Artikel

Latent indices in assortative matching models

A large class of two-sided matching models that include both transferable and non-transferable utility result in positive assortative matching along a latent index. Data from matching markets, however, may not exhibit perfect assortativity due to the presence of unobserved characteristics. This paper studies the identification and estimation of such models. We show that the distribution of the latent index is not identified when data from one-to-one matches are observed. Remarkably, the model is nonparametrically identified using data in a single large market when each agent on one side has at least two matched partners. The additional empirical content in many-to-one matches is demonstrated using simulations and stylized examples. We then derive asymptotic properties of a minimum distance estimator as the size of the market increases, allowing estimation using dependent data from a single large matching market. The nature of the dependence requires modification of existing empirical process techniques to obtain a limit theorem.

Language
Englisch

Bibliographic citation
Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 8 ; Year: 2017 ; Issue: 3 ; Pages: 685-728 ; New Haven, CT: The Econometric Society

Classification
Wirtschaft
Model Construction and Estimation
Bargaining Theory; Matching Theory
Subject
Matching
identification
estimation

Event
Geistige Schöpfung
(who)
Diamond, William
Agarwal, Nikhil
Event
Veröffentlichung
(who)
The Econometric Society
(where)
New Haven, CT
(when)
2017

DOI
doi:10.3982/QE736
Handle
Last update
20.09.2024, 8:23 AM CEST

Data provider

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Object type

  • Artikel

Associated

  • Diamond, William
  • Agarwal, Nikhil
  • The Econometric Society

Time of origin

  • 2017

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