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Partial Identification in Matching Models for the Marriage Market

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  • Cristina Gualdani
  • Shruti Sinha

Abstract

We study partial identification of the preference parameters in the one-to-one matching model with perfectly transferable utilities. We do so without imposing parametric distributional assumptions on the unobserved heterogeneity and with data on one large market. We provide a tractable characterisation of the identified set under various classes of nonparametric distributional assumptions on the unobserved heterogeneity. Using our methodology, we re-examine some of the relevant questions in the empirical literature on the marriage market, which have been previously studied under the Logit assumption. Our results reveal that many findings in the aforementioned literature are primarily driven by such parametric restrictions.

Suggested Citation

  • Cristina Gualdani & Shruti Sinha, 2019. "Partial Identification in Matching Models for the Marriage Market," Papers 1902.05610, arXiv.org, revised Jul 2022.
  • Handle: RePEc:arx:papers:1902.05610
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    References listed on IDEAS

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    8. Sinha, Shruti, 2018. "Identification in One-to-One Matching Models with Nonparametric Unobservables," TSE Working Papers 18-897, Toulouse School of Economics (TSE).
    9. Dagsvik, John K, 2000. "Aggregation in Matching Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(1), pages 27-57, February.
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    Cited by:

    1. Timothy Christensen & Benjamin Connault, 2023. "Counterfactual Sensitivity and Robustness," Econometrica, Econometric Society, vol. 91(1), pages 263-298, January.

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