How much do we learn? Measuring symmetric and asymmetric deviations from Bayesian updating through choices

• 成果类型: Article
• 署名作者: Aydogan, Ilke; Baillon, Aurelien; Kemel, Emmanuel; Li, Chen
• 署名单位: Universite de Lille; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Humanities & Social Sciences (INSHS); IESEG School of Management; Centre National de la Recherche Scientifique (CNRS); Ecole Normale Superieure de Lyon (ENS de LYON); Universite Claude Bernard Lyon 1; Universite Jean Monnet; Universite Lyon 2; emlyon business school; Centre National de la Recherche Scientifique (CNRS); Hautes Etudes Commerciales (HEC) Paris; Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam
• 刊物名称: QUANTITATIVE ECONOMICS
• ISSN/ISSBN: 1759-7323
• DOI: 10.3982/QE2094
• 发表日期: 2025
• 页码: 329-365
• 关键词: Non-Bayesian updating; conservatism; confirmatory bias; perceived signals; belief elicitation; C91; D83

摘要

Belief-updating biases hinder the correction of inaccurate beliefs and lead to suboptimal decisions. We complement Rabin and Schrag's (1999) portable extension of the Bayesian model by including conservatism in addition to confirmatory bias. Additionally, we show how to identify these two forms of biases from choices. In an experiment, we found that the subjects exhibited confirmatory bias by misreading 19% of the signals that contradicted their priors. They were also conservative and acted as if they missed 28% of the signals.