Artikel

Learning by matching

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.

Sprache
Englisch

Erschienen in
Journal: Theoretical Economics ; ISSN: 1555-7561 ; Volume: 15 ; Year: 2020 ; Issue: 1 ; Pages: 29-56 ; New Haven, CT: The Econometric Society

Klassifikation
Wirtschaft
Bargaining Theory; Matching Theory
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Thema
Two-sided matching
incomplete information
stability
learning-blocking path
convergence

Ereignis
Geistige Schöpfung
(wer)
Chen, Yi-chun
Hu, Gaoji
Ereignis
Veröffentlichung
(wer)
The Econometric Society
(wo)
New Haven, CT
(wann)
2020

DOI
doi:10.3982/TE3088
Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Chen, Yi-chun
  • Hu, Gaoji
  • The Econometric Society

Entstanden

  • 2020

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