Estimating Second Order Probability Beliefs from Subjective Survival Data

Archived Abstract of Former PSC Researcher

Hudomiet, Péter, and Robert Willis. 2013. "Estimating Second Order Probability Beliefs from Subjective Survival Data." Decision Analysis, 10(2): 152-170.

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 underweighted. We also find that less educated people, smokers, and women have less certain beliefs, and recent health shocks increase uncertainty about survival, too.

DOI:10.1287/deca.2013.0266 (Full Text)

PMCID: PMC3882032. (Pub Med Central)

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