Partial Identification in Nonparametric One-to-One Matching Models

Gualdani, Cristina and Sinha, Shruti (2019) Partial Identification in Nonparametric One-to-One Matching Models. TSE Working Paper, n. 19-993, Toulouse

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Official URL: http://tse-fr.eu/pub/33016

Abstract

We consider the one-to-one matching models with transfers of Choo and Siow (2006) and Galichon and Salanié (2015). When the analyst has data on one large market only, we study identification of the systematic components of the agents’ preferences without imposing parametric restrictions on the probability distribution of the latent variables. Specifically, we provide a tractable characterisation of the region of parameter values that exhausts all the implications of the model and data (the sharp identified set), under various classes of nonparametric distributional assumptions on the unobserved terms. We discuss a way to conduct inference on the sharp identified set and conclude with Monte Carlo simulations.

Item Type: Monograph (Working Paper)
Language: English
Date: February 2019
Place of Publication: Toulouse
Uncontrolled Keywords: One-to-One Matching, Transfers, Stability, Partial Identification, Nonparametric Identification, Linear Programming
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse Capitole
Site: UT1
Date Deposited: 21 Feb 2019 14:51
Last Modified: 11 Jul 2019 12:54
OAI ID: oai:tse-fr.eu:33016
URI: http://publications.ut-capitole.fr/id/eprint/31540

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