Asymptotic distribution of factor augmented estimators for panel regression

In this paper we derive an asymptotic theory for linear panel regression augmented with estimated common factors. We give conditions under which the estimated factors can be used in place of the latent factors in the regression equation. For the principal components estimate of the factor space it is shown that these conditions are satisfied when T/N→0 and N/T3→0 under regularity. Monte Carlo studies verify the asymptotic theory.

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Year of publication:	2012
Authors:	Greenaway-McGrevy, Ryan ; Han, Chirok ; Sul, Donggyu
Published in:	Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 169.2012, 1, p. 48-53
Publisher:	Elsevier
Subject:	Factor augmented panel regression \| Factor augmented estimator \| Principal component augmented estimator \| Cross section dependence \| Interactive fixed effects

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Type of publication:	Article
Classification:	C33 - Models with Panel Data
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011052339