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A Consistent Nonparametric Test for Causality

Author

Listed:
  • Kohtarro Hitomi

    (Institute of Technology, Kyoto University)

  • Yoshinori Kawasaki

    (Institute of Statistical Mathematics)

  • Ryo Okui

    (University of Pennsylvania)

  • Yoshihiko Nishiyama

    (Institute of Economic Research, Kyoto University)

Abstract

We propose a nonparametric test for Granger-type causality. A conceptually similar work will be Hidalgo (2000), who introduced a nonparametric Granger causality test in the frequency domain for weakly stationary linear processes. He is mainly concerned with the test under long range dependent observations, and it does not have a power against some alternatives of series with nonlinear dynamics. We construct a test statistic based on moment conditions allowing for nonlinear dependence. The test has a nontrivial power against T1/2-local alternatives where T is sample size. Its null asymptotic distribution is not normal, but we can easily calculate the critical region by simularion.

Suggested Citation

  • Kohtarro Hitomi & Yoshinori Kawasaki & Ryo Okui & Yoshihiko Nishiyama, 2005. "A Consistent Nonparametric Test for Causality," KIER Working Papers 602, Kyoto University, Institute of Economic Research.
    • Handle: RePEc:kyo:wpaper:602
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    Cited by:

    1. Kunitomo, N. & McAleer, M.J. & Nishiyama, Y., 2010. "Moment Restriction-based Econometric Methods: An Overview," Econometric Institute Research Papers EI 2010-61, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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