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The Income Elasticity of the Value per Statistical Life: Transferring Estimates between High and Low Income Populations

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  • Hammitt James K.

    (Harvard University (Center for Risk Analysis) and Toulouse School of Economics (LERNA-INRA))

  • Robinson Lisa A

    (Independent Consultant)

Abstract

The income elasticity of the value per statistical life (VSL) is an important parameter for policy analysis. Mortality risk reductions often dominate the quantified benefits of environmental and other policies, and estimates of their value are frequently transferred across countries with significantly different income levels. U.S. regulatory agencies typically assume that a 1.0 percent change in real income over time will lead to a 0.4 to 0.6 percent change in the VSL. While elasticities within this range are supported by substantial research, they appear nonsensical if applied to populations with significantly smaller incomes. When transferring values between high and lower income countries, analysts often instead assume an elasticity of 1.0, but the resulting VSL estimates appear large in comparison to income. Elasticities greater than 1.0 are supported by research on the relationship between long-term economic growth and the VSL, by cross-country comparisons, and by new research that estimates the VSL by income quantile. Caution is needed when applying these higher elasticities, however, because the resulting VSLs appear smaller than expected future earnings or consumption in some cases, contrary to theory. In addition to indicating the need for more research, this comparison suggests that, in the interim, VSL estimates should be bounded below by estimates of future income or consumption.

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Bibliographic Info

Article provided by De Gruyter in its journal Journal of Benefit-Cost Analysis.

Volume (Year): 2 (2011)
Issue (Month): 1 (January)
Pages: 1-29

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Handle: RePEc:bpj:jbcacn:v:2:y:2011:i:1:n:1

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Cited by:
  1. Cropper, Maureen & Hammitt, James K. & Robinson, Lisa A., 2011. "Valuing Mortality Risk Reductions: Progress and Challenges," Discussion Papers dp-11-10, Resources For the Future.
  2. Hammitt, James & Roman, Henry & Stieb, David & Walsh, Tyra, 2012. "Expert Elicitation of the Value per Statistical Life in an Air Pollution Context," TSE Working Papers 12-290, Toulouse School of Economics (TSE).
  3. Andersson, Henrik, 2012. "Consistency in preferences for road safety: An analysis of precautionary and stated behavior," TSE Working Papers 12-359, Toulouse School of Economics (TSE).
  4. Hultkrantz, Lars & Svensson, Mikael, 2012. "A Comparison of Benefit Cost and Cost Utility Analysis in Practice: Divergent Policies in Sweden," Karlstad University Working Papers in Economics 1, Department of Economics, Karlstad University.
  5. Gianmarco León & Edward Miguel, 2013. "Transportation Choices and the Value of Statistical Life," NBER Working Papers 19494, National Bureau of Economic Research, Inc.
  6. Ian W.H. Parry & Jon Strand, 2011. "International Fuel Tax Assessment," IMF Working Papers 11/168, International Monetary Fund.
  7. Ian W.H. Parry, 2011. "Reforming the Tax System to Promote Environmental Objectives," IMF Working Papers 11/124, International Monetary Fund.
  8. Henrik Andersson & James Hammitt & Gunnar Lindberg & Kristian Sundström, 2013. "Willingness to Pay and Sensitivity to Time Framing: A Theoretical Analysis and an Application on Car Safety," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 56(3), pages 437-456, November.
  9. 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.
  10. Hammitt, James & Haninger, Kevin, 2011. "Valuing Morbidity Risk: Willingness to Pay per Quality-Adjusted Life Year," LERNA Working Papers 11.09.343, LERNA, University of Toulouse.

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