Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195464
Authors: 
Yamada, Hiroshi
Du, Ruixue
Year of Publication: 
2018
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 6 [Year:] 2018 [Issue:] 3 [Pages:] 1-10
Abstract: 
ℓ1 polynomial trend filtering, which is a filtering method described as an ℓ1-norm penalized least-squares problem, is promising because it enables the estimation of a piecewise polynomial trend in a univariate economic time series without prespecifying the number and location of knots. This paper shows some theoretical results on the filtering, one of which is that a small modification of the filtering provides not only identical trend estimates as the filtering but also extrapolations of the trend beyond both sample limits.
Subjects: 
ℓ1 trend filtering
Hodrick–Prescott filtering
Whittaker–Henderson method of graduation
Lasso regression
basis pursuit denoising
total variation denoising
JEL: 
C22
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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