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On Testing for Diagonality of Large Dimensional Covariance Matrices

Author

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  • George Kapetanios

    (Queen Mary, University of London)

Abstract

Datasets in a variety of disciplines require methods where both the sample size and the dataset dimensionality are allowed to be large. This framework is drastically different from the classical asymptotic framework where the number of observations is allowed to be large but the dimensionality of the dataset remains fixed. This paper proposes a new test of diagonality for large dimensional covariance matrices. The test is based on the work of John (1971) and Ledoit and Wolf (2002) among others. The theoretical properties of the test are discussed. A Monte Carlo study of the small sample properties of the test indicate that it behaves well under the null hypothesis and has superior power properties compared to an existing test of diagonality for large datasets.

Suggested Citation

  • George Kapetanios, 2004. "On Testing for Diagonality of Large Dimensional Covariance Matrices," Working Papers 526, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:526
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    File URL: https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/2004/items/wp526.pdf
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    References listed on IDEAS

    as
    1. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    2. Chang, Yoosoon, 2002. "Nonlinear IV unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 110(2), pages 261-292, October.
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    Cited by:

    1. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2012. "A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model," Journal of Econometrics, Elsevier, vol. 170(1), pages 164-177.
    2. Badi H. Baltagi & Qu Feng & Chihwa Kao, 2009. "Testing for Sphericity in a Fixed Effects Panel Data Model (Revised July 2009)," Center for Policy Research Working Papers 112, Center for Policy Research, Maxwell School, Syracuse University.

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    More about this item

    Keywords

    Panel data; Large sample covariance matrix; Maximum eigenvalue;
    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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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