Pakel, Cavit2020-02-042020-02-0420190304-4076http://hdl.handle.net/11693/53051Fixed 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.EnglishNonlinear dynamic panelsIncidental parameter biasIntegrated likelihood methodProfile likelihood methodFemale labour force participationArticle10.1016/j.jeconom.2019.05.020