IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpem/0311007.html
   My bibliography  Save this paper

Examination Of Some More Powerful Modifications Of The Dickey- Fuller Test

Author

Listed:
  • Steve Leybourne

    (Nottingham)

  • Paul Newbold

    (Nottingham)

  • Tae-Hwan Kim

    (Nottingham)

Abstract

Although the t-ratio variant of the Dickey-Fuller test is the most commonly applied unit root test in practical applications, it has been known for some time that readily implementable, more powerful modifications are available. We explore the large sample properties of five of these modified tests, and the small sample properties of these five plus six hybrids. As a result of this study we recommend two particular test procedures.

Suggested Citation

  • Steve Leybourne & Paul Newbold & Tae-Hwan Kim, 2003. "Examination Of Some More Powerful Modifications Of The Dickey- Fuller Test," Econometrics 0311007, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0311007
    Note: Type of Document -
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0311/0311007.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dong Wan Shin & Beong Soo So, 2001. "recursive Mean Adjustment for Unit Root Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(5), pages 595-612, September.
    2. Leybourne, S J, 1995. "Testing for Unit Roots Using Forward and Reverse Dickey-Fuller Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(4), pages 559-571, November.
    3. 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.
    4. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    5. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    6. Pantula, Sastry G & Gonzalez-Farias, Graciela & Fuller, Wayne A, 1994. "A Comparison of Unit-Root Test Criteria," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 449-459, October.
    7. Ng, S. & Perron, P., 1994. "Unit Root Tests ARMA Models with Data Dependent Methods for the Selection of the Truncation Lag," Cahiers de recherche 9423, Universite de Montreal, Departement de sciences economiques.
    8. 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.
    9. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    10. Taylor, A M Robert, 2002. "Regression-Based Unit Root Tests with Recursive Mean Adjustment for Seasonal and Nonseasonal Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 269-281, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jürgen Wolters & Uwe Hassler, 2006. "Unit Root Testing," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 4, pages 41-56, Springer.
    2. Murray, Christian J. & Nelson, Charles R., 2000. "The uncertain trend in U.S. GDP," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 79-95, August.
    3. Sánchez, Ismael, 2000. "Spectral density estimators at frequency zero for nonstationarity tests in arma models," DES - Working Papers. Statistics and Econometrics. WS 10132, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    5. Paulo M. M. Rodrigues, 2013. "Recursive adjustment, unit root tests and structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 62-82, January.
    6. Ismael Sánchez, 2004. "Implementing unit roost tests in ARMA models of unknow order," Statistical Papers, Springer, vol. 45(2), pages 249-266, April.
    7. Norman J. Morin & John M. Roberts, 1999. "Is hysteresis important for U.S. unemployment?," Finance and Economics Discussion Series 1999-56, Board of Governors of the Federal Reserve System (U.S.).
    8. Isabel Cortés-Jiménez & Manuel Artís, 2005. "The role of the tourism sector in economic development - Lessons from the Spanish experience," ERSA conference papers ersa05p488, European Regional Science Association.
    9. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Mean and variance causality between the Cyprus Stock Exchange and major equity markets," Working Papers 0501, University of Crete, Department of Economics.
    10. Eleni Constantinou & Avo Kazandjian & Georgios P. Kouretas & Vera Tahmazian, 2008. "Common Stochastic Trends Among The Cyprus Stock Exchange And The Ase, Lse And Nyse," Bulletin of Economic Research, Wiley Blackwell, vol. 60(4), pages 327-349, October.
    11. António Portugal Duarte & João Sousa Andrade, 2012. "How the Gold Standard functioned in Portugal: an analysis of some macroeconomic aspects," Applied Economics, Taylor & Francis Journals, vol. 44(5), pages 617-629, February.
    12. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    13. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    14. Charles Nelson & Jeremy Piger & Eric Zivot, 1999. "Unit Root Tests in the Presence of Markov Regime-Switching," Discussion Papers in Economics at the University of Washington 0040, Department of Economics at the University of Washington.
    15. Steven Cook, 2003. "The nonstationarity of the consumption-income ratio: Evidence from more powerful Dickey-Fuller tests," Applied Economics Letters, Taylor & Francis Journals, vol. 10(7), pages 393-395.
    16. Vicente Esteve & Francisco Requena, 2006. "A Cointegration Analysis of Car Advertising and Sales Data in the Presence of Structural Change," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 13(1), pages 111-128.
    17. Sanchez, Ismael, 1998. "Testing for Unit Roots with Prediction Errors," University of California at San Diego, Economics Working Paper Series qt8pc6n1j8, Department of Economics, UC San Diego.
    18. Robert A. Amano & Wai-Ming Ho & Tony S. Wirjanto, 1999. "Intraperiod and Intertemporal Substitution in Import Demand," Cahiers de recherche CREFE / CREFE Working Papers 84, CREFE, Université du Québec à Montréal.
    19. Steven Cook, 2005. "Estimating the autoregressive parameter: recursive mean adjustment and the initial condition," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 203-206.
    20. Stephen Leybourne & A. M. Robert Taylor, 2003. "Seasonal Unit Root Tests Based on Forward and Reverse Estimation," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 441-460, July.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    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:wpa:wuwpem:0311007. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.