Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/104132
Authors: 
Schlicht, Ekkehart
Year of Publication: 
2004
Series/Report no.: 
Munich Discussion Paper 2004-2
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.
Subjects: 
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
JEL: 
C22
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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