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Identification and estimation of a triangular model with multiple endogenous variables and insufficiently many instrumental variables

Liquan Huang, Umair Khalil () and Neşe Yıldız

Journal of Econometrics, 2019, vol. 208, issue 2, 346-366

Abstract: We develop a novel identification method for a partially linear model with multiple endogenous variables of interest but a single instrumental variable, which could even be binary. We present an easy-to-implement consistent estimator for the parametric part. This estimator retains n-convergence rate and asymptotic normality even though we have a generated regressor in our setup. The nonparametric part of the model is also identified. We also outline how our identification strategy can be extended to a fully non-parametric model. Finally, we use our methods to assess the impact of smoking during pregnancy on birth weight.

Keywords: Identification; Multiple endogenous variables; Control function approach (search for similar items in EconPapers)
JEL-codes: C31 C36 C13 C14 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:208:y:2019:i:2:p:346-366

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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