Estimating the number of common factors in serially dependent approximate factor models

Ryan Greenaway-McGrevy, Chirok Han, Donggyu Sul

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A simple data-dependent filtering method is proposed before applying the Bai-Ng method to estimate the number of common factors in the conventional approximate factor model. The asymptotic justification is provided and the finite-sample performance is examined.

Original languageEnglish
Pages (from-to)531-534
Number of pages4
JournalEconomics Letters
Volume116
Issue number3
DOIs
Publication statusPublished - 2012 Sep 1

Fingerprint

Common factors
Justification
Finite sample

Keywords

  • Cross-section dependence
  • Factor model
  • Factor number estimation
  • Least squares dummy variable (LSDV) filter
  • Prewhitening

ASJC Scopus subject areas

  • Economics and Econometrics
  • Finance

Cite this

Estimating the number of common factors in serially dependent approximate factor models. / Greenaway-McGrevy, Ryan; Han, Chirok; Sul, Donggyu.

In: Economics Letters, Vol. 116, No. 3, 01.09.2012, p. 531-534.

Research output: Contribution to journalArticle

Greenaway-McGrevy, Ryan ; Han, Chirok ; Sul, Donggyu. / Estimating the number of common factors in serially dependent approximate factor models. In: Economics Letters. 2012 ; Vol. 116, No. 3. pp. 531-534.
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