关于买方可能学到什么的分歧

中文摘要 AI 辅助

我引入了一个稳健性准则，适用于玩家可能对由内生选择的信息所诱导的信号分布产生分歧的环境。秉承Hansen和Sargent（2008）的精神，一个信息选择通过其在围绕其诱导的信号分布的$\n$-熵球内的信念上的最坏情况收益来评估。我将这一公式应用于双边贸易中的买方最优学习（Roesler和Szentes，2017）。如果贸易总是有效率的，分歧会提高价格并使买方的需求曲线扭曲，同时保持完全贸易。当贸易可能无效率时，相同的特征在贸易条件下成立，并伴有内生放大的分歧水平。

英文摘要

I introduce a robustness criterion for settings where players may disagree about the distribution over signals induced by endogenously chosen information. In the spirit of Hansen and Sargent (2008), an information choice is evaluated by its worst-case payoff over beliefs within an $η$-entropy ball around the signal distribution it induces. I apply this formulation to buyer-optimal learning in bilateral trade (Roesler and Szentes, 2017). If trade is always efficient, disagreement raises the price and twists the buyer's demand curve while preserving full trade. When trade may be inefficient, the same characterization holds conditional on trade with an endogenously amplified disagreement level.

发表机构

• University of Southern California（南加州大学）

机构由 AI 辅助整理，请以论文原文为准。