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

Cavit Pakel

Journal of Econometrics, 2019, vol. 213, issue 2, 459-492

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.

Keywords: Nonlinear dynamic panels; Incidental parameter bias; Integrated likelihood method; Profile likelihood method; Female labour force participation (search for similar items in EconPapers)
JEL-codes: C13 C23 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:213:y:2019:i:2:p:459-492

DOI: 10.1016/j.jeconom.2019.05.020

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