为小概率风险投保的价值评估：一项元分析
Valuing insurance against small probability risks: A meta-analysis
AI总结：
本文通过元分析发现低概率风险保险的平均支付意愿仅为预期损失的87%，并揭示概率信息、收入年龄、文化因素及方法学因素对支付意愿的异质性影响。
摘要：
针对低概率、高影响风险的自愿保险需求低于预期。为评估该需求的规模，我们利用实验诱导和调查估计的数据集，对条件价值评估研究进行了元分析。我们发现，保险的平均陈述性支付意愿（WTP）为预期损失的87%。我们进行了元回归分析，以考察这些研究中总体WTP的异质性。元回归显示，损失概率信息和概率水平对相对支付意愿有正向影响，而受访者的平均收入和年龄则有负向影响。此外，我们识别出文化子因素，如权力距离和不确定性规避，为国际样本间WTP差异提供了额外解释。与抽样和数据收集过程相关的方法学因素显著影响陈述性WTP。我们的结果对模型设定和发表偏倚具有稳健性，与当前关于低概率风险管理中陈述偏好的讨论相关。
英文摘要：
The demand for voluntary insurance against low-probability, high-impact risks is lower than expected. To assess the magnitude of the demand, we conduct a meta-analysis of contingent valuation studies using a dataset of experimentally elicited and survey-based estimates. We find that the average stated willingness to pay (WTP) for insurance is 87% of expected losses. We perform a meta-regression analysis to examine the heterogeneity in aggregate WTP across these studies. The meta-regression reveals that information about loss probability and probability levels positively influence relative willingness to pay, whereas respondents' average income and age have a negative effect. Moreover, we identify cultural sub-factors, such as power distance and uncertainty avoidance, that provided additional explanations for differences in WTP across international samples. Methodological factors related to the sampling and data collection process significantly influence the stated WTP. Our results, robust to model specification and publication bias, are relevant to current debates on stated preferences for low-probability risks management.
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