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

Series: Working Papers. 1702.

Author: Luis J. Álvarez.

Topics: Quantitative methods | Non-financial corporations, businesses | International Economy | Economic situation | Banco de España.

Published in: Econometrics 2017, 5(1), 1

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Business cycle estimation with high-pass and band-pass local polynomial regression (653 KB)

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.