Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171906
Authors: 
Álvarez, Luis J.
Year of Publication: 
2017
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 5 [Year:] 2017 [Issue:] 1 [Pages:] 1-11
Abstract: 
Filters constructed on the basis of standard local polynomial regression (LPR) methods have been used in the literature to estimate the business cycle. We provide a frequency domain interpretation of the contrast filter obtained by the difference of a series and its long-run LPR component and show that it operates as a kind of high-pass filter, so that it provides a noisy estimate of the cycle. We alternatively propose band-pass local polynomial regression methods aimed at isolating the cyclical component. Results are compared to standard high-pass and band-pass filters. Procedures are illustrated using the US GDP series.
Subjects: 
business cycles
local polynomial regression
filtering
high-pass
band-pass
US cycles
JEL: 
C13
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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