IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v118y2013i2p389-392.html
   My bibliography  Save this article

Recursive predictive tests for structural change of long-memory ARFIMA processes with unknown break points

Author

Listed:
  • Wang, Shin-Huei
  • Vasilakis, Chrysovalantis

Abstract

This paper considers the theoretical justifications of Lütkpohl’s (1988) test statistics when the data-generating process is relaxed to be a stationary ARFIMA process. Under suitable regularity conditions, we prove the applicability of Lütkpohl’s (1988) method to the stationary ARFIMA (p, d, q) process with d∈ (−0.5, 0.5). The practical advantages of our results imply that the potential one or more change points of an ARFIMA process can be detected via recursive predictive tests based on AR regression, even though the exact order of the ARFIMA (p, d, q) is unknown. The spurious break considered in Kuan and Hsu (1998) can also be resolved by Lütkpohl’s (1988) predictive tests, and the simulations conducted in this paper confirm our theoretical results.

Suggested Citation

  • Wang, Shin-Huei & Vasilakis, Chrysovalantis, 2013. "Recursive predictive tests for structural change of long-memory ARFIMA processes with unknown break points," Economics Letters, Elsevier, vol. 118(2), pages 389-392.
  • Handle: RePEc:eee:ecolet:v:118:y:2013:i:2:p:389-392
    DOI: 10.1016/j.econlet.2012.11.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512006015
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. D. Poskitt, 2007. "Autoregressive approximation in nonstandard situations: the fractionally integrated and non-invertible cases," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(4), pages 697-725, December.
    2. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    3. Hidalgo, Javier & Robinson, Peter M., 1996. "Testing for structural change in a long-memory environment," Journal of Econometrics, Elsevier, vol. 70(1), pages 159-174, January.
    4. Lutkepohl, Helmut, 1988. "Prediction tests for structural stability," Journal of Econometrics, Elsevier, vol. 39(3), pages 267-296, November.
    5. Hosking, Jonathan R. M., 1996. "Asymptotic distributions of the sample mean, autocovariances, and autocorrelations of long-memory time series," Journal of Econometrics, Elsevier, vol. 73(1), pages 261-284, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Structural breaks; Predictive tests; Long memory;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:118:y:2013:i:2:p:389-392. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.