The authors thank Qi Li, the editor (Anindya Banerjee), and two anonymous referees for helpful comments. Most of the research for this article was done while the third author was at the University of Cambridge. He acknowledges financial support from Sinopia, quantitative specialist of HSBC Global Asset Management. The opinions expressed in this article do not necessarily represent those of DNB.
Diagnostic Tests of Cross-section Independence for Limited Dependent Variable Panel Data Models*
Article first published online: 5 JUL 2011
© Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2011
Oxford Bulletin of Economics and Statistics
Volume 74, Issue 2, pages 253–277, April 2012
How to Cite
Hsiao, C., Pesaran, M. H. and Pick, A. (2012), Diagnostic Tests of Cross-section Independence for Limited Dependent Variable Panel Data Models. Oxford Bulletin of Economics and Statistics, 74: 253–277. doi: 10.1111/j.1468-0084.2011.00646.x
- Issue published online: 9 FEB 2012
- Article first published online: 5 JUL 2011
- Final Manuscript Received: January 2011
This article considers the problem of testing for cross-section independence in limited dependent variable panel data models. It derives a Lagrangian multiplier (LM) test and shows that in terms of generalized residuals of Gourieroux et al. (1987) it reduces to the LM test of Breusch and Pagan (1980). Because of the tendency of the LM test to over-reject in panels with large N (cross-section dimension), we also consider the application of the cross-section dependence test (CD) proposed by Pesaran (2004). In Monte Carlo experiments it emerges that for most combinations of N and T the CD test is correctly sized, whereas the validity of the LM test requires T (time series dimension) to be quite large relative to N. We illustrate the cross-sectional independence tests with an application to a probit panel data model of roll-call votes in the US Congress and find that the votes display a significant degree of cross-section dependence.