Estimating the Smoothing Parameter in the So-Called Hodrick-Prescott Filter - Ekkehart Schlicht (Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät, 2004)
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.
urn:nbn:de:bvb:19-epub-304-2
Keywords: C22; 330; 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