Business cycle estimation with high-pass and band-pass local polynomial regression
No 1702, Working Papers from Banco de España, Working Papers Homepage
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
New Economics Papers: this item is included in nep-ets and nep-mac
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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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