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On the Measurement of Job Risk in Hedonic Wage Models

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  • Black, Dan A.
  • Kniesner, Thomas J.

Abstract

We examine the incidence, form, and research consequences of measurement error in measures of fatal injury risk in U.S. workplaces using both BLS and NIOSH data. These data are commonly used in hedonic wage studies. Despite the fact that each of our measures of job risk purport to measure the same thing – the risk of a fatality while on the job – the various measures of job risk are not highly correlated, with the maximum correlation being 0.53. Indeed, many of the estimated value of statistical life estimates are negative. We find that the National Institute of Safety and Health’s industry risk measure produces implicit value of life estimates most in line with both economic theory and the mode result for the existing literature than other risk measures examined. Because we find non-classical measurement error that differs across risk measures and is not independent of other regressors, innovative statistical procedures need be applied to obtain statistically improved estimates of wage-fatality risk tradeoffs.

Suggested Citation

  • Black, Dan A. & Kniesner, Thomas J., 2003. "On the Measurement of Job Risk in Hedonic Wage Models," National Center for Environmental Economics-NCEE Working Papers 280809, United States Environmental Protection Agency (EPA).
    • Handle: RePEc:ags:nceewp:280809
    DOI: 10.22004/ag.econ.280809
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    1. Griliches, Zvi, 1986. "Economic data issues," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 25, pages 1465-1514, Elsevier.
    2. J.J. Heckman & E.E. Leamer (ed.), 2001. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 5, number 5.
    3. Lalive, Rafael, 2003. "Did We Overestimate the Value of Health?," Journal of Risk and Uncertainty, Springer, vol. 27(2), pages 171-193, October.
    4. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    5. Kniesner, Thomas J & Leeth, John D, 1991. "Compensating Wage Differentials for Fatal Injury Risk in Australia, Japan, and the United States," Journal of Risk and Uncertainty, Springer, vol. 4(1), pages 75-90, January.
    6. Mark McClellan & Douglas Staiger, 1999. "The Quality of Health Care Providers," NBER Working Papers 7327, National Bureau of Economic Research, Inc.
    7. William T. Dickens & Brian A. Ross, 1984. "Consistent Estimation Using Data From More Than One Sample," NBER Technical Working Papers 0033, National Bureau of Economic Research, Inc.
    8. Ivar Ekeland & James J. Heckman & Lars Nesheim, 2002. "Identifying Hedonic Models," American Economic Review, American Economic Association, vol. 92(2), pages 304-309, May.
    9. Viscusi, W Kip, 1993. "The Value of Risks to Life and Health," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1912-1946, December.
    10. Thomas J. Kane & Cecilia Elena Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," NBER Working Papers 7235, National Bureau of Economic Research, Inc.
    11. Thomas J. Kane & Cecilia Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," Working Papers 798, Princeton University, Department of Economics, Industrial Relations Section..
    12. Hausman, Jerry A. & Newey, Whitney K. & Ichimura, Hidehiko & Powell, James L., 1991. "Identification and estimation of polynomial errors-in-variables models," Journal of Econometrics, Elsevier, vol. 50(3), pages 273-295, December.
    13. Mellow, Wesley & Sider, Hal, 1983. "Accuracy of Response in Labor Market Surveys: Evidence and Implications," Journal of Labor Economics, University of Chicago Press, vol. 1(4), pages 331-344, October.
    14. Viscusi, W Kip & Aldy, Joseph E, 2003. "The Value of a Statistical Life: A Critical Review of Market Estimates throughout the World," Journal of Risk and Uncertainty, Springer, vol. 27(1), pages 5-76, August.
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    More about this item

    Keywords

    Health Economics and Policy; Risk and Uncertainty;

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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