Diagnostic Tests of Cross‐section Independence for Limited Dependent Variable Panel Data Models* |
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| Authors: | Cheng Hsiao M. Hashem Pesaran Andreas Pick |
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| Affiliation: | 1. Department of Economics, University of Southern California, Los Angeles, USA;2. Hong Kong University of Science and Technology, Hong Kong;3. WISE, Xiamen University, Xiamen, China (e‐mail: chsiao@usc.edu);4. Faculty of Economics, University of Cambridge, Cambridge, UK;5. CIMF, University of Cambridge, Cambridge, UK;6. Department of Economics, University of Southern California, Los Angeles, USA (e‐mail: mhp1@cam.ac.uk);7. Department of Econometrics, Erasmus University Rotterdam, Rotterdam, The Netherlands;8. De Nederlandsche Bank, Amsterdam, The Netherlands;9. CIMF, University of Cambridge, Cambridge, UK (e‐mail: andreas.pick@cantab.net) |
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| Abstract: | 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. |
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| Keywords: | C12 C33 C35 |
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