Abstract
This note gives a fairly complete statistical description of the Hodrick-Prescott Filter (1997), originally proposed by Leser (1961). It builds on an approach to seasonal adjustment suggested by Leser (1963) and Schlicht (1981, 1984). A moments estimator for the smoothing parameter is proposed that is asymptotically equivalent to the maximum-likelihood estimator, has a straightforward intuitive interpretation and is more appropriate for short series than the maximum-likelihood estimator. The method is illustrated by an application and several simulations.
Item Type: | Paper |
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Keywords: | Hodrick-Prescott filter, Kalman filter, Kalman-Bucy, Whittaker-Henderson graduation, spline, state-space models, random walk, time-varying coefficients, adaptive estimation, time-series, seasonal adjustment, trend |
Faculties: | Economics Economics > Munich Discussion Papers in Economics Economics > Munich Discussion Papers in Economics > Statistical Methods Economics > Chairs > Chair of Institutional Economics (closed) |
Subjects: | 300 Social sciences > 300 Social sciences, sociology and anthropology 300 Social sciences > 330 Economics |
JEL Classification: | C22 |
URN: | urn:nbn:de:bvb:19-epub-304-2 |
Language: | English |
Item ID: | 304 |
Date Deposited: | 13. Apr 2005 |
Last Modified: | 05. Nov 2020, 05:45 |