Bayesian Identification: A Theory for State-Dependent Utilities

• 成果类型: Article
• 署名作者: Lu, Jay
• 署名单位: University of California System; University of California Los Angeles
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.20171534
• 发表日期: 2019
• 页码: 3192-3228
• 关键词: subjective-probability; preference; flexibility; definition; beliefs; CHOICE

摘要

We provide a revealed preference methodology for identifying beliefs and utilities that can vary across states. A notion of comparative informativeness is introduced that is weaker than the standard Blackwell ranking. We show that beliefs and state-dependent utilities can be identified using stochastic choice from two informational treatments, where one is strictly more informative than another. Moreover, if the signal structure is known, then stochastic choice from a single treatment is enough for identification. These results illustrate novel identification methodologies unique to stochastic choice. Applications include identifying biases in job hiring, loan approvals, and medical advice.