Double Filter Instrumental Variable Estimation of Panel Data Models with Weakly Exogenous Variables

Abstract

In this paper, we propose instrumental variables (IV) and generalized method of moments (GMM) estimators for panel data models with weakly exogenous variables. The model is allowed to include heterogeneous time trends besides the standard fixed effects. The proposed IV and GMM estimators are obtained by applying a forward filter to the model and a backward filter to the instruments in order to remove fixed effects, thereby called the double filter IV and GMM estimators. We derive the asymptotic properties of the proposed estimators under fixed T and large N, and large T and large N asymptotics where N and T denote the dimensions of cross section and time series, respectively. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias corrected fixed effects estimator when both N and T are large. Monte Carlo simulation results reveal that the proposed estimator performs well in finite samples and outperforms the conventional IV/GMM estimators using instruments in levels in many cases.

Keywords: GMM; panel data; weak exogeneity; dynamic panel