Publication Type

Journal Article

Version

submittedVersion

Publication Date

10-2013

Abstract

Motivated by the first-differencing method for linear panel data models, we propose a class of iterative local polynomial estimators for nonparametric dynamic panel data models with or without exogenous regressors. The estimators utilize the additive structure of the first-differenced model—the fact that the two additive components have the same functional form, and the unknown function of interest is implicitly defined as a solution of a Fredholm integral equation of the second kind. We establish the uniform consistency and asymptotic normality of the estimators. We also propose a consistent test for the correct specification of linearity in typical dynamic panel data models based on the L2 distance of our nonparametric estimates and the parametric estimates under the linear restriction. We derive the asymptotic distributions of the test statistic under the null hypothesis and a sequence of Pitman local alternatives, and prove its consistency against global alternatives. Simulations suggest that the proposed estimators and tests perform well for finite samples. We apply our new method to study the relationships among economic growth, the initial economic condition and capital accumulation, and find a significant nonlinear relation between economic growth and the initial economic condition.

Keywords

Additive models, Dynamic panel data models, Fredholm integral equation, Iterative estimator, Linearity, Local polynomial regression, Specification test

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

176

Issue

2

First Page

112

Last Page

133

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2013.04.020

Publisher

Elsevier

Additional URL

https://doi.org/10.1016/j.jeconom.2013.04.020

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