Learning by matching

• 成果类型: Article
• 署名作者: Chen, Yi-Chun; Hu, Gaoji
• 署名单位: National University of Singapore; National University of Singapore; Shanghai University of Finance & Economics
• 刊物名称: THEORETICAL ECONOMICS
• ISSN/ISSBN: 1933-6837
• DOI: 10.3982/TE3088
• 发表日期: 2020-01-01
• 页码: 29-56
• 关键词: Two-sided matching; incomplete information; STABILITY; learning-blocking path; CONVERGENCE

摘要

This paper studies a stability notion and matching processes in the job market with incomplete information on the workers' side. Each worker is associated with a type, and each firm cares about the type of her employee under a match. Moreover, firms' information structure is described by partitions over possible worker type profiles. With this firm-specific information, we propose a stability notion which, in addition to requiring individual rationality and no blocking pairs, captures the idea that the absence of rematching conveys no further information. When an allocation is not stable under the status quo information structure, a new pair of an allocation and an information structure will be derived. We show that starting from an arbitrary allocation and an arbitrary information structure, the process of allowing randomly chosen blocking pairs to rematch, accompanied by information updating, will converge with probability one to an allocation that is stable under the updated information structure. Our results are robust with respect to various alternative learning patterns.