Semiparametric Varying Coefficient Models with Endogenous Covariates

McMaster University, Department of Economics, Working Paper Series, 2016-02

36 Pages Posted: 27 Aug 2016

See all articles by Samuele Centorrino

Samuele Centorrino

SUNY Stony Brook

Jeffrey Racine

Department of Economics - McMaster University

Date Written: March 15, 2016

Abstract

Though parametric methods are popular in applied settings, practitioners often require nonparametric alternatives. However, fully nonparametric methods are known to suffer from the curse of dimensionality, which limits their practical application. Semiparametric methods occupy a middle ground, have the desirable feature that they are both exible, and provide an attractive alternative to fully nonparametric methods, while attenuating the curse-of-dimensionality. Traditional semiparametric methods, such as the popular `varying coefficient' specification, do not account for endogenous covariates, which restricts their application. In this paper we consider the estimation of semiparametric varying coeffcient models when the functional coeffcients may contain (continuous) endogenous covariates thereby extending the reach of this exible and powerful class of models.

Suggested Citation

Centorrino, Samuele and Racine, Jeffrey, Semiparametric Varying Coefficient Models with Endogenous Covariates (March 15, 2016). McMaster University, Department of Economics, Working Paper Series, 2016-02, Available at SSRN: https://ssrn.com/abstract=2826639 or http://dx.doi.org/10.2139/ssrn.2826639

Samuele Centorrino

SUNY Stony Brook ( email )

NY 11733-4384
United States

Jeffrey Racine (Contact Author)

Department of Economics - McMaster University ( email )

Hamilton, Ontario L8S 4M4
Canada

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