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Evaluating Change in Objective Ambiguous Mortality Probability: Valuing Reduction in Ambiguity Size and Risk Level

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  • Masahide Watanabe
  • Toshio Fujimi

Abstract

This article develops a valuation model to evaluate mortality probability changes under objective ambiguity, where multiple mortality probabilities are exogenously given. We construct the valuation model based on $$\upalpha $$ α -maxmin expected utility to evaluate the reduction in ambiguity size and risk level as well as estimate the subjects’ ambiguity attitude. Our model can bring an interesting policy implication. If the subjects are ambiguity-averse, a reduction in ambiguity size with a constant risk level can increases welfare. Thus, even if risk level cannot be lowered, reduction in ambiguity size can also be used as a measure toward increasing welfare. Our model can empirically estimate this welfare change resulting from the reduction in ambiguity size. To demonstrate how our model works, we apply it to survey data on a public program that reduces mortality probability in accidents caused by wildlife. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Masahide Watanabe & Toshio Fujimi, 2015. "Evaluating Change in Objective Ambiguous Mortality Probability: Valuing Reduction in Ambiguity Size and Risk Level," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 60(1), pages 1-15, January.
    • Handle: RePEc:kap:enreec:v:60:y:2015:i:1:p:1-15
    DOI: 10.1007/s10640-013-9754-8
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    Cited by:

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    More about this item

    Keywords

    $$upalpha $$ α -Maxmin expected utility; Mortality probability; Objective ambiguity; Valuation; Q51; D81;
    All these keywords.

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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