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Generalized Runs Test for the IID Hypothesis

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  • Jin Seo Cho

    ()
    (Department of Economics, Korea University, Seoul, South Korea)

  • Halbert White

    ()
    (Department of Economics, University of California, San Diego, U.S.A.)

Abstract

We provide a familiy of tests for the IID hypothesis based on generalized runs, powerful against unspecified alternatives, providing a useful complement to test designed for specific alternatives, such as serial correlation, GARCH, or structural breaks. Our tests have appealing computational simplicity in that they do not require kernel density estimation, with the associated challenge of bandwidth selection. Simulations show levels close to nominal asymptotic levels.Our tests have power against both dependent and heterogeneous alternatives, as both theory and simulations demonstrate.

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Bibliographic Info

Paper provided by Institute of Economic Research, Korea University in its series Discussion Paper Series with number 0913.

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Length: 85 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:iek:wpaper:0913

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Keywords: IID condition; Runs test; Geometric Distribution; Gaussian process; Dependence; Structural Break;

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