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

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 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\upalpha $$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi mathvariant="normal">α</mi> </math> </EquationSource> </InlineEquation>-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