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Author: Gaillac, Christophe
Resulting in 1 citation.
1. D'Haultfoeuille, Xavier
Gaillac, Christophe
Maurel, Arnaud
Partially Linear Models Under Data Combination
Review of Economic Studies published online (29 March 2024): rdae022.
Also: https://doi.org/10.1093/restud/rdae022
Cohort(s): NLSY79
Publisher: Oxford University Press
Keyword(s): Data Combination; Geometric Properties; Microeconomics, Empirical; Optimal Transport Theory; Partially Linear Model

Permission to reprint the abstract has not been received from the publisher.

We study partially linear models when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequently in empirical microeconomics. Using recent tools from optimal transport theory, we derive a constructive characterization of the sharp identified set. We then build on this result and develop a novel inference method that exploits the specific geometric properties of the identified set. Our method exhibits good performances in finite samples, while remaining very tractable. We apply our approach to study intergenerational income mobility over the period 1850–1930 in the U.S. Our method allows us to relax the exclusion restrictions used in earlier work, while delivering confidence regions that are informative.
Bibliography Citation
D'Haultfoeuille, Xavier, Christophe Gaillac and Arnaud Maurel. "Partially Linear Models Under Data Combination." Review of Economic Studies published online (29 March 2024): rdae022.