Why You Should Never Use the Hodrick-Prescott Filter

James D. Hamilton

No 23429, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Here's why. (1) The HP filter produces series with spurious dynamic relations that have no basis in the underlying data-generating process. (2) Filtered values at the end of the sample are very different from those in the middle, and are also characterized by spurious dynamics. (3) A statistical formalization of the problem typically produces values for the smoothing parameter vastly at odds with common practice, e.g., a value for λ far below 1600 for quarterly data. (4) There's a better alternative. A regression of the variable at date t+h on the four most recent values as of date t offers a robust approach to detrending that achieves all the objectives sought by users of the HP filter with none of its drawbacks.

JEL-codes: C22 E32 E47 (search for similar items in EconPapers)
Date: 2017-05
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-ets and nep-mac
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Citations: View citations in EconPapers (176)

Published as James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, vol 100(5), pages 831-843.

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