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Generalized runs tests for the IID hypothesis

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  • Cho, Jin Seo
  • White, Halbert

Abstract

We provide a family of tests for the IID hypothesis based on generalized runs, powerful against unspecified alternatives, providing a useful complement to tests 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

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 162 (2011)
Issue (Month): 2 (June)
Pages: 326-344

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Handle: RePEc:eee:econom:v:162:y:2011:i:2:p:326-344

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Web page: http://www.elsevier.com/locate/jeconom

Related research

Keywords: IID condition Runs test Geometric distribution Gaussian process Dependence Structural break;

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