@article{a938d05679814c309d0e971c939c2fe0,
title = "Integrated likelihood based inference for nonlinear panel data models with unobserved effects",
abstract = "We propose a new integrated likelihood based approach for estimating panel data models when the unobserved individual effects enter the model nonlinearly. Unlike existing integrated likelihoods in the literature, the one we propose is closer to a genuine likelihood. Although the statistical theory for the proposed estimator is developed in an asymptotic setting where the number of individuals and the number of time periods both approach infinity, results from a simulation study suggest that our methodology can work very well even in moderately sized panels of short duration in both static and dynamic models.",
keywords = "Fixed effects, Integrated likelihood, Nonlinear models, Panel data",
author = "Martin Schumann and Severini, {Thomas A.} and Gautam Tripathi",
note = "Funding Information: We thank the editor Serena Ng, an associate editor, and three anonymous referees, for comments that greatly improved this paper. We also thank Antonio Cosma, Geert Dhaene, Arnaud Dupuy, Bernd Fitzenberger, Dennis Kristensen, Taisuke Otsu, Martin Weidner, and seminar participants at Aarhus, Bonn, Cologne, CORE, Dortmund, Humboldt, KU-Leuven, LSE, Luxembourg, Mannheim, UCL, the 2nd joint conference of the Belgian, Royal Spanish and Luxembourg Mathematical Societies in Rioja, and the 2016 European Meeting of the Econometric Society in Geneva, for helpful suggestions and conversations. The simulation experiments reported in this paper were carried out using the HPC facilities of the University of Luxembourg (Varrette et al. 2014, http://hpc.uni.lu). Publisher Copyright: {\textcopyright} 2020 Elsevier B.V.",
year = "2021",
month = jul,
doi = "10.1016/j.jeconom.2020.10.001",
language = "English (US)",
volume = "223",
pages = "73--95",
journal = "Journal of Econometrics",
issn = "0304-4076",
publisher = "Elsevier BV",
number = "1",
}