Belief Bias Identification
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摘要
This paper develops a unified structural framework that identifies multiple, potentially-confounded belief-updating biases by using elicited prior and posterior beta distributions, and tests it in a laboratory urn experiment; at the population level base-rate neglect persists but overinference vanishes once richer bias channels are included, while individual-level analysis reveals widespread heterogeneity with sequence-related (hot-hand / gambler) and motivated-belief biases as primary drivers [page::0].
