Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure

60 Pages Posted: 28 Nov 2004

See all articles by M. Hashem Pesaran

M. Hashem Pesaran

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

Date Written: November 2004

Abstract

This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individual-specific regressors, and the factor loadings differ over the cross section units. The basic idea behind the proposed estimation procedure is to filter the individual-specific regressors by means of (weighted) cross-section aggregates such that asymptotically as the cross-section dimension (N) tends to infinity the differential effects of unobserved common factors are eliminated. The estimation procedure has the advantage that it can be computed by OLS applied to an auxiliary regression where the observed regressors are augmented by (weighted) cross sectional averages of the dependent variable and the individual specific regressors. Two different but related problems are addressed: one that concerns the coefficients of the individual-specific regressors, and the other that focusses on the mean of the individual coefficients assumed random. In both cases appropriate estimators, referred to as common correlated effects (CCE) estimators, are proposed and their asymptotic distribution as N with T (the time-series dimension) fixed or as N and T (jointly) are derived under different regularity conditions. One important feature of the proposed CCE mean group (CCEMG) estimator is its invariance to the (unknown but fixed) number of unobserved common factors as N and T (jointly). The small sample properties of the various pooled estimators are investigated by Monte Carlo experiments that confirm the theoretical derivations and show that the pooled estimators have generally satisfactory small sample properties even for relatively small values of N and T.

Keywords: cross section dependence, large panels, common correlated effects, heterogeneity, estimation and inference

JEL Classification: C12, C13, C33

Suggested Citation

Pesaran, M. Hashem, Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure (November 2004). Available at SSRN: https://ssrn.com/abstract=625981

M. Hashem Pesaran (Contact Author)

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

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
146
Abstract Views
3,056
rank
244,142
PlumX Metrics