IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v5y2017i1p1-d86946.html
   My bibliography  Save this article

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

Author

Listed:
  • Luis J. Álvarez

    (Banco de España, Madrid 28014, Spain)

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.

Suggested Citation

  • Luis J. Álvarez, 2017. "Business Cycle Estimation with High-Pass and Band-Pass Local Polynomial Regression," Econometrics, MDPI, vol. 5(1), pages 1-11, January.
    • Handle: RePEc:gam:jecnmx:v:5:y:2017:i:1:p:1-:d:86946
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/5/1/1/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2225-1146/5/1/1/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    2. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    3. Edward E. Leamer, 2007. "Housing is the business cycle," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 149-233.
    4. D. S. G. Pollock, 2016. "Econometric Filters," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 669-691, December.
    5. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    6. Estela Bee Dagum & Alessandra Luati, 2009. "A Cascade Linear Filter to Reduce Revisions and False Turning Points for Real Time Trend-Cycle Estimation," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 40-59.
    7. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aastveit, Knut Are & Trovik, Tørres, 2014. "Estimating the output gap in real time: A factor model approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 180-193.
    2. Maravall, A. & del Rio, A., 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 975-998, October.
    3. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    4. Lubik, Thomas A. & Matthes, Christian & Verona, Fabio, 2019. "Assessing U.S. aggregate fluctuations across time and frequencies," Bank of Finland Research Discussion Papers 5/2019, Bank of Finland.
    5. Pontines, Victor, 2017. "The financial cycles in four East Asian economies," Economic Modelling, Elsevier, vol. 65(C), pages 51-66.
    6. Michaelides, Panayotis G. & Milios, John G. & Konstantakis, Konstantinos N. & Tarnaras, Panayiotis, 2015. "Quantity-of-money fluctuations and economic instability: empirical evidence for the USA (1958–2006)," MPRA Paper 90145, University Library of Munich, Germany.
    7. L.A. Gil-Alana, 2005. "Fractional Cyclical Structures & Business Cycles in the Specification of the US Real Output," European Research Studies Journal, European Research Studies Journal, vol. 0(1-2), pages 99-126.
    8. Aadland, David, 2005. "Detrending time-aggregated data," Economics Letters, Elsevier, vol. 89(3), pages 287-293, December.
    9. Durech, Richard & Minea, Alexandru & Mustea, Lavinia & Slusna, Lubica, 2014. "Regional evidence on Okun's Law in Czech Republic and Slovakia," Economic Modelling, Elsevier, vol. 42(C), pages 57-65.
    10. Heer, Burkhard & Süssmuth, Bernd, 2013. "Tax bracket creep and its effects on income distribution," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 393-408.
    11. Odia Ndongo, Yves Francis, 2006. "Datation du Cycle du PIB Camerounais entre 1960 et 2003," MPRA Paper 552, University Library of Munich, Germany.
    12. Berger, Tino & Richter, Julia & Wong, Benjamin, 2022. "A unified approach for jointly estimating the business and financial cycle, and the role of financial factors," Journal of Economic Dynamics and Control, Elsevier, vol. 136(C).
    13. Fukuda, Kosei, 2009. "Measuring major and minor cycles in univariate economic time series," Economic Modelling, Elsevier, vol. 26(5), pages 1093-1100, September.
    14. Perron, Pierre & Wada, Tatsuma, 2009. "Let's take a break: Trends and cycles in US real GDP," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 749-765, September.
    15. Ghate, Chetan & Pandey, Radhika & Patnaik, Ila, 2013. "Has India emerged? Business cycle stylized facts from a transitioning economy," Structural Change and Economic Dynamics, Elsevier, vol. 24(C), pages 157-172.
    16. James B. Bullard & John Duffy, 2004. "Learning and structural change in macroeconomic data," Working Papers 2004-016, Federal Reserve Bank of St. Louis.
    17. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    18. Han, Yang & Liu, Zehao & Ma, Jun, 2020. "Growth cycles and business cycles of the Chinese economy through the lens of the unobserved components model," China Economic Review, Elsevier, vol. 63(C).
    19. Rand, John & Tarp, Finn, 2002. "Business Cycles in Developing Countries: Are They Different?," World Development, Elsevier, vol. 30(12), pages 2071-2088, December.
    20. Mertens, Elmar, 2010. "Structural shocks and the comovements between output and interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1171-1186, June.

    More about this item

    Keywords

    business cycles; local polynomial regression; filtering; high-pass; band-pass; US cycles;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecnmx:v:5:y:2017:i:1:p:1-:d:86946. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.