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Using HP Filtered Data for Econometric Analysis: Some Evidence from Monte Carlo Simulations

  • Mark Meyer

    ()

  • Peter Winker*

    ()

The Hodrick-Prescott (HP) filter has become a widely used tool for detrending integrated time series in applied econometric analysis. Even though the theoretical time series literature sums up an extensive catalogue of severe criticism against an econometric analysis of HP filtered data, the original Hodrick and Prescott (1980, 1997) suggestion to measure the strength of association between (macro-)economic variables by a regression analysis of corresponding HP filtered time series still appears to be popular. A contradictory situation which might be justified only if HP induced distortions were quantitatively negligible in empirical applications. However, this hypothesis can hardly be maintained as the simulation results presented within this paper indicate that HP filtered series give seriously rise to spurious regression results.

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File URL: http://hdl.handle.net/10.1007/s10182-005-0206-9
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Article provided by Springer & German Statistical Society in its journal Allgemeines Statistisches Archiv.

Volume (Year): 89 (2005)
Issue (Month): 3 (August)
Pages: 303-320

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Handle: RePEc:spr:alstar:v:89:y:2005:i:3:p:303-320
DOI: 10.1007/s10182-005-0206-9
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