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.
Highlights
Cross-sectional dependence, described as the interaction between cross-sectional units, has been well discussed in the spatial literature
This paper derives the limiting distribution of the scaled version of Lagrange Multiplier (LM) test proposed by Pesaran (2004) but applied to a ...xed e¤ects model
We ...nd that this LM test exhibits an asymptotic bias which is related to the number of cross-sectional units n and the number of time periods T
Summary
Cross-sectional dependence, described as the interaction between cross-sectional units (e.g., households, ...rms and states etc.), has been well discussed in the spatial literature. As is the case under serial correlation in time series, cross-sectional dependence leads to e¢ ciency loss for least squares and invalidates conventional t-tests and F -tests which use standard variance-covariance estimators. This paper derives the asymptotic bias of this scaled version of the LM test in the context of a ...xed e¤ects homogeneous panel data model. Because it is based on the ...xed e¤ects residuals, we denote it by LMP to distinguish it from CDlm. The asymptotic bias of LMP is found to be a constant related to n and T which suggests a simple bias corrected LM test for the null hypothesis.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
