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DYNAMIC LINEAR PANEL REGRESSION MODELS WITH INTERACTIVE FIXED EFFECTS

Published online by Cambridge University Press:  10 December 2015

Hyungsik Roger Moon*
Affiliation:
University of Southern California Yonsei University
Martin Weidner
Affiliation:
University College London
*
*Address correspondence to Hyungsik Roger Moon, Department of Economics and USC Dornsife INET, University of Southern California, Los Angeles, CA 90089-0253. e-mail: moonr@usc.edu.

Abstract

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, for example lagged-dependent variables. The first-order asymptotic theory of the least squares (LS) estimator of the regression coefficients is worked out in the limit where both the cross-sectional dimension and the number of time periods become large. We find two sources of asymptotic bias of the LS estimator: bias due to correlation or heteroscedasticity of the idiosyncratic error term, and bias due to predetermined (as opposed to strictly exogenous) regressors. We provide a bias-corrected LS estimator. We also present bias-corrected versions of the three classical test statistics (Wald, LR, and LM test) and show their asymptotic distribution is a χ2-distribution. Monte Carlo simulations show the bias correction of the LS estimator and of the test statistics also work well for finite sample sizes.

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Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2015 

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