Income Elasticities and Global Values of a Statistical Life

By W. Kip Viscusi, C. Masterman. Journal of Benefit-Cost Analysis, 2017

320 citations recorded by the source corpus.

Countries throughout the world use estimates of the value of a statistical life (VSL) to monetize fatality risks in benefit-cost analyses. However, the vast majority of countries lack reliable revealed preference or stated preference estimates of the VSL. This article proposes that the best way to calculate a population-average VSL for countries with insufficient or unreliable data is to transfer a base VSL from the United States calculated using labor market estimates from Census of Fatal Occupational Injuries data, coupled with adjustments for differences in income between the United States and the country of interest. This approach requires estimation of two critical inputs: a base U.S. VSL and the income elasticity of the VSL. Drawing upon previous meta-analyses that include adjustments for publication selection biases, we adopt a base VSL of $9.6 million. We utilize a sample of 953 VSL estimates from 68 labor market studies of the VSL covering fourteen lower-middle income to high income nations. We estimate the income elasticity of the VSL within the United States to be from 0.5 to 0.7 and to be just above 1.0 for non-U.S. countries. Quantile regression reveals that much of the disparity in income elasticities is attributable to income differences between the United States and other countries, as the income elasticity increases for lower income populations. Using income classifications from the World Bank, we calculate average VSLs in lower income, lower-middle income, upper-middle income, and upper income countries to be $107,000, $420,000, $1.2 million, and $6.4 million, respectively. We also present VSL estimates for all 189 countries for which World Bank income data are available, yielding a VSL range from $45,000 to $18.3 million.

Subfields: Economics and Econometrics, General Health Professions

View Paper: https://www.semanticscholar.org/paper/379cc4bc7b708b3d756118888f3573bf4609be14

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In Economics and Econometrics

  1. Liguo Lin
  2. P. Barwick
  3. Shanjun Li
  4. E. Zou

In General Health Professions

  1. Liguo Lin
  2. P. Barwick
  3. Shanjun Li
  4. E. Zou

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