Lattice Operations for the Stable Set in Substitutable Matching Markets via re-equilibration Dynamics

Agustín Bonifacio, Noelia Juarez and Paola Manasero

No 333, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)

Abstract: We compute the lattice operations for the (pairwise) stable set in two-sided matching markets where only substitutability on agents’ choice functions is imposed. To dothis, we use Tarski operators defined on the lattices of worker-quasi-stable and firmquasi-stable matchings. These operators resemble lay-off and vacancy chain dynamics, respectively. First, we compute the lattice operations in the many-to-one model. Then, we extend these operations to a many-to-many model with substitutable choicefunctions on one side and responsive preferences on the other, via a morphism that relates many-to-one with many-to-many matchings in a natural way. Finally, we presentthe lattice operations in the many-to-many model with substitutable choice functionson both sides.

Keywords: two-sided matching; worker-quasi-stability; firm-quasi-stability; Tarski operator; lattice operations; re-equilibration (search for similar items in EconPapers)
JEL-codes: C78 D47 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2024-08
New Economics Papers: this item is included in nep-des
References: Add references at CitEc
Citations:

Downloads: (external link)
https://rednie.eco.unc.edu.ar/files/DT/333.pdf (application/pdf)

Related works:
Working Paper: Lattice operations for the stable set in substitutable matching markets via re-equilibration dynamics (2024)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:333

Access Statistics for this paper

More papers in Working Papers from Red Nacional de Investigadores en Economía (RedNIE) Contact information at EDIRC.
Bibliographic data for series maintained by Laura Inés D Amato ().