IDEAS home Printed from https://ideas.repec.org/a/ect/emjrnl/v11y2008i1p105-127.html
   My bibliography  Save this article

A bias-adjusted LM test of error cross-section independence

Author

Listed:
  • M. Hashem Pesaran
  • Aman Ullah
  • Takashi Yamagata

Abstract

This paper proposes a bias-adjusted version of Breusch and Pagan (1980) Lagrange multiplier (LM) test statistic of error cross-section independence, in the case of panel models with strictly exogenous regressors and normal errors. The exact mean and variance of the test indicator of the LM test statistic are provided for the purpose of the bias-adjustments. It is shown that the centring of the LM statistic is correct for fixed T and N. Importantly, the proposed bias-adjusted LM test is consistent even when the Pesaran's (2004) CD test is inconsistent. Also an alternative bias-adjusted LM test, which is consistent under local error cross-section dependence of any fixed order p, is proposed. The finite sample behaviour of the proposed tests is investigated and compared to that of the LM and CD tests. It is shown that the bias-adjusted LM tests successfully control the size, maintaining satisfactory power in panel with exogenous regressors and normal errors. However, it is also shown that the bias-adjusted LM test is not as robust as the CD test to non-normal errors and/or in the presence of weakly exogenous regressors. Copyright Royal Economic Society 2007

Suggested Citation

  • 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.
    • Handle: RePEc:ect:emjrnl:v:11:y:2008:i:1:p:105-127
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ullah, Aman, 2004. "Finite Sample Econometrics," OUP Catalogue, Oxford University Press, number 9780198774488, Decembrie.
    2. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    3. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    4. Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hsiao, Cheng & Pesaran, M. Hashem & Pick, Andreas, 2007. "Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models," IZA Discussion Papers 2756, Institute of Labor Economics (IZA).
    2. Thomas, Ashok & Spataro, Luca & Mathew, Nanditha, 2014. "Pension funds and stock market volatility: An empirical analysis of OECD countries," Journal of Financial Stability, Elsevier, vol. 11(C), pages 92-103.
    3. Gianko Michailidis & Concepció Patxot & Meritxell Solé, 2019. "Do pensions foster education? An empirical perspective," Applied Economics, Taylor & Francis Journals, vol. 51(38), pages 4127-4150, August.
    4. Eugene Kouassi & Gnoudentiho G Silue & Oluyele Akinkugbe & Jean Marcelin B Brou, 2017. "Health expenditures and Income with Nonstationary Panel Data: Evidence from ECOWAS Member Countries," Economics Bulletin, AccessEcon, vol. 37(3), pages 2198-2218.
    5. Salim, Ruhul & Yao, Yao & Chen, George S., 2017. "Does human capital matter for energy consumption in China?," Energy Economics, Elsevier, vol. 67(C), pages 49-59.
    6. 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.
    7. Schneider, Nicolas & Strielkowski, Wadim, 2023. "Modelling the unit root properties of electricity data—A general note on time-domain applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    8. Muhammad Shafiullah & Luke Emeka Okafor & Usman Khalid, 2019. "Determinants of international tourism demand: Evidence from Australian states and territories," Tourism Economics, , vol. 25(2), pages 274-296, March.
    9. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    10. Claudiu Tiberiu Albulescu & Dominique Pépin & Aviral Kumar Tiwari, 2016. "A RE-EXAMINATION OF REAL INTEREST PARITY IN CEECs USING ‘OLD’ AND ‘NEW’ SECOND-GENERATION PANEL UNIT ROOT TESTS," Bulletin of Economic Research, Wiley Blackwell, vol. 68(2), pages 133-150, April.
    11. Chen Qian & Ghulam Rasool Madni, 2022. "Encirclement of Natural Resources, Green Investment, and Economic Complexity for Mitigation of Ecological Footprints in BRI Countries," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    12. Alexander Chudik & M. Hashem Pesaran, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization Institute Working Papers 153, Federal Reserve Bank of Dallas.
    13. Feng, Long & Zhao, Ping & Ding, Yanling & Liu, Binghui, 2021. "Rank-based tests of cross-sectional dependence in panel data models," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    14. Magazzino, Cosimo & Alola, Andrew Adewale & Schneider, Nicolas, 2021. "The trilemma of innovation, logistics performance, and environmental quality in 25 topmost logistics countries: a quantile regression evidence," LSE Research Online Documents on Economics 117654, London School of Economics and Political Science, LSE Library.
    15. Cotte Poveda Alexander, 2011. "Socio-Economic Development and Violence: An Empirical Application for Seven Metropolitan Areas in Colombia," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 17(1), pages 1-23, September.
    16. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    17. Khalid, Usman & Shafiullah, Muhammad, 2021. "Financial development and governance: A panel data analysis incorporating cross-sectional dependence," Economic Systems, Elsevier, vol. 45(2).
    18. Massimiliano Mazzanti & Antonio Musolesi, 2013. "The heterogeneity of carbon Kuznets curves for advanced countries: comparing homogeneous, heterogeneous and shrinkage/Bayesian estimators," Applied Economics, Taylor & Francis Journals, vol. 45(27), pages 3827-3842, September.
    19. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    20. 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.

    More about this item

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ect:emjrnl:v:11:y:2008:i:1:p:105-127. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley-Blackwell Digital Licensing or Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.