Partially Linear Models with Endogeneity: a conditional moment based approach

Bertille Antoine and Xiaolin Sun
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Xiaolin Sun: Simon Fraser University, https://ca.linkedin.com/in/xiaolin-sun-5b4834123?challengeId=AQEKMknhx1CjKwAAAXNtVhC97iiLSZIA1AckyKS1r__vzk0mT0_iqUip37E4-CBxAH6-SfpTfj5PVubFqzwNrb0QLklj_Mbz3w&submissionId=228ab370-1687-2316-194d-c8a5513b7049

Discussion Papers from Department of Economics, Simon Fraser University

Abstract: In a partially linear conditional moment model, we propose a new estimator for the slope parameter of the endogenous variable of interest which combines a Robinson’s transformation (Robinson (1988)), to partial out the non-linear part of the model, with a smooth minimum distance approach (Lavergne and Patilea (2013)), to exploit all the information of the conditional mean independence restriction. Our estimator is easy to compute, consistent and √n-asymptotically normal under standard regularity conditions. Simulations show that our estimator is competitive with GMM-type estimators, and often displays a smaller bias and variance, as well as better coverage rates for confidence intervals. We revisit and extend some of the empirical results in Dinkelman (2011) who estimates the impact of electrification on employment growth in South Africa: overall, we obtain estimates that are smaller in magnitude, more precise, and still economically relevant.

Keywords: Robinson’s transformation; Conditional mean independence; Nonlinearity; Minimum distance estimation; Instrument. (search for similar items in EconPapers)
JEL-codes: C13 C21 C51 D04 (search for similar items in EconPapers)
Date: 2020-07
New Economics Papers: this item is included in nep-ecm and nep-ore
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Journal Article: Partially linear models with endogeneity: a conditional moment-based approach (2022)
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