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A general dependence test and applications

Author

Listed:
  • David Johnson

    (Division of Price and Index Number Research, Bureau of Labor Statistics, 2 Massachusetts Ave., NE, Room 3105, Washington, DC 20212, USA)

  • Robert McClelland

    (Division of Price and Index Number Research, Bureau of Labor Statistics, 2 Massachusetts Ave., NE, Room 3105, Washington, DC 20212, USA)

Abstract

We describe a test, based on the correlation integral, for the independence of a variable and a vector that can be used with serially dependent data. Monte Carlo simulations suggest that the test has good power to detect dependence in several models, performing nearly as well or better than the BDS test in univariate time series and complementing the BDS test in distributed lag models. Finally, we apply our test in conjunction with the BDS test to examine models of US unemployment rates. © 1998 John Wiley & Sons, Ltd.

Suggested Citation

  • David Johnson & Robert McClelland, 1998. "A general dependence test and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(6), pages 627-644.
    • Handle: RePEc:jae:japmet:v:13:y:1998:i:6:p:627-644
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    File URL: http://qed.econ.queensu.ca:80/jae/1998-v13.6/
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    Citations

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    Cited by:

    1. Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," CERGE-EI Working Papers wp235, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    2. Matilla-Garcia, Mariano, 2007. "A non-parametric test for independence based on symbolic dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 31(12), pages 3889-3903, December.
    3. Diks, Cees, 2003. "Detecting serial dependence in tail events: a test dual to the BDS test," Economics Letters, Elsevier, vol. 79(3), pages 319-324, June.
    4. George Kapetanios, 2007. "A Test for Serial Dependence Using Neural Networks," Working Papers 609, Queen Mary University of London, School of Economics and Finance.
    5. Evzen Kocenda & Lubos Briatka, 2005. "Optimal Range for the iid Test Based on Integration Across the Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 265-296.

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