Arbeitspapier

Estimating the Smoothing Parameter in the So-Called Hodrick-Prescott Filter

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.

Language
Englisch

Bibliographic citation
Series: Munich Discussion Paper ; No. 2004-2

Classification
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Subject
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

Event
Geistige Schöpfung
(who)
Schlicht, Ekkehart
Event
Veröffentlichung
(who)
Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät
(where)
München
(when)
2004

DOI
doi:10.5282/ubm/epub.304
Handle
URN
urn:nbn:de:bvb:19-epub-304-2
Last update
20.09.2024, 8:21 AM CEST

Data provider

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Object type

  • Arbeitspapier

Associated

  • Schlicht, Ekkehart
  • Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät

Time of origin

  • 2004

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