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Testing constant cross-sectional dependence with time-varying marginal distributions in parametric models

Author

Listed:
  • Kaldorf Matthias

    (Center for Macroeconomic Research, University of Cologne, Koln, Germany)

  • Wied Dominik

    (Institute for Econometrics and Statistics, University of Cologne, Koln, Germany)

Abstract

This paper proposes parametric two-step procedures for assessing the stability of cross-sectional dependency measures in the presence of potential breaks in the marginal distributions. The procedures are based on formerly proposed sup-LR tests in which restricted and unrestricted likelihood functions are compared with each other. First, we show theoretically that standard asymptotics do not hold in this situation. We propose a suitable bootstrap scheme and derive test statistics in different commonly used settings. The properties of the test statistics and precision of the associated change-point estimator are analysed and compared with existing non-parametric methods in various Monte Carlo simulations. These studies reveal advantages in test power for higher-dimensional data and an almost uniform superiority of the sup-LR test in terms of precision of the change-point estimator. We then apply this method to equity returns of European banks during the financial crisis of 2008.

Suggested Citation

  • Kaldorf Matthias & Wied Dominik, 2022. "Testing constant cross-sectional dependence with time-varying marginal distributions in parametric models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 1-24, February.
    • Handle: RePEc:bpj:sndecm:v:26:y:2022:i:1:p:1-24:n:5
    DOI: 10.1515/snde-2019-0043
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    More about this item

    Keywords

    cumulated sums; empirical copula; structural break; sup-LR test; two-step procedure;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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