Generalized runs tests for the IID hypothesis

Jin Seo Cho, Halbert White

Research output: Contribution to journalArticle

14 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)326-344
Number of pages19
JournalJournal of Econometrics
Volume162
Issue number2
DOIs
Publication statusPublished - 2011 Jun 1

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

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