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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 Bureau of Labor Statistics and National Intitute of Occupational Safety and Health data. Of the various measures examined the NIOSH industry risk measure produces implicit value of life estimates most in line with both economic theory and the mode result for the existing literature. 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. Copyright 2003 by Kluwer Academic Publishers

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  • Black, Dan A & Kniesner, Thomas J, 2003. "On the Measurement of Job Risk in Hedonic Wage Models," Journal of Risk and Uncertainty, Springer, vol. 27(3), pages 205-220, December.
    • Handle: RePEc:kap:jrisku:v:27:y:2003:i:3:p:205-20
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    1. 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.
    2. 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.
    3. J.J. Heckman & E.E. Leamer (ed.), 2001. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 5, number 5.
    4. Lalive, Rafael, 2003. "Did We Overestimate the Value of Health?," Journal of Risk and Uncertainty, Springer, vol. 27(2), pages 171-193, October.
    5. 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.
    6. 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.
    7. Mark McClellan & Douglas Staiger, 1999. "The Quality of Health Care Providers," NBER Working Papers 7327, 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. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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..
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    JEL classification:

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

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