Universität zu Köln

Breitung, Joerg and Hansen, Philipp . Alternative estimation approaches for the factor augmented panel data model with smallT. Empir. Econ.. HEIDELBERG: PHYSICA-VERLAG GMBH & CO. ISSN 1435-8921

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Abstract

In this paper, we compare alternative estimation approaches for factor augmented panel data models. Our focus lies on panel data sets where the number of panel groups (N) is large relative to the number of time periods (T). The principal component (PC) and common correlated effects (CCE) estimators were originally developed for panel data with largeNandT, whereas the GMM approaches of Ahn et al. (J Econ 728 174:1-14, 2013) and Robertson and Sarafidis (J Econ 185(2):526-541, 2015) assume thatTis small (that isTis fixed in the asymptotic analysis). Our comparison of existing methods addresses three different issues. First, we analyze the possibility of an inappropriate normalization of the factor space (the so-called normalization failure). In particular we propose a variant of the CCE estimator that avoids the normalization failure by adapting a weighting scheme inspired by the analysis of Mundlak (Econometrica 46(1):69-85, 1978). Second, we analyze the effects of estimating versus fixing the number of factors in advance. Third, we demonstrate how the design of the Monte Carlo simulations favors some estimators, which explains the conflicting findings from existing Monte Carlo experiments.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Breitung, Joerg UNSPECIFIED UNSPECIFIED UNSPECIFIED Hansen, Philipp UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-315478
DOI:	10.1007/s00181-020-01948-7
Journal or Publication Title:	Empir. Econ.
Publisher:	PHYSICA-VERLAG GMBH & CO
Place of Publication:	HEIDELBERG
ISSN:	1435-8921
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language REGRESSION-MODELS; NUMBER; DEPENDENCE; INFERENCE Multiple languages Economics; Social Sciences, Mathematical Methods Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/31547