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Near Observational Equivalence and Fractionally Integrated Processes

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  • Francesc Marmol
  • Juan C. Reboredo

Abstract

The aim of this paper is to study the presence of nearly observationally equivalence problems in fractionally integrated processes. In order to illustrate our results, by means of a Monte Carlo study, we analyze the finite sample behaviour of the usual Durbin‐Watson statistic in a regression between two independent nonstationary fractionally integrated processes with MA(1) innovations.

Suggested Citation

  • Francesc Marmol & Juan C. Reboredo, 1999. "Near Observational Equivalence and Fractionally Integrated Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(2), pages 283-290, May.
    • Handle: RePEc:bla:obuest:v:61:y:1999:i:2:p:283-290
    DOI: 10.1111/1468-0084.00129
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    1. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    2. Crato, Nuno & Rothman, Philip, 1994. "Fractional integration analysis of long-run behavior for US macroeconomic time series," Economics Letters, Elsevier, vol. 45(3), pages 287-291.
    3. 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.
    4. Jon Faust, 1993. "Near observational equivalence and unit root processes: formal concepts and implications," International Finance Discussion Papers 447, Board of Governors of the Federal Reserve System (U.S.).
    5. Sowell, Fallaw, 1992. "Modeling long-run behavior with the fractional ARIMA model," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 277-302, April.
    6. Marmol, Francesc, 1998. "Spurious regression theory with nonstationary fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 84(2), pages 233-250, June.
    7. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
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