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Spurious regression under broken trend stationarity

  • Antonio E. Noriega

    ()

    (Department of Economics and Finance, Universidad de Guanajuato)

  • Daniel Ventosa-Santaularia

    ()

    (Department of Economics and Finance, Universidad de Guanajuato)

We study the phenomenon of spurious regression between two random variables, when the generating mechanism of individual series is assumed to follow a stationary process around a trend with (possibly) multiple breaks in the level and slope of trend. We develop the relevant asymptotic theory and show that the phenomenon of spurious regression occurs independently of the structure assumed for the errors. In contrast to previous findings, the presence of a spurious relationship will be less severe when breaks are present in the generating mechanism of individual series. This is true whether the regression model includes a linear trend or not. Simulations confirm our asymptotic results, and reveal that in finite samples, the phenomenon of spurious regression is sensitive to the presence of a linear trend in the regression model, and to the relative location of breaks within the sample.

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File URL: http://economia.ugto.org/WorkingPapers/EM200501.pdf
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Paper provided by Universidad de Guanajuato, Department of Economics and Finance in its series Department of Economics and Finance Working Papers with number EM200501.

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Length: 19 pages
Date of creation: Jan 2005
Publication status: Published in Journal of Time Series Analysis (2006)
Handle: RePEc:gua:wpaper:em200501
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