Asymptotic distribution of factor augmented estimators for panel regression

Ryan Greenaway-McGrevy, Chirok Han, Donggyu Sul

Research output: Contribution to journalArticle

38 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 languageEnglish
Pages (from-to)48-53
Number of pages6
JournalJournal of Econometrics
Volume169
Issue number1
DOIs
Publication statusPublished - 2012 Jul 1

Fingerprint

Asymptotic distribution
Regression
Asymptotic Theory
Estimator
Common factor
Monte Carlo Study
Principal Components
Regularity
Verify
Estimate
Factors
Asymptotic theory
Panel regression
Latent factors
Monte Carlo study
Common factors
Principal components
Equations
Common Factors

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
  • Applied Mathematics
  • History and Philosophy of Science

Cite this

Asymptotic distribution of factor augmented estimators for panel regression. / Greenaway-McGrevy, Ryan; Han, Chirok; Sul, Donggyu.

In: Journal of Econometrics, Vol. 169, No. 1, 01.07.2012, p. 48-53.

Research output: Contribution to journalArticle

Greenaway-McGrevy, Ryan ; Han, Chirok ; Sul, Donggyu. / Asymptotic distribution of factor augmented estimators for panel regression. In: Journal of Econometrics. 2012 ; Vol. 169, No. 1. pp. 48-53.
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