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Dynamic linear panel regression models with interactive fixed effects

Authors: Hyungsik Roger Moon and Martin Weidner
Date: 10 December 2015
Type: Journal Article, Econometric Theory, Vol. 33, No. 1, pp. 158-195
DOI: 10.1017/S0266466615000328

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.

Previous version:
Hyungsik Roger Roger Moon and Martin Weidner December 2014, Dynamic linear panel regression models with interactive fixed effects, cemmap Working Paper, CWP47/14, IFS

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