Learning by matching

Yi-Chun Chen () and Gaoji Hu ()
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Yi-Chun Chen: Department of Economics, National University of Singapore
Gaoji Hu: School of Economics, Shanghai University of Finance and Economics

Theoretical Economics, 2020, vol. 15, issue 1

Abstract: 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.

Keywords: Two-sided matching; incomplete information; stability; learning-blocking path; convergence (search for similar items in EconPapers)
JEL-codes: C78 D83 (search for similar items in EconPapers)
Date: 2020-02-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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