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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.23116 |
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| _version_ | 1866908680026324992 |
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| author | Galichon, Alfred Jacquet, Antoine Salakhutdinov, Georgy |
| author_facet | Galichon, Alfred Jacquet, Antoine Salakhutdinov, Georgy |
| contents | We present a general framework for matching with transferable utility (TU) that accommodates arbitrary heterogeneity without relying on the logit structure. The optimal assignment problem is characterized by tractable linear programming formulation, allowing flexible error distributions and correlation patterns. We introduce an iterative algorithm that solves large-scale assignment problems with guaranteed convergence and an intuitive economic interpretation, and we show how the same structure supports a simulated moment-matching estimator of the systematic surplus. Experiments using simulated data demonstrate the algorithm's scalability and the estimator's consistency under correct specification, as well as systematic bias arising from logit misspecification. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_23116 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Transferable Utility Matching Beyond Logit: Computation and Estimation with General Heterogeneity Galichon, Alfred Jacquet, Antoine Salakhutdinov, Georgy Econometrics We present a general framework for matching with transferable utility (TU) that accommodates arbitrary heterogeneity without relying on the logit structure. The optimal assignment problem is characterized by tractable linear programming formulation, allowing flexible error distributions and correlation patterns. We introduce an iterative algorithm that solves large-scale assignment problems with guaranteed convergence and an intuitive economic interpretation, and we show how the same structure supports a simulated moment-matching estimator of the systematic surplus. Experiments using simulated data demonstrate the algorithm's scalability and the estimator's consistency under correct specification, as well as systematic bias arising from logit misspecification. |
| title | Transferable Utility Matching Beyond Logit: Computation and Estimation with General Heterogeneity |
| topic | Econometrics |
| url | https://arxiv.org/abs/2511.23116 |