A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels

73 Pages Posted: 15 Nov 2017

See all articles by Alexander Chudik

Alexander Chudik

Federal Reserve Banks - Federal Reserve Bank of Dallas

M. Hashem Pesaran

University of Southern California - Department of Economics; University of Cambridge - Trinity College (Cambridge)

Multiple version iconThere are 2 versions of this paper

Date Written: 2017-09-01

Abstract

This paper contributes to the GMM literature by introducing the idea of self-instrumenting target variables instead of searching for instruments that are uncorrelated with the errors, in cases where the correlation between the target variables and the errors can be derived. The advantage of the proposed approach lies in the fact that, by construction, the instruments have maximum correlation with the target variables and the problem of weak instrument is thus avoided. The proposed approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In this paper we focus on the latter and consider both univariate and multivariate panel data models with short time dimension. Simple Bias-corrected Methods of Moments (BMM) estimators are proposed and shown to be consistent and asymptotically normal, under very general conditions on the initialization of the processes, individual-specific effects, and error variances allowing for heteroscedasticity over time as well as cross-sectionally. Monte Carlo evidence document BMM’s good small sample performance across different experimental designs and sample sizes, including in the case of experiments where the system GMM estimators are inconsistent. We also find that the proposed estimator does not suffer size distortions and has satisfactory power performance as compared to other estimators.

JEL Classification: C12, C13, C23

Suggested Citation

Chudik, Alexander and Pesaran, M. Hashem, A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels (2017-09-01). Globalization and Monetary Policy Institute Working Paper No. 327, Available at SSRN: https://ssrn.com/abstract=3071636 or http://dx.doi.org/10.24149/gwp327

Alexander Chudik (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Dallas ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States

M. Hashem Pesaran

University of Southern California - Department of Economics

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

University of Cambridge - Trinity College (Cambridge) ( email )

United Kingdom

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