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Tests for Serial Independence and Linearity based on Correlation Integrals

Author

Listed:
  • Cees Diks
  • Sebastiano Manzan

    (CeNDEF, University of Amsterdam)

Abstract

We propose information theoretic tests for serial independence and linearity in time series. The test statisticsare based on the conditional mutual information, a general measure of dependence between lagged variables. In caseof rejecting the null hypothesis, this readily provides insights into the lags through which the dependence arises.The conditional mutual information is estimated using the correlation integral from chaos theory. The signi[tanceof the test statistics is determined with a permutation procedure and a parametric bootstrap in the testsfor serial independence and linearity, respectively.The size and power properties of the tests are examined numerically and illustrated with applications to somebenchmark time series.

Suggested Citation

  • Cees Diks & Sebastiano Manzan, 2001. "Tests for Serial Independence and Linearity based on Correlation Integrals," Tinbergen Institute Discussion Papers 01-085/1, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20010085
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    References listed on IDEAS

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    1. Aparicio F. M. & Escribano A., 1998. "Information-Theoretic Analysis of Serial Dependence and Cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(3), pages 1-24, October.
    2. Diks, C.G.H., 1999. "Consistent Testing for Serial Independence," CeNDEF Working Papers 99-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    3. Yongmiao Hong, 1998. "Testing for pairwise serial independence via the empirical distribution function," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 429-453.
    4. Ngai Hang Chan & Lanh Tat Tran, 1992. "Nonparametric Tests For Serial Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(1), pages 19-28, January.
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    6. P. M. Robinson, 1991. "Consistent Nonparametric Entropy-Based Testing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 437-453.
    7. Hjellvik, Vidar & Yao, Qiwei & Tjostheim, Dag, 1998. "Linearity testing using local polynominal approximation," LSE Research Online Documents on Economics 6638, London School of Economics and Political Science, LSE Library.
    8. Miguel A. Delgado, 1996. "Testing Serial Independence Using The Sample Distribution Function," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(3), pages 271-285, May.
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    More about this item

    Keywords

    serial independence; linearity; bootstrap; permutation test; nonparametric estimation; nonlinear time series analysis; correlation integral;
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