Business cycle estimation with high-pass and band-pass local polynomial regression

Luis Alvarez

No 1702, Working Papers from Banco de España

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 between a series and its long-run LPR component and show that it operates as a kind of high-pass filter, meaning 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.

Keywords: business cycles; local polynomial regression; filtering; high-pass; band-pass; US cycles (search for similar items in EconPapers)
JEL-codes: C13 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2017-01
New Economics Papers: this item is included in nep-ets and nep-mac
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http://www.bde.es/f/webbde/SES/Secciones/Publicaci ... /17/Fich/dt1702e.pdf First version, January 2017 (application/pdf)

Related works:
Journal Article: Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:bde:wpaper:1702

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