Evaluating Change in Objective Ambiguous Mortality Probability: Valuing Reduction in Ambiguity Size and Risk Level
Evaluating Change in Objective Ambiguous Mortality Probability: Valuing Reduction in Ambiguity Size and Risk Level
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DOI：
10.1007/s10640-013-9754-8
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发表时间：
2015
影响因子：
5.9
通讯作者：
Masahide Watanabe;T. Fujimi
中科院分区：
文献类型：
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作者：
Masahide Watanabe;T. Fujimi
本文开发了一个评估模型来评估客观模糊条件下的死亡率概率变化，其中多个死亡率概率是外生给出的。我们构建了基于最大最小期望效用的评估模型来评估歧义大小和风险水平的减少以及估计主体的歧义态度。我们的模型可以带来有趣的政策含义。如果受试者厌恶模糊性，那么在风险水平恒定的情况下减少模糊性大小可以增加福利。因此，即使风险水平无法降低，模糊度大小的减少也可以作为增加福利的措施。我们的模型可以凭经验估计由于模糊度大小的减少而导致的福利变化。为了演示我们的模型是如何工作的，我们将其应用于一个公共项目的调查数据，该项目降低了野生动物造成的事故的死亡率概率。
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-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.