Estimation of a Partially Linear Regression in Triangular Systems

Xin Geng, Carlos Martins-Filho and Feng Yao
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Xin Geng: IFPRI
Feng Yao: West Virginia University, Department of Economics

No 15-46, Working Papers from Department of Economics, West Virginia University

Abstract: We propose a kernel-based estimator for a partially linear regression in a triangular system where endogenous regressors appear both in the nonparametric and linear components of the regression. Compared with alternative estimators currently available in the literature (Ai and Chen 2003; Otsu 2011), our estimator has an explicit functional form, is easier to implement, and exhibits better experimental finite sample performance. The estimator is inspired by the control function approach of Newey et al. (1999) and was initially proposed by Martins-Filho and Yao (2012). It explores conditional moment restrictions that make it suitable for additive regression estimation as in Kim et al. (1999) and Manzan and Zerom (2005). We establish consistency and asymptotic normality of the estimator for the parameters in the linear component of the model and give a uniform convergence rate for the estimator of the nonparametric component. In addition, for statistical inference, a consistent estimator for the covariance of the limiting distribution of the parametric estimator is provided. We illustrate the empirical viability of our estimation procedure by applying it to the study of the impact of foreign aid and policy on growth of per capita gross domestic product (GDP) in developing countries.

Keywords: partially linear regression; endogeneity; semiparametric instrumental variable estimation (search for similar items in EconPapers)
JEL-codes: C14 C36 (search for similar items in EconPapers)
Pages: 57 pages
Date: 2015-10
New Economics Papers: this item is included in nep-ecm and nep-ore
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Working Paper: Estimation of a Partially Linear Regression in Triangular Systems (2018)
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