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A quantile estimation approach to identify income and age variation in the value of a statistical life

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  • Evans, Mary F.
  • Schaur, Georg

Abstract

In theory, heterogeneity in individual characteristics translates into variation in the marginal willingness to pay for a mortality risk reduction. Two dimensions of heterogeneity, with respect to income and age, have recently received attention due to their policy relevance. We propose a quantile regression approach to simultaneously explore these two sources of heterogeneity and their interactions within the context of the hedonic wage model, the most common revealed preference approach for obtaining value of statistical life estimates. We illustrate the approach using data from the Health and Retirement Study (HRS). We find that the impact of age on the wage-risk tradeoff varies across the wage distribution. This result indicates important interactions between age and income heterogeneity. Thus, the conventional mean hedonic wage regression, even when the mean effect is allowed to vary with age, masks important heterogeneity.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jeeman:v:59:y:2010:i:3:p:260-270
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    Cited by:

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    2. Polat, Sezgin, 2013. "Wage Compensation for Risk: The Case of Turkey," GIAM Working Papers 13-11, Galatasaray University Economic Research Center.
    3. Gerking, Shelby & Dickie, Mark & Veronesi, Marcella, 2014. "Valuation of human health: An integrated model of willingness to pay for mortality and morbidity risk reductions," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 20-45.
    4. Christoph M. Rheinberger & Felix Schläpfer & Michael Lobsiger, 2017. "A Novel Approach to Estimating the Demand Value of Road Safety," Working Papers 2017.15, Fondazione Eni Enrico Mattei.
    5. James K. Hammitt & Fangli Geng & Xiaoqi Guo & Chris P. Nielsen, 2019. "Valuing mortality risk in China: Comparing stated-preference estimates from 2005 and 2016," Journal of Risk and Uncertainty, Springer, vol. 58(2), pages 167-186, June.
    6. W. Kip Viscusi, 2015. "The Role of Publication Selection Bias in Estimates of the Value of a Statistical Life," American Journal of Health Economics, University of Chicago Press, vol. 1(1), pages 27-52, Winter.
    7. Doucouliagos, Hristos & Stanley, T.D. & Viscusi, W. Kip, 2014. "Publication selection and the income elasticity of the value of a statistical life," Journal of Health Economics, Elsevier, vol. 33(C), pages 67-75.
    8. Hammitt James K. & Robinson Lisa A, 2011. "The Income Elasticity of the Value per Statistical Life: Transferring Estimates between High and Low Income Populations," Journal of Benefit-Cost Analysis, De Gruyter, vol. 2(1), pages 1-29, January.
    9. Hua Zan & Robert L. Scharff, 2017. "Regional Differences in the Value of Statistical Life," Journal of Consumer Policy, Springer, vol. 40(2), pages 157-176, June.
    10. Kochi, Ikuho & Taylor, Laura O., 2011. "Risk Heterogeneity and the Value of Reducing Fatal Risks: Further Market-Based Evidence," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 2(3), pages 1-28, August.
    11. 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.
    12. 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.
    13. Herrera-Araujo, Daniel & Rochaix, Lise, 2020. "Does the Value per Statistical Life vary with age or baseline health? Evidence from a compensating wage study in France," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    14. 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.
    15. Gentry, Elissa Philip & Viscusi, W. Kip, 2016. "The fatality and morbidity components of the value of statistical life," Journal of Health Economics, Elsevier, vol. 46(C), pages 90-99.
    16. 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.
    17. W. Viscusi, 2010. "The heterogeneity of the value of statistical life: Introduction and overview," Journal of Risk and Uncertainty, Springer, vol. 40(1), pages 1-13, February.
    18. N. Witvorapong & T. Komonpaisarn, 2020. "The Value of a Statistical Life in Thailand: Evidence from the Labour Market," Journal of Consumer Policy, Springer, vol. 43(3), pages 491-518, September.
    19. Ketcham, Jonathan & Kuminoff, Nicolai & Saha, Nirman, 2023. "Valuing Statistical Life Using Seniors' Medical Spending," RFF Working Paper Series 23-16, Resources for the Future.
    20. Gabriele Curci & Domenico Depalo & Alessandro Palma, 2023. "The Dirtier You Breathe, The Less Safe You Are. The Effect of Air Pollution on Work Accidents," CEIS Research Paper 554, Tor Vergata University, CEIS, revised 24 May 2023.
    21. Rheinberger, Christoph M. & Schläpfer, Felix & Lobsiger, Michael, 2018. "A novel approach to estimating the demand value of public safety," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 285-305.

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