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Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence

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  • Pakel, Cavit

Abstract

Fixed effects estimation of nonlinear dynamic panel models is subject to the incidental parameter issue, leading to a biased asymptotic distribution. While this problem has been studied extensively in the literature, a general analysis allowing for both serial and cross-sectional dependence is missing. In this paper we investigate the large-N,T theory of the profile and integrated likelihood estimators, allowing for dependence across both dimensions. We show that under stronger dependence types the asymptotic bias disappears, but a Op(1∕T) small-sample bias remains. We provide bias correction and inference methods, and also obtain primitive conditions for asymptotic normality under various dependence settings.

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  • Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    • Handle: RePEc:eee:econom:v:213:y:2019:i:2:p:459-492
    DOI: 10.1016/j.jeconom.2019.05.020
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    More about this item

    Keywords

    Nonlinear dynamic panels; Incidental parameter bias; Integrated likelihood method; Profile likelihood method; Female labour force participation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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