Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research
Timothy Cogley () and
James Nason ()
No 93-01, Working Papers in Applied Economic Theory from Federal Reserve Bank of San Francisco
This paper studies the effects of applying the Hodrick-Prescott filter to trend and difference stationary time series. Applying the Hodrick-Prescott filter to an integrated process is similar to detrending a random walk. When the data are difference stationary, the Hodrick-Prescott filter can generate business cycle dynamics even if none are present in the original data. We study the implications for interpreting stylized facts about business cycles and for analyzing data generated by real business cycle models.
Keywords: Business cycles; Time-series analysis (search for similar items in EconPapers)
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Journal Article: Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research (1995)
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