Slope Takers in Anonymous Markets

• 成果类型: Article
• 署名作者: Quint, Daniel; Weretka, Marek
• 署名单位: University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: AMERICAN ECONOMIC JOURNAL-MICROECONOMICS
• ISSN/ISSBN: 1945-7669
• DOI: 10.1257/mic.20220078
• 发表日期: 2023
• 页码: 306-318
• 关键词: large-block transactions; BEHAVIOR; prices

摘要

We present a learning-based selection argument for Linear Bayesian Nash equilibrium in a Walrasian auction. Endowments vary stochastically; traders model residual supply as linear, estimate its slope from past trade data, and periodically update these estimates. In the standard setting with quadratic preferences, we show that this learning process converges to the unique LBN. Anonymity and statistical learning therefore support this commonly used equilibrium selection rule. (JEL D43, D44, D83)