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Observation Driven Long Run Equilibria

Author

Listed:
  • Katarzyna Łasak

    (Tinbergen Institute and University of Amsterdam)

  • Johannes Lont

    (Vrije Universiteit Amsterdam)

Abstract

In this paper the Fractional Vector Error Correction Model (FVECM) is extended by allowing three of its parameters to vary with time: the equilibrium relationship parameter $$\beta $$β, the variance $$\sigma ^{2}$$σ2 and the cointegration degree parameter $$b$$b. These parameters are independently updated based on the Generalized Autoregressive Score (GAS) framework. In this way three new FVECM–GAS models are created, and also the concept of ‘time-varying cointegration’ is introduced. Data from these models are simulated, and the models are compared with their fixed parameter counterparts. We show that the FVECM–GAS models perform better in the cases shown here, and thus extend the FVECM model in a useful way. We also note that an approach with fixed parameters may lead to negligence of the cointegration relationship, providing another source of errors.

Suggested Citation

  • Katarzyna Łasak & Johannes Lont, 2020. "Observation Driven Long Run Equilibria," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 551-575, February.
  • Handle: RePEc:kap:compec:v:55:y:2020:i:2:d:10.1007_s10614-019-09903-0
    DOI: 10.1007/s10614-019-09903-0
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    References listed on IDEAS

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    1. Søren Johansen & Morten Ørregaard Nielsen, 2012. "Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model," Econometrica, Econometric Society, vol. 80(6), pages 2667-2732, November.
    2. Katarzyna Lasak, 2008. "Maximum likelihood estimation of fractionally cointegrated systems," CREATES Research Papers 2008-53, Department of Economics and Business Economics, Aarhus University.
    3. Lasak, Katarzyna, 2010. "Likelihood based testing for no fractional cointegration," Journal of Econometrics, Elsevier, vol. 158(1), pages 67-77, September.
    4. 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.
    5. Søren Johansen, 2009. "Representation of Cointegrated Autoregressive Processes with Application to Fractional Processes," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 121-145.
    6. Johansen, SØren, 2008. "A Representation Theory For A Class Of Vector Autoregressive Models For Fractional Processes," Econometric Theory, Cambridge University Press, vol. 24(3), pages 651-676, June.
    7. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
    8. Katarzyna Łasak & Carlos Velasco, 2015. "Fractional Cointegration Rank Estimation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 241-254, April.
    9. 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.
    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.
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