A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model

Badi H. Baltagi, Qu Feng, Chihwa Kao

Research output: Contribution to journalArticlepeer-review

560 Scopus citations

Abstract

It is well known that the standard Breusch and Pagan (1980) LM test for cross-equation correlation in a SUR model is not appropriate for testing cross-sectional dependence in panel data models when the number of cross-sectional units (n) is large and the number of time periods (T) is small. In fact, a scaled version of this LM test was proposed by Pesaran (2004) and its finite sample bias was corrected by Pesaran et al. (2008). This was done in the context of a heterogeneous panel data model. This paper derives the asymptotic bias of this scaled version of the LM test in the context of a fixed effects homogeneous panel data model. This asymptotic bias is found to be a constant related to n and T, which suggests a simple bias corrected LM test for the null hypothesis. Additionally, the paper carries out some Monte Carlo experiments to compare the finite sample properties of this proposed test with existing tests for cross-sectional dependence.

Original languageEnglish (US)
Pages (from-to)164-177
Number of pages14
JournalJournal of Econometrics
Volume170
Issue number1
DOIs
StatePublished - Sep 2012

Keywords

  • Cross-sectional dependence
  • Fixed effects
  • High dimensional inference
  • John test
  • LM test
  • Panel data

ASJC Scopus subject areas

  • Economics and Econometrics

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