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Does the Cause of Death Matter? The Effect of Dread, Controllability, Exposure and Latency on the Vsl

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  • Alberini, Anna
  • Scasny, Milan

Abstract

The Value of a Statistical Life is a key input into the calculation of the benefits of environmental policies that save lives. To date, the VSL used in environmental policy analyses has not been adjusted for age or the cause of death. Air pollution regulations, however, are linked to reductions in the risk of dying for cancer, heart disease, and respiratory illnesses, raising the question whether a single VSL should be applied for all of these causes of death. We conducted a conjoint choice experiment survey in Milan, Italy, to investigate this question. We find that the VSL increases with dread, exposure, the respondents’ assessments of the baseline risks, and experience with the specific risks being studied. The VSL is higher when the risk reduction is delivered by a public program, and increases with the effectiveness rating assigned by the respondent to public programs that address specific causes of death. The effectiveness of private risk-reducing behaviors is also positively associated with the VSL, but the effect is only half as large as that of public program effectiveness. The coefficients on dummies for the cause of death per se—namely, whether it’s cancer, a road traffic accident or a respiratory illness—are strongly statistically significant. All else the same, the fact that the cause of the death is “cancer” results in a VSL that is almost one million euro above the amount predicted by dread, exposure, beliefs, etc. The VSL in the road safety context is about one million euro less than what is predicted by dread, exposure, beliefs, etc. These effects are large, but the majority of the variation in the VSL is accounted for by the public program feature, the effectiveness of public programs at reducing the indicated risk, and dread. The effects of exposure and experience are smaller. These results raise the question whether using VSL figures based on private risk reduction, which is usually recommended to avoid double-counting, severely understates how much a society might be willing to pay for public safety.

Suggested Citation

  • Alberini, Anna & Scasny, Milan, 2010. "Does the Cause of Death Matter? The Effect of Dread, Controllability, Exposure and Latency on the Vsl," Sustainable Development Papers 98097, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemdp:98097
    DOI: 10.22004/ag.econ.98097
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    Cited by:

    1. S. Olofsson & U.-G. Gerdtham & L. Hultkrantz & U. Persson, 2018. "Measuring the end-of-life premium in cancer using individual ex ante willingness to pay," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(6), pages 807-820, July.
    2. Rebecca L. McDonald & Susan M. Chilton & Michael W. Jones-Lee & Hugh R. T. Metcalf, 2016. "Dread and latency impacts on a VSL for cancer risk reductions," Journal of Risk and Uncertainty, Springer, vol. 52(2), pages 137-161, April.
    3. Alberini, Anna & Ščasný, Milan, 2018. "The benefits of avoiding cancer (or dying from cancer): Evidence from a four- country study," Journal of Health Economics, Elsevier, vol. 57(C), pages 249-262.
    4. Shelby Gerking & Wiktor Adamowicz & Mark Dickie & Marcella Veronesi, 2017. "Baseline risk and marginal willingness to pay for health risk reduction," Journal of Risk and Uncertainty, Springer, vol. 55(2), pages 177-202, December.
    5. McDonald, R.L. & Chilton, S.M. & Jones-Lee, M.W. & Metcalf, H.R.T., 2017. "Evidence of variable discount rates and non-standard discounting in mortality risk valuation," Journal of Environmental Economics and Management, Elsevier, vol. 82(C), pages 152-167.
    6. Sara Olofsson & Ulf G. Gerdtham & Lars Hultkrantz & Ulf Persson, 2019. "Dread and Risk Elimination Premium for the Value of a Statistical Life," Risk Analysis, John Wiley & Sons, vol. 39(11), pages 2391-2407, November.
    7. Barrientos, Manuel & Lavin, Felipe Vasquez & Ponce Oliva, Roberto D., 2020. "Assessing the Incorporation of Latent Variables in the Estimation of the Value of a Statistical Life," EfD Discussion Paper 20-22, Environment for Development, University of Gothenburg.
    8. Alberini, Anna & Ščasný, Milan, 2013. "Exploring heterogeneity in the value of a statistical life: Cause of death v. risk perceptions," Ecological Economics, Elsevier, vol. 94(C), pages 143-155.
    9. Olofsson, Sara & Gerdtham , Ulf-G & Hultkrantz , Lars & Persson , Ulf, 2016. "Chained Approach vs Contingent Valuation for Estimating the Value of Risk Reduction," Working Papers 2016:34, Lund University, Department of Economics.
    10. Meressa, Abrha Megos & Navrud, Stale, 2020. "Not my cup of coffee: Farmers’ preferences for coffee variety traits – Lessons for crop breeding in the age of climate change," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 9(3), December.
    11. Slunge, Daniel & Sterner, Thomas & Adamowicz, Wiktor, 2019. "Valuation when baselines are changing: Tick-borne disease risk and recreational choice," Resource and Energy Economics, Elsevier, vol. 58(C).

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J17 - Labor and Demographic Economics - - Demographic Economics - - - Value of Life; Foregone Income
    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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