Asymptotic distribution of factor augmented estimators for panel regression

Ryan Greenaway-McGrevy; Chirok Han; Donggyu Sul

doi:10.1016/j.jeconom.2012.01.003

Asymptotic distribution of factor augmented estimators for panel regression

Ryan Greenaway-McGrevy, Chirok Han, Donggyu Sul

Research output: Contribution to journal › Article › peer-review

64 Citations (Scopus)

Abstract

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 TN→0 and N ^T3→0 under regularity. Monte Carlo studies verify the asymptotic theory.

Original language	English
Pages (from-to)	48-53
Number of pages	6
Journal	Journal of Econometrics
Volume	169
Issue number	1
DOIs	https://doi.org/10.1016/j.jeconom.2012.01.003
Publication status	Published - 2012 Jul

Bibliographical note

Funding Information:
The views expressed herein are those of the authors and not necessarily those of the Bureau of Economic Analysis or the Department of Commerce. We thank I. Choi, Sainan Jin, C.J. Kim, H. R. Moon, Liangjun Su, K. Tanaka, Y. J. Whang, the editors and anonymous referees for helpful comments. A previous version of this paper was circulated under the title “Estimating and Testing Idiosyncratic Equations using Cross Section Dependent Panel Data”. Research for the paper was supported under a Marsden grant.

Keywords

Cross section dependence
Factor augmented estimator
Factor augmented panel regression
Interactive fixed effects
Principal component augmented estimator

ASJC Scopus subject areas

Economics and Econometrics

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10.1016/j.jeconom.2012.01.003

Cite this

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title = "Asymptotic distribution of factor augmented estimators for panel regression",

abstract = "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 TN→0 and N T3→0 under regularity. Monte Carlo studies verify the asymptotic theory.",

keywords = "Cross section dependence, Factor augmented estimator, Factor augmented panel regression, Interactive fixed effects, Principal component augmented estimator",

author = "Ryan Greenaway-McGrevy and Chirok Han and Donggyu Sul",

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AU - Han, Chirok

AU - Sul, Donggyu

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N2 - 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 TN→0 and N T3→0 under regularity. Monte Carlo studies verify the asymptotic theory.

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KW - Cross section dependence

KW - Factor augmented estimator

KW - Factor augmented panel regression

KW - Interactive fixed effects

KW - Principal component augmented estimator

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JO - Journal of Econometrics

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Asymptotic distribution of factor augmented estimators for panel regression

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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