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Best Estimate Selection Bias in the Value of a Statistical Life

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  • Viscusi, W. Kip

Abstract

Selection of the best estimates of economic parameters frequently relies on the “best estimates†or a meta-analysis of the “best set†of parameter estimates from the literature. Using an all-set dataset consisting of all reported estimates of the value of a statistical life (VSL) as well as a best-set sample of the best estimates from these studies, this article estimates statistically significant publication selection biases in each case. Biases are much greater for the best-set sample, as one might expect, given the subjective nature of the best-set selection process. For the all-set sample, the mean bias-corrected estimate of the VSL for the preferred specification is $8.1 million for the whole sample and $11.4 million based on the CFOI data, while for the best-set results, the whole sample value is $3.5 million, and the CFOI data estimate is $4.4 million. Previous estimates of huge publication selection biases in the VSL estimates are attributable to these studies’ reliance on best-set samples.

Suggested Citation

  • Viscusi, W. Kip, 2018. "Best Estimate Selection Bias in the Value of a Statistical Life," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 9(2), pages 205-246, July.
    • Handle: RePEc:cup:jbcoan:v:9:y:2018:i:02:p:205-246_00
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    Cited by:

    1. Alex Hollingsworth & Krzysztof Karbownik & Melissa A. Thomasson & Anthony Wray, 2022. "The Gift of a Lifetime: The Hospital, Modern Medicine, and Mortality," NBER Working Papers 30663, National Bureau of Economic Research, Inc.
    2. W. Kip Viscusi, 2020. "Pricing the global health risks of the COVID-19 pandemic," Journal of Risk and Uncertainty, Springer, vol. 61(2), pages 101-128, October.
    3. Thomas J. Kniesner & W. Kip Viscusi, 2023. "Compensating Differentials for Occupational Health and Safety Risks: Implications of Recent Evidence," Research in Labor Economics, in: 50th Celebratory Volume, volume 50, pages 83-116, Emerald Group Publishing Limited.
    4. Daniel R. Petrolia & Dennis Guignet & John Whitehead & Cannon Kent & Clay Caulder & Kelvin Amon, 2021. "Nonmarket Valuation in the Environmental Protection Agency's Regulatory Process," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 952-969, September.
    5. Rebecca Newman & Ilan Noy, 2023. "The global costs of extreme weather that are attributable to climate change," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. Zarko Kalamov, 2021. "Evaluating Marginal Internalities: A New Approach," CESifo Working Paper Series 9476, CESifo.
    7. Fernando-Ignacio Sánchez-Martínez & Jorge-Eduardo Martínez-Pérez & José-María Abellán-Perpiñán & José-Luis Pinto-Prades, 2021. "The value of statistical life in the context of road safety: new evidence on the contingent valuation/standard gamble chained approach," Journal of Risk and Uncertainty, Springer, vol. 63(2), pages 203-228, October.
    8. Nelson, Jon Paul, 2020. "Fixed-effect versus random-effects meta-analysis in economics: A study of pass-through rates for alcohol beverage excise taxes," Economics Discussion Papers 2020-1, Kiel Institute for the World Economy (IfW Kiel).
    9. Hamid Noghanibehambari & Farzaneh Noghani, 2023. "Long‐run intergenerational health benefits of women empowerment: Evidence from suffrage movements in the US," Health Economics, John Wiley & Sons, Ltd., vol. 32(11), pages 2583-2631, November.

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