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Testing Weak Cross-Sectional Dependence in Large Panels

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  • M. Hashem Pesaran

Abstract

This paper considers testing the hypothesis that errors in a panel data model are weakly Cross-sectionally dependent (CD), 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. 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 the cross-sectional exponent that lie 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.

Suggested Citation

  • M. Hashem Pesaran, 2012. "Testing Weak Cross-Sectional Dependence in Large Panels," CESifo Working Paper Series 3800, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_3800
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    File URL: http://www.cesifo-group.de/DocDL/cesifo1_wp3800.pdf
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    References listed on IDEAS

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    1. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2016. "Exponent of Cross‐Sectional Dependence: Estimation and Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 929-960, September.
    2. N/A, 1973. "A Correction," The Indian Economic & Social History Review, , vol. 10(2), pages 207-207, April.
    3. 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.
    4. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    5. 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, March.
    6. 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.
    7. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
    8. 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, July.
    9. Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
    10. 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.
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    Citations

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    Cited by:

    1. Badi H. Baltagi & Chihwa Kao & Fa Wang, 2017. "Asymptotic power of the sphericity test under weak and strong factors in a fixed effects panel data model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 853-882, October.
    2. Daniel Goya, 2014. "The Multiple Impacts of the Exchange Rate on Export Diversification," Cambridge Working Papers in Economics 1436, Faculty of Economics, University of Cambridge.
    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.
    4. 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.
    5. Jesús Clemente & María Dolores Gadea & Antonio Montañés & Marcelo Reyes, 2017. "Structural Breaks, Inflation and Interest Rates: Evidence from the G7 Countries," Econometrics, MDPI, Open Access Journal, vol. 5(1), pages 1-17, February.
    6. Daniel Goya, 2018. "The Exchange Rate and Export Variety: A cross-country analysis with long panel estimators," Working Papers 2018-01, Escuela de Negocios y Economía, Pontificia Universidad Católica de Valparaíso.
    7. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    8. Ramsay Bush Georgia, 2018. "Financial openness, policy vs. realized outcomes," Working Papers 2018-04, Banco de México.
    9. Hevia, Constantino & Serven, Luis, 2013. "Partial consumption insurance and financial openness across the world," Policy Research Working Paper Series 6479, The World Bank.

    More about this item

    Keywords

    exponent of cross-sectional dependence; diagnostic tests; panel data models; dynamic heterogenous panels;

    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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