Inferring beliefs as subjectively imprecise probabilities

Theory and Decision 73 (1):161-184 (2012)
We propose a method for estimating subjective beliefs, viewed as a subjective probability distribution. The key insight is to characterize beliefs as a parameter to be estimated from observed choices in a well-defined experimental task and to estimate that parameter as a random coefficient. The experimental task consists of a series of standard lottery choices in which the subject is assumed to use conventional risk attitudes to select one lottery or the other and then a series of betting choices in which the subject is presented with a range of bookies offering odds on the outcome of some event that the subject has a belief over. Knowledge of the risk attitudes of subjects conditions the inferences about subjective beliefs. Maximum simulated likelihood methods are used to estimate a structural model in which subjects employ subjective beliefs to make bets. We present evidence that some subjective probabilities are indeed best characterized as probability distributions with non-zero variance.
Keywords Subjective risk  Subjective beliefs  Random coefficients  Non-linear mixed logit  Experiments
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DOI 10.1007/s11238-011-9276-1
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References found in this work BETA
Leonard Savage (1971). Elicitation of Personal Probabilities and Expectations. Journal of the American Statistical Association 66 (336):783-801.

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