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Testing Weak Cross-Sectional Dependence in Large Panels

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  • Pesaran, M. H.

Abstract

This paper considers testing the hypothesis that errors in a panel data model are weakly cross sectionally dependent, using the exponent of cross-sectional dependence , introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the CD test depends on the relative expansion rates of N and T . When T = O , for some , then the implicit null of the CD test is given by , which gives , when N and T tend to infinity at the same rate such that T /N , with being a finite positive constant. It is argued that in the case of large N panels, the null of weak dependence is more appropriate than the null of independence which could be quite restrictive for large panels. Using Monte Carlo experiments, it is shown that the CD test has the correct size for values of in the range [0, 1/4], for all combinations of N and T , and irrespective of whether the panel contains lagged values of the dependent variables, so long as there are no major asymmetries in the error distribution.

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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 1208.

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Date of creation: 28 Feb 2012
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Handle: RePEc:cam:camdae:1208

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Web page: http://www.econ.cam.ac.uk/index.htm

Related research

Keywords: Exponent of cross-sectional dependence; Diagnostic tests; Panel data models; Dynamic heterogenous panels;

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References

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  1. Chudik, A. & Pesaran, M.H. & Tosetti, E., 2009. "Weak and Strong Cross Section Dependence and Estimation of Large Panels," Cambridge Working Papers in Economics 0924, Faculty of Economics, University of Cambridge.
  2. M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, 03.
  3. Sarafidis, Vasilis & Yamagata, Takashi & Robertson, Donald, 2009. "A test of cross section dependence for a linear dynamic panel model with regressors," Journal of Econometrics, Elsevier, vol. 148(2), pages 149-161, February.
  4. Francesco Moscone & Elisa Tosetti, 2009. "A Review And Comparison Of Tests Of Cross-Section Independence In Panels," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 528-561, 07.
  5. 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.
  6. Sarafidis, Vasilis & Wansbeek, Tom, 2010. "Cross-sectional Dependence in Panel Data Analysis," MPRA Paper 20367, University Library of Munich, Germany.
  7. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2011. "Testing for sphericity in a fixed effects panel data model," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-47, February.
  8. N/A, 1973. "A Correction," The Indian Economic & Social History Review, , vol. 10(2), pages 207-207, April.
  9. Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
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Cited by:
  1. Karaman Örsal, Deniz Dilan, 2014. "Do the global stochastic trends drive the real house prices in OECD countries?," Economics Letters, Elsevier, vol. 123(1), pages 9-13.
  2. Hevia, Constantino & Serven, Luis, 2013. "Partial consumption insurance and financial openness across the world," Policy Research Working Paper Series 6479, The World Bank.
  3. Cem Ertur & Antonio Musolesi, 2014. "Dépendance individuelle forte et faible : une analyse en données de panel de la diffusion internationale de la technologie," Working Papers halshs-01015208, HAL.

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