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On the Measurement of Job Risk in Hedonic Wage Models

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  • Dan A. Black
  • Thomas K. Kniesner

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.

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File URL: http://yosemite.epa.gov/ee/epa/eed.nsf/WPNumber/2003-06/$File/2003-06.PDF
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Bibliographic Info

Paper provided by National Center for Environmental Economics, U.S. Environmental Protection Agency in its series NCEE Working Paper Series with number 200306.

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Length: 28 pages
Date of creation: Aug 2003
Date of revision: Aug 2003
Handle: RePEc:nev:wpaper:wp200306

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Keywords: hedonic wage equation; price of risk; implicit value of life; measurement error;

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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 1912-46, December.
  2. Lalive, Rafael, 2003. " Did We Overestimate the Value of Health?," Journal of Risk and Uncertainty, Springer, vol. 27(2), pages 171-93, October.
  3. 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.
  4. Ivar Ekeland & James Heckman & Lars Nesheim, 2002. "Identifying hedonic models," CeMMAP working papers CWP06/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. 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.
  6. 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 331-44, October.
  7. Aldy, Joseph E. & Viscusi, W. Kip, 2003. "The Value of Statistical Life: A Critical Review of Market Estimates throughout the World," Working paper 282, Regulation2point0.
  8. 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.
  9. 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.
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