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An Alternative Approach For Testing For Linear Association For Two Independent Stationary Ar(1) Processes

Author

Listed:
  • Christos Agiakloglou

    (Economics - University of Piraeus)

Abstract

Spurious correlations occur when two independent time series are found to be correlated according to the typical statistical procedure for testing the null hypothesis of zero correlation in the population. Using a Monte Carlo analysis, this study examines the spurious correlation phenomenon for two independent stationary AR(1) processes and it finds that if an alternative testing procedure is applied to these two series, the spurious behavior is eliminated using the variance of the sample correlation coefficient of these two series, suggested by Bartlett (1935).

Suggested Citation

  • Christos Agiakloglou, 2011. "An Alternative Approach For Testing For Linear Association For Two Independent Stationary Ar(1) Processes," Post-Print hal-00730233, HAL.
    • Handle: RePEc:hal:journl:hal-00730233
    DOI: 10.1080/00036846.2011.595695
    Note: View the original document on HAL open archive server: https://hal.science/hal-00730233
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    References listed on IDEAS

    as
    1. Clive Granger & Namwon Hyung & Yongil Jeon, 2001. "Spurious regressions with stationary series," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 899-904.
    2. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    3. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    4. 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.
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