Simulation Code and Data for: Slope-Takers in Anonymous Markets
收藏ICPSR2023-01-01 更新2026-04-16 收录
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https://www.openicpsr.org/openicpsr/project/179101/version/V1/view
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资源简介：
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.
提供机构：
University of Wisconsin-Madison
创建时间：
2023-01-01
