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‘General Diagnostic Tests for Cross Section Dependence in Panels’

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  • Pesaran, M.H.

Abstract

This paper proposes simple tests of error cross section dependence which are applicable to a variety of panel data models, including stationary and unit root dynamic heterogeneous panels with short T and large N. The proposed tests are based on average of pair-wise correlation coefficients of the OLS residuals from the individual regressions in the panel, and can be used to test for cross section dependence of any fixed order p, as well as the case where no a priori ordering of the cross section units is assumed, referred to a CD(p) and CD tests, respectively. Asymptotic distribution of these tests are derived and their power function analysed under different alternatives. It is shown that these test are correctly centred for fixed N and T, and are robust to single or multiple breaks in the slope coefficients and/or error variances. The small sample properties of the tests have the correct size in very small samples and satisfactory power, and as predicted by the theory, quite robust to the presence of unit roots and structural breaks. The use of the CD test is illustrated by applying it to study the degree of dependence in per capital output innovations across countries within a given region and across countries in different regions. The results show significant evidence of cross dependence in output innovations across many countries and regions of the world.

Suggested Citation

  • Pesaran, M.H., 2004. "‘General Diagnostic Tests for Cross Section Dependence in Panels’," Cambridge Working Papers in Economics 0435, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0435 Note: EM
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    References listed on IDEAS

    as
    1. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
    2. N/A, 1973. "A Correction," The Indian Economic & Social History Review, , vol. 10(2), pages 207-207, April.
    3. Robert J. Barro, 1998. "Determinants of Economic Growth: A Cross-Country Empirical Study," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262522543, January.
    4. Pesaran, H.M., 2003. "Estimation and Inference in Large Heterogeneous Panels with Cross Section Dependence," Cambridge Working Papers in Economics 0305, Faculty of Economics, University of Cambridge.
    5. Lee, Kevin & Pesaran, M Hashem & Smith, Ron, 1997. "Growth and Convergence in Multi-country Empirical Stochastic Solow Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., pages 357-392.
    6. Swamy, P A V B, 1970. "Efficient Inference in a Random Coefficient Regression Model," Econometrica, Econometric Society, vol. 38(2), pages 311-323, March.
    7. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    8. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 239-253.
    9. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    10. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    11. Ahn, Seung Chan & Hoon Lee, Young & Schmidt, Peter, 2001. "GMM estimation of linear panel data models with time-varying individual effects," Journal of Econometrics, Elsevier, vol. 101(2), pages 219-255, April.
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    More about this item

    Keywords

    cross section dependence; spatial dependence; diagnostic tests; dynamic heterogeneous panels; empirical growth;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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