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从主观生存数据估计二阶概率信念

Estimating Second Order Probability Beliefs from Subjective Survival Data.

作者信息

Hudomiet Péter, Willis Robert J

机构信息

Department of Economics and Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48109.

出版信息

Decis Anal. 2013 Jun;10(2). doi: 10.1287/deca.2013.0266.

Abstract

Based on subjective survival probability questions in the Health and Retirement Study (HRS), we use an econometric model to estimate the determinants of individual-level uncertainty about personal longevity. This model is built around the modal response hypothesis (MRH), a mathematical expression of the idea that survey responses of 0%, 50%, or 100% to probability questions indicate a high level of uncertainty about the relevant probability. We show that subjective survival expectations in 2002 line up very well with realized mortality of the HRS respondents between 2002 and 2010. We show that the MRH model performs better than typically used models in the literature of subjective probabilities. Our model gives more accurate estimates of low probability events and it is able to predict the unusually high fraction of focal 0%, 50%, and 100% answers observed in many data sets on subjective probabilities. We show that subjects place too much weight on parents' age at death when forming expectations about their own longevity, whereas other covariates such as demographics, cognition, personality, subjective health, and health behavior are under weighted. We also find that less educated people, smokers, and women have less certain beliefs, and recent health shocks increase uncertainty about survival, too.

摘要

基于健康与退休研究(HRS)中的主观生存概率问题,我们使用计量经济学模型来估计个人层面关于个人寿命不确定性的决定因素。该模型围绕模态响应假设(MRH)构建,这是一种数学表达式,其观点是对概率问题给出0%、50%或100%的调查回应表明对相关概率存在高度不确定性。我们表明,2002年的主观生存预期与HRS受访者在2002年至2010年期间的实际死亡率非常吻合。我们表明,MRH模型在主观概率文献中比通常使用的模型表现更好。我们的模型对低概率事件给出了更准确的估计,并且能够预测在许多关于主观概率的数据集里观察到的异常高比例的焦点0%、50%和100%答案。我们表明,在形成对自身寿命的预期时,受试者过于看重父母的死亡年龄,而其他协变量,如人口统计学、认知、性格、主观健康和健康行为等则权重不足。我们还发现,受教育程度较低的人、吸烟者和女性的信念较不确定,而且近期的健康冲击也会增加生存的不确定性。

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