Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression
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 t...
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| Language: | English |
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MDPI AG
2017-01-01
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| Series: | Econometrics |
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| Online Access: | http://www.mdpi.com/2225-1146/5/1/1 |
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doaj-6ac6d8c93abe496489550ebc780081bf2020-11-24T22:52:26ZengMDPI AGEconometrics2225-11462017-01-0151110.3390/econometrics5010001econometrics5010001Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial RegressionLuis J. Álvarez0Banco de España, Madrid 28014, SpainFilters 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.http://www.mdpi.com/2225-1146/5/1/1business cycleslocal polynomial regressionfilteringhigh-passband-passUS cycles |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Luis J. Álvarez |
| spellingShingle |
Luis J. Álvarez Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression Econometrics business cycles local polynomial regression filtering high-pass band-pass US cycles |
| author_facet |
Luis J. Álvarez |
| author_sort |
Luis J. Álvarez |
| title |
Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression |
| title_short |
Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression |
| title_full |
Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression |
| title_fullStr |
Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression |
| title_full_unstemmed |
Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression |
| title_sort |
business cycle estimation with high-pass and band-pass local polynomial regression |
| publisher |
MDPI AG |
| series |
Econometrics |
| issn |
2225-1146 |
| publishDate |
2017-01-01 |
| description |
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. |
| topic |
business cycles local polynomial regression filtering high-pass band-pass US cycles |
| url |
http://www.mdpi.com/2225-1146/5/1/1 |
| work_keys_str_mv |
AT luisjalvarez businesscycleestimationwithhighpassandbandpasslocalpolynomialregression |
| _version_ |
1725666203798601728 |