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Moving estimates test with time varying bandwidth

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  • Na, Okyoung
  • Lee, Sangyeol
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    Abstract

    In this paper, we consider the problem of testing for parameter changes in time series models based on a moving estimates (ME) test. It is widely accepted that detecting some changes, for instance, those caused by temporary parameter shifts by the existing cusum test is difficult. A MV test with a fixed bandwidth has been developed to circumvent the defect, but the test still does not perform well under certain conditions. Motivated by this, we propose a MV test with a time varying bandwidth to outperform the original test. In order to illustrate our findings, we have provided simulation results.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 98 (2007)
    Issue (Month): 7 (August)
    Pages: 1356-1375

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    Handle: RePEc:eee:jmvana:v:98:y:2007:i:7:p:1356-1375

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    Related research

    Keywords: Test for parameter change Moving estimates test Cusum test Time series Strong mixing processes;

    References

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    1. Sangyeol Lee & Okyoung Na & Seongryong Na, 2003. "On the cusum of squares test for variance change in nonstationary and nonparametric time series models," Annals of the Institute of Statistical Mathematics, Springer, vol. 55(3), pages 467-485, September.
    2. Lee, Sangyeol & Na, Okyoung, 2005. "Test for parameter change in stochastic processes based on conditional least-squares estimator," Journal of Multivariate Analysis, Elsevier, vol. 93(2), pages 375-393, April.
    3. Sangyeol Lee & Jeongcheol Ha & Okyoung Na & Seongryong Na, 2003. "The Cusum Test for Parameter Change in Time Series Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 30(4), pages 781-796.
    4. Chu, Chia-Shang James & Hornik, Kurt & Kuan, Chung-Ming, 1995. "The Moving-Estimates Test for Parameter Stability," Econometric Theory, Cambridge University Press, vol. 11(04), pages 699-720, August.
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    Cited by:
    1. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
    2. C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.

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