IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v24y2004i3p239-255.html
   My bibliography  Save this article

The Exact Maximum Likelihood-Based Test for Fractional Cointegration: Critical Values, Power and Size

Author

Listed:
  • Emmanuel Dubois
  • Sandrine Lardic
  • Valérie Mignon

Abstract

The exact maximum likelihood (EML) procedure can be used as a residual-based test of the hypothesis of no cointegration against the alternative of fractional cointegration. Since the corresponding asymptotic properties have not yet been established, this paper provides simulated critical values, power and size relating to the EML-based test for fractional cointegration. Monte Carlo simulations indicate that the simulated density of the EML-based test is shifted to the left compared to the standard normal distribution and exhibits a strong excess of kurtosis in the absence of autoregressive components in the regression residuals. The power and size comparison indicates that the EML-based test is more powerful than other fractional cointegration tests (Lo, Lobato-Robinson and Geweke and Porter-Hudak) in small and medium sample sizes. Moreover, by simulating integrated time series with AR(1), and respectively MA(1), disturbances, it is shown that, whatever the sample size, the EML-based test exhibits the lowest size distortions for positive AR(1) and negative MA(1) coefficients, respectively. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Emmanuel Dubois & Sandrine Lardic & Valérie Mignon, 2004. "The Exact Maximum Likelihood-Based Test for Fractional Cointegration: Critical Values, Power and Size," Computational Economics, Springer;Society for Computational Economics, vol. 24(3), pages 239-255, July.
  • Handle: RePEc:kap:compec:v:24:y:2004:i:3:p:239-255
    DOI: 10.1007/s10614-004-3544-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-004-3544-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10614-004-3544-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ignacio N. Lobato & Peter M. Robinson, 1998. "A Nonparametric Test for I(0)," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 475-495.
    2. Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June.
    3. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    4. Doornik, Jurgen A. & Ooms, Marius, 2003. "Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 333-348, March.
    5. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    6. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    7. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    8. W. L. Chou & Y. C. Shih, 1997. "Long-run purchasing power parity and long-term memory: evidence from Asian newly industrialized countries," Applied Economics Letters, Taylor & Francis Journals, vol. 4(9), pages 575-578.
    9. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
    10. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    11. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    12. Ooms, M. & Doornik, J.A., 1999. "Inference and Forecasting for Fractional Autoregressive Integrated Moving Average Models, with an application to US and UK inflation," Econometric Institute Research Papers EI 9947/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marcel Aloy & Gilles de Truchis, 2012. "Estimation and Testing for Fractional Cointegration," Working Papers halshs-00793206, HAL.
    2. Marco R. Barassi & Gianluigi De Pascale & Raffaele Lagravinese, 2021. "Testing the law of one-price in the US gasoline market: a long memory approach," SERIES 03-2021, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Jun 2021.
    3. Valérie Mignon & Sandrine Lardic, 2003. "Cointégration fractionnaire entre la consommation et le revenu," Économie et Prévision, Programme National Persée, vol. 158(2), pages 123-142.
    4. Dufrénot, Gilles & Lardic, Sandrine & Mathieu, Laurent & Mignon, Valérie & Péguin-Feissolle, Anne, 2008. "Explaining the European exchange rates deviations: Long memory or non-linear adjustment?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 207-215, July.
    5. M.Y. TEWELDEMEDHIN & H.D. VAN SCHALKWYK & Rena RAVINDER, 2009. "The Agricultural Industry And Economic Growth In South Africa – An Empirical Analysis," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 4, pages 43-56, November.

    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. Henryk Gurgul & Tomasz Wójtowicz, 2006. "Long-run properties of trading volume and volatility of equities listed in DJIA index," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(3-4), pages 29-56.
    2. Valerie Mignon & Sandrine Lardic, 2004. "The exact maximum likelihood estimation of ARFIMA processes and model selection criteria: A Monte Carlo study," Economics Bulletin, AccessEcon, vol. 3(21), pages 1-16.
    3. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    4. repec:ebl:ecbull:v:3:y:2004:i:21:p:1-16 is not listed on IDEAS
    5. Javier Hualde & Morten {O}rregaard Nielsen, 2022. "Fractional integration and cointegration," Papers 2211.10235, arXiv.org.
    6. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    7. Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 405-443.
    8. repec:ebl:ecbull:v:3:y:2003:i:14:p:1-10 is not listed on IDEAS
    9. Tomasz Wójtowicz & Henryk Gurgul, 2009. "Long memory of volatility measures in time series," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(1), pages 37-54.
    10. Paramsothy Silvapulle, 2001. "A Score Test For Seasonal Fractional Integration And Cointegration," Econometric Reviews, Taylor & Francis Journals, vol. 20(1), pages 85-104.
    11. Elkin Castaño & Santiago Gallón & Karoll Gómez, 2010. "Estimation Biases, Size and Power of a Test on the Long Memory Parameter in ARFIMA Models," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 73, pages 131-148.
    12. S. Lardic & V. Mignon, 2002. "Term premium and long-range dependence in volatility : A FIGARCH-M estimation on some Asian countries," THEMA Working Papers 2002-26, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    13. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    14. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    15. Castano Vélez, Elkin & Gallón Gómez, Santiago Alejandro & Gómez Portilla, Karoll, 2011. "Sesgos en estimación, tamano y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA," Revista Lecturas de Economía, Universidad de Antioquia, CIE, February.
    16. Mauro Coli & Lara Fontanella & Mariagrazia Granturco, 2005. "Parametric estimation for ARFIMA models via spectral methods," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(1), pages 11-27, February.
    17. Ana Pérez & Esther Ruiz, 2002. "Modelos de memoria larga para series económicas y financieras," Investigaciones Economicas, Fundación SEPI, vol. 26(3), pages 395-445, September.
    18. Valérie Mignon & Sandrine Lardic, 2003. "Cointégration fractionnaire entre la consommation et le revenu," Économie et Prévision, Programme National Persée, vol. 158(2), pages 123-142.
    19. Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
    20. Koop, Gary & Ley, Eduardo & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian analysis of long memory and persistence using ARFIMA models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 149-169.
    21. Geoffrey Ngene & Ann Nduati Mungai & Allen K. Lynch, 2018. "Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-38, June.
    22. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.

    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:kap:compec:v:24:y:2004:i:3:p:239-255. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.