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Maximum likelihood estimation of the multivariate fractional cointegrating model

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  • Lyhagen, Johan

    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

Departures from an economic equilibrium should be mean reverting. The deviations are often assumed to be integrated of order zero but this is too restrictive. It is sufficient that the shocks are integrated of an order less than one, i.e. they may be fractionally integrated. A fractionally cointegrated system is developed. Further, estimation and testing are discussed, analytically and by Monte Carlo simulations. The Monte Carlo simulations shows that it is much more severe to ignore fractional cointegration than incorporating it when it is not present.

Suggested Citation

  • Lyhagen, Johan, 1998. "Maximum likelihood estimation of the multivariate fractional cointegrating model," SSE/EFI Working Paper Series in Economics and Finance 233, Stockholm School of Economics.
    • Handle: RePEc:hhs:hastef:0233
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    References listed on IDEAS

    as
    1. 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.
    2. Baillie, Richard T & Bollerslev, Tim, 1994. "Cointegration, Fractional Cointegration, and Exchange Rate Dynamics," Journal of Finance, American Finance Association, vol. 49(2), pages 737-745, June.
    3. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    4. Andersson, Michael K. & Gredenhoff, Mikael P., 1998. "Power and Bias of Likelihood Based Inference in the Cointegration Model under Fractional Cointegration," SSE/EFI Working Paper Series in Economics and Finance 221, Stockholm School of Economics.
    5. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    6. Li, Hongyi & Maddala, G. S., 1997. "Bootstrapping cointegrating regressions," Journal of Econometrics, Elsevier, vol. 80(2), pages 297-318, October.
    7. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    8. Hylleberg, Svend & Mizon, Grayham E, 1989. "Cointegration and Error Correction Mechanisms," Economic Journal, Royal Economic Society, vol. 99(395), pages 113-125, Supplemen.
    9. Banerjee, Anindya & Dolado, Juan J. & Galbraith, John W. & Hendry, David, 1993. "Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data," OUP Catalogue, Oxford University Press, number 9780198288107.
    10. G. Geoffrey Booth & Yiuman Tse, 1995. "Long memory in interest rate futures markets: A fractional cointegration analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(5), pages 573-584, August.
    11. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    12. Cheung, Yin-Wong & Lai, Kon S, 1993. "A Fractional Cointegration Analysis of Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 103-112, January.
    13. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    14. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    15. Sowell, Fallaw, 1990. "The Fractional Unit Root Distribution," Econometrica, Econometric Society, vol. 58(2), pages 495-505, March.
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    Citations

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    Cited by:

    1. Lasak, Katarzyna, 2010. "Likelihood based testing for no fractional cointegration," Journal of Econometrics, Elsevier, vol. 158(1), pages 67-77, September.
    2. Kirstin Hubrich & Helmut Lutkepohl & Pentti Saikkonen, 2001. "A Review Of Systems Cointegration Tests," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 247-318.
    3. Simwaka, Kisu, 2012. "Time varying fractional cointegration," MPRA Paper 39505, University Library of Munich, Germany.
    4. Katarzyna Łasak & Carlos Velasco, 2015. "Fractional Cointegration Rank Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 241-254, April.
    5. Katarzyna Lasak, 2008. "Maximum likelihood estimation of fractionally cointegrated systems," CREATES Research Papers 2008-53, Department of Economics and Business Economics, Aarhus University.

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    More about this item

    Keywords

    Fractional integration; Granger representation theorem; Likelihood ratio test; Monte Carlo.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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