Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression

Luis Alvarez

Econometrics, 2017, vol. 5, issue 1, 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.

Keywords: business cycles; local polynomial regression; filtering; high-pass; band-pass; US cycles (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2017
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Working Paper: Business cycle estimation with high-pass and band-pass local polynomial regression (2017)
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