Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/104449
Authors: 
Bloechl, Andreas
Year of Publication: 
2014
Series/Report no.: 
Munich Discussion Paper 2014-44
Abstract: 
Penalized splines are widespread tools for the estimation of trend and cycle, since they allow a data driven estimation of the penalization parameter by the incorporation into a linear mixed model. Based on the equivalence of penalized splines and the Hodrick-Prescott filter, this paper connects the mixed model framework of penalized splines to the Wiener- Kolmogorov filter. In the case that trend and cycle are described by ARIMA-processes, this filter yields the mean squarred error minimizing estimations of both components. It is shown that for certain settings of the parameters, a penalized spline within the mixed model framework is equal to the Wiener-Kolmogorov filter for a second fold integrated random walk as the trend and a stationary ARMA-process as the cyclical component.
Subjects: 
Hodrick-Prescott filter
mixed models
penalized splines
trend estimation
Wiener-Kolmogorov filter
JEL: 
C22
C52
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.