Woock, C., & Ziliak, J. P. (2008). The value of a statistical life: Evidence from panel data. Syracuse, NY, Syracuse University.
  14. Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74–89.CrossRefGoogle Scholar
  15. Lamarche, C. (2006). Robust penalized quantile regression estimation for panel data. Norman, Oklahoma, University of Oklahoma. Department of Economics.
  16. Leigh, J. P. & Folsom, R. N. (1984). Estimates of the value of accident avoidance at the job depend on the concavity of the equalizing differences curve. Quarterly Review of Economics and Business, 24(1), 55–66.Google Scholar
  17. Manski, C. F. (2009). When consensus choice dominates individualism: Jensen’s inequality and collective decisions under uncertainty. National Bureau of Economic Research Working Paper Series, No. 15172.Google Scholar
  18. Mellow, W. & Sider, H. (1983). Accuracy of response in labor market surveys: evidence and implications. Journal of Labor Economics, 1(4), 331–344.CrossRefGoogle Scholar
  19. Olson, C. A. (1981). An analysis of wage differentials received by workers on dangerous jobs. The Journal of Human Resources, 16(2), 167–185.CrossRefGoogle Scholar
  20. U.S. Bureau of Labor Statistics. (2009). Employed persons by detailed industry and occupation for 1993-2001, Current Population Survey.Google Scholar
  21. U.S. Department of Transportation, Office of the Assistant Secretary for Transportation Policy. (2005). Revised departmental guidance: Treatment of the value of preventing fatalities and injuries in preparing economic analyses. Washington, DC.Google Scholar
  22. U.S. Office of Management and Budget. (2003). OMB CIRCULAR A-4, Regulatory Analysis (Rep. No. A-4). Washington, DC.Google Scholar
  23. Viscusi, W. K. (1981). Occupational safety and health regulation: Its impact and policy alternatives. In J. P. Crecine (Ed.), Research in Public Policy Analysis and Management (Vol. 2, pp. 281–299). Greenwich, CT: JAI Press.Google Scholar
  24. Viscusi, W. K. & Evans, W. N. (1990). Utility functions that depend on health status: estimates and economic implications. The American Economic Review, 80(3), 353–374.Google Scholar
  25. Viscusi, W. K. (1993). The value of risks to life and health. Journal of Economic Literature, 31, 1912–1946.Google Scholar
  26. Viscusi, W. K. & Aldy, J. E. (2003). The value of a statistical life: A critical review of market estimates throughout the world. Journal of Risk and Uncertainty, 27(1), 5–76.CrossRefGoogle Scholar
  27. Viscusi, W. K. (2004). The value of life: Estimates with risks by occupation and industry. Economic Inquiry, 42(1), 29–48.CrossRefGoogle Scholar
  28. Viscusi, W. K. (2009). Valuing risks of death from terrorism and natural disasters. Journal of Risk and Uncertainty, 38(3), 191–213.CrossRefGoogle Scholar
  29. Ziliak, J. P., & Kniesner, T. J. (1998). The importance of sample attrition in life-cycle labor supply estimation. Journal of Human Resources, 33(2), 507–530.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Thomas J. Kniesner
    • 1
    • 2
    Email author
  • W. Kip Viscusi
    • 3
  • James P. Ziliak
    • 4
  1. 1.Senior Research Associate, Center for Policy ResearchSyracuse UniversitySyracuseUSA
  2. 2.IZABonnGermany
  3. 3.University Distinguished Professor of Law, Economics, and ManagementVanderbilt UniversityNashvilleUSA
  4. 4.Carol Martin Gatton Chair in Microeconomics, Center for Poverty ResearchUniversity of KentuckyLexingtonUSA

Personalised recommendations