Selecting the tuning parameter of the ℓ1 trend filter
Yamada Hiroshi (yamada@hiroshima-u.ac.jp) and
Yoon Gawon
Additional contact information
Yamada Hiroshi: Department of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashi-Hiroshima 739-8525, Japan
Yoon Gawon: Department of Economics, Kookmin University, 136–702, S. Korea
Studies in Nonlinear Dynamics & Econometrics, 2016, vol. 20, issue 1, 97-105
Abstract:
The ℓ1 trend filter, which is similar to the popular Hodrick–Prescott (HP) filter, seems to be very promising because it enables us to estimate a piecewise linear trend without specifying the location and number of kink points a priori. Such a trend may be regarded as a result of occasional permanent shocks to the growth rate. Similarly to the HP filter, the value of the tuning parameter needs to be selected in applying this filter. This paper proposes a method for selecting the tuning parameter of the ℓ1 trend filter and its generalization.
Keywords: Hodrick–Prescott filter; lasso; ℓ1 trend filter; sparsity; tuning parameter (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1515/snde-2014-0089 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:20:y:2016:i:1:p:97-105:n:5
Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html
DOI: 10.1515/snde-2014-0089
Access Statistics for this article
Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach
More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla (peter.golla@degruyter.com).