IDEAS home Printed from https://ideas.repec.org/p/pur/prukra/1303.html
   My bibliography  Save this paper

A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence

Author

Listed:
  • Mohitosh Kejriwal

Abstract

This paper proposes a new procedure for estimating the number of structural changes in the persistence of a univariate time series. In contrast to the extant literature that primarily assumes (regime-wise) stationarity, our framework also allows the underlying stochastic process to switch between stationary [I(0)] and unit root [I(1)] regimes. We develop a sequential testing approach based on the simultaneous application of two Wald-type tests for structural change, one of which assumes the process is I(0)-stable under the null hypothesis while the other assumes the stable I(1) model as the null hypothesis. This feature allows the procedure to maintain correct asymptotic size regardless of whether the regimes are I(0) or I(1). We also propose a novel procedure for distinguishing processes with pure level and/or trend shifts from those that are also subject to concurrent shifts in persistence. The large sample properties of the recommended procedures are derived and the relevant asymptotic critical values tabulated. Our Monte Carlo experiments demonstrate that the advocated approach compares favorably relative to the commonly employed approach based on I(0) sequential testing, especially when the data contain an I(1) segment.

Suggested Citation

  • Mohitosh Kejriwal, 2017. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Purdue University Economics Working Papers 1303, Purdue University, Department of Economics.
  • Handle: RePEc:pur:prukra:1303
    as

    Download full text from publisher

    File URL: http://www.krannert.purdue.edu/programs/phd/working-papers-series/2017/1303-MohitoshKejriwal.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Marianne Sensier & Dick van Dijk, 2004. "Testing for Volatility Changes in U.S. Macroeconomic Time Series," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 833-839, August.
    2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    3. Kejriwal, Mohitosh & Perron, Pierre, 2010. "Testing for Multiple Structural Changes in Cointegrated Regression Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 503-522.
    4. Perron, Pierre & Qu, Zhongjun, 2006. "Estimating restricted structural change models," Journal of Econometrics, Elsevier, vol. 134(2), pages 373-399, October.
    5. Eiji Kurozumi, 2005. "Detection of Structural Change in the Long-run Persistence in a Univariate Time Series," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 181-206, April.
    6. Elliott, Graham, 1999. "Efficient Tests for a Unit Root When the Initial Observation Is Drawn from Its Unconditional Distribution," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(3), pages 767-783, August.
    7. Kejriwal, Mohitosh & Perron, Pierre, 2012. "A note on estimating a structural change in persistence," Economics Letters, Elsevier, vol. 117(3), pages 932-935.
    8. Yao, Yi-Ching, 1988. "Estimating the number of change-points via Schwarz' criterion," Statistics & Probability Letters, Elsevier, vol. 6(3), pages 181-189, February.
    9. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    10. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2008. "Testing for a change in persistence in the presence of non-stationary volatility," Journal of Econometrics, Elsevier, vol. 147(1), pages 84-98, November.
    11. Kejriwal, Mohitosh & Perron, Pierre & Zhou, Jing, 2013. "Wald Tests For Detecting Multiple Structural Changes In Persistence," Econometric Theory, Cambridge University Press, vol. 29(02), pages 289-323, April.
    12. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
    13. Stephen Leybourne & Tae-Hwan Kim & Vanessa Smith & Paul Newbold, 2003. "Tests for a change in persistence against the null of difference-stationarity," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 291-311, December.
    14. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    15. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    16. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    17. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, June.
    18. Chih-Chiang Hsu & Chung-Ming Kuan, 2001. "Distinguishing between trend-break models: method and empirical evidence," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-1.
    19. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    20. Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
    21. Busetti, Fabio & Taylor, A. M. Robert, 2004. "Tests of stationarity against a change in persistence," Journal of Econometrics, Elsevier, vol. 123(1), pages 33-66, November.
    22. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    23. A. M. Robert Taylor, 2005. "Fluctuation Tests for a Change in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(2), pages 207-230, April.
    24. Kim, Jae-Young, 2000. "Detection of change in persistence of a linear time series," Journal of Econometrics, Elsevier, vol. 95(1), pages 97-116, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    multiple structural changes; unit root; stationary; sequential procedure; Wald tests;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pur:prukra:1303. 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: (Krannert PHD). General contact details of provider: http://edirc.repec.org/data/kspurus.html .

    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.