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Complementarity and the Measurement of Individual Risk Tradeoffs: Accounting for Quantity and Quality of Life Effects

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  • Mary F. Evans
  • V. Kerry Smith

Abstract

This paper considers the factors responsible for differences with age in estimates of the wage compensation an individual requires to accept increased occupational fatality risk. We derive a relationship between the value of a statistical life (VSL) and the degree of complementarity between consumption and labor supplied when health status serves as a potential source of variation in this relationship. Our empirical analysis finds that variations in an individual's health status or quality of life and anticipated longevity threats lead to significant differences in the estimated wage/risk tradeoffs. We describe how extensions to the specification of hedonic wage models, including measures for quality of life and anticipated longevity threats, help to explain the diversity in past studies examining how the estimated wage-risk tradeoff changes with age.

Suggested Citation

  • Mary F. Evans & V. Kerry Smith, 2008. "Complementarity and the Measurement of Individual Risk Tradeoffs: Accounting for Quantity and Quality of Life Effects," NBER Working Papers 13722, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:13722
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    Cited by:

    1. Evans, Mary F. & Schaur, Georg, 2010. "A quantile estimation approach to identify income and age variation in the value of a statistical life," Journal of Environmental Economics and Management, Elsevier, vol. 59(3), pages 260-270, May.
    2. Maureen Cropper & James K. Hammitt & Lisa A. Robinson, 2011. "Valuing Mortality Risk Reductions: Progress and Challenges," Annual Review of Resource Economics, Annual Reviews, vol. 3(1), pages 313-336, October.
    3. V. Kerry Smith, 2008. "Risk Perceptions, Optimism, and Natural Hazards," Risk Analysis, John Wiley & Sons, vol. 28(6), pages 1763-1767, December.
    4. W. Viscusi & Elissa Gentry, 2015. "The value of a statistical life for transportation regulations: A test of the benefits transfer methodology," Journal of Risk and Uncertainty, Springer, vol. 51(1), pages 53-77, August.
    5. Tyler Kustra, 2017. "HIV/AIDS, Life Expectancy, and the Opportunity Cost Model of Civil War," Journal of Conflict Resolution, Peace Science Society (International), vol. 61(10), pages 2130-2157, November.
    6. Lisa A. Robinson & James K. Hammitt, 2016. "Valuing Reductions in Fatal Illness Risks: Implications of Recent Research," Health Economics, John Wiley & Sons, Ltd., vol. 25(8), pages 1039-1052, August.
    7. Jonathan M. Lee & Laura O. Taylor, 2019. "Randomized Safety Inspections and Risk Exposure on the Job: Quasi-experimental Estimates of the Value of a Statistical Life," American Economic Journal: Economic Policy, American Economic Association, vol. 11(4), pages 350-374, November.
    8. James O’Brien, 2018. "Age, autos, and the value of a statistical life," Journal of Risk and Uncertainty, Springer, vol. 57(1), pages 51-79, August.
    9. Stephen C. Newbold, 2011. "Valuing Health Risk Changes Using a Life-Cycle Consumption Framework," NCEE Working Paper Series 201103, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Apr 2011.
    10. V. Kerry Smith & Carol Mansfield, 2015. "The design of benefit–cost architecture for homeland security policy analysis," Chapters, in: Carol Mansfield & V. K. Smith (ed.), Benefit–Cost Analyses for Security Policies, chapter 2, pages 26-60, Edward Elgar Publishing.
    11. Mary Evans & V. Smith, 2010. "Measuring how risk tradeoffs adjust with income," Journal of Risk and Uncertainty, Springer, vol. 40(1), pages 33-55, February.

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    More about this item

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • J17 - Labor and Demographic Economics - - Demographic Economics - - - Value of Life; Foregone Income

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