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Testing for cross-sectional dependence in a panel factor model using the wild bootstrap $$F$$ test

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  • Badi Baltagi
  • Chihwa Kao
  • Sanggon Na

Abstract

This paper considers testing for cross-sectional dependence in a panel factor model. Based on the model considered by Bai (Econometrica 71: 135–171, 2003 ), we investigate the use of a simple $$F$$ test for testing for cross-sectional dependence when the factor may be known or unknown. The limiting distributions of these $$F$$ test statistics are derived when the cross-sectional dimension and the time-series dimension are both large. The main contribution of this paper is to propose a wild bootstrap $$F$$ test which is shown to be consistent and which performs well in Monte Carlo simulations especially when the factor is unknown. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Badi Baltagi & Chihwa Kao & Sanggon Na, 2013. "Testing for cross-sectional dependence in a panel factor model using the wild bootstrap $$F$$ test," Statistical Papers, Springer, vol. 54(4), pages 1067-1094, November.
    • Handle: RePEc:spr:stpapr:v:54:y:2013:i:4:p:1067-1094
    DOI: 10.1007/s00362-013-0499-9
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    References listed on IDEAS

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    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. Kramer, Walter & Michels, Sonja, 1997. "Autocorrelation- and heteroskedasticity-consistent t-values with trending data," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 141-147.
    3. James R. Schott, 2005. "Testing for complete independence in high dimensions," Biometrika, Biometrika Trust, vol. 92(4), pages 951-956, December.
    4. Chris D. Orme & Takashi Yamagata, 2006. "The asymptotic distribution of the F-test statistic for individual effects," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 404-422, November.
    5. Donald W. K. Andrews, 2005. "Cross-Section Regression with Common Shocks," Econometrica, Econometric Society, vol. 73(5), pages 1551-1585, September.
    6. Bai, Jushan & Kao, Chihwa & Ng, Serena, 2009. "Panel cointegration with global stochastic trends," Journal of Econometrics, Elsevier, vol. 149(1), pages 82-99, April.
    7. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
    8. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    9. Boos, Dennis D. & Brownie, Cavell, 1995. "ANOVA and rank tests when the number of treatments is large," Statistics & Probability Letters, Elsevier, vol. 23(2), pages 183-191, May.
    10. Kramer, W., 1989. "On the robustness of the F-test to autocorrelation among disturbances," Economics Letters, Elsevier, vol. 30(1), pages 37-40.
    11. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
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    Citations

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    Cited by:

    1. Corinna Ghirelli, 2015. "Scars of early non-employment for low educated youth: evidence and policy lessons from Belgium," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-34, December.
    2. Yannick Hoga, 2022. "Quantifying the data-dredging bias in structural break tests," Statistical Papers, Springer, vol. 63(1), pages 143-155, February.
    3. Rui Wang & Xingzhong Xu, 2021. "A Bayesian-motivated test for high-dimensional linear regression models with fixed design matrix," Statistical Papers, Springer, vol. 62(4), pages 1821-1852, August.
    4. Corinna.Ghirelli, 2014. "The scarring effect of early non-employment," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 14/895, Ghent University, Faculty of Economics and Business Administration.
    5. Niklas Ahlgren & Paul Catani, 2017. "Wild bootstrap tests for autocorrelation in vector autoregressive models," Statistical Papers, Springer, vol. 58(4), pages 1189-1216, December.
    6. Joakim Westerlund & Sagarika Mishra, 2017. "On the determination of the number of factors using information criteria with data-driven penalty," Statistical Papers, Springer, vol. 58(1), pages 161-184, March.
    7. Corinna GHIRELLI, 2015. "Scars of early non-employment in a rigid labour market," LIDAM Discussion Papers IRES 2015008, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).

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    More about this item

    Keywords

    Panel factor model; $$F$$ test; Wild bootstrap; Cross-sectional dependence; C12; C15; C33;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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