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Scoring Six Detrending Methods on Timing, Lead-Lag Relations, and Cycle Periods: An Empirical Study of US and UK Recessions 1977–2020

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  • Knut Lehre Seip

    (Oslo Metropolitan University: OsloMet – storbyuniversitetet)

  • Dan Zhang

    (Oslo Metropolitan University: OsloMet – storbyuniversitetet)

Abstract

This study evaluates six commonly used detrending methods and discuss how detrending may change the timing of events, the identification of lead-lag relations between GDP and employment, and the identification of cycle periods. The detrending methods examined includes linear detrending, polynomial detrending, the first-order differencing, locally weighted scatterplot smoothing (LOESS), Hodrick–Prescott filter, and the Hamilton filter. We apply the detrending methods to the United States and United Kingdom gross domestic product (GDP) from 1977 to 2020. We find that for the GDP series the first-order differencing score best on all three criteria, however, it also shows more false recessions than the other detrending methods. A linear, a polynomial, and a LOESS trend all scored well. The three methods miss-specified the timing of the recessions with less than one quarter and all three gave results that would comply with stylized facts in macroeconomics. The Hodrick–Prescott (HP) filter and Hamilton filter did not achieve high scores on one or two of the criteria and scored worst on average performance.

Suggested Citation

  • Knut Lehre Seip & Dan Zhang, 2024. "Scoring Six Detrending Methods on Timing, Lead-Lag Relations, and Cycle Periods: An Empirical Study of US and UK Recessions 1977–2020," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 3087-3116, November.
  • Handle: RePEc:kap:compec:v:64:y:2024:i:5:d:10.1007_s10614-024-10548-x
    DOI: 10.1007/s10614-024-10548-x
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    References listed on IDEAS

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    1. Hilde Bjørnland & Leif Brubakk & Anne Jore, 2008. "Forecasting inflation with an uncertain output gap," Empirical Economics, Springer, vol. 35(3), pages 413-436, November.
    2. Viv B. Hall & Peter Thomson & Stuart McKelvie, 2017. "On the robustness of stylised business cycle facts for contemporary New Zealand," New Zealand Economic Papers, Taylor & Francis Journals, vol. 51(3), pages 193-216, September.
    3. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    4. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
    5. Canova, Fabio, 1999. "Does Detrending Matter for the Determination of the Reference Cycle and the Selection of Turning Points?," Economic Journal, Royal Economic Society, vol. 109(452), pages 126-150, January.
    6. Zarnowitz, Victor & Ozyildirim, Ataman, 2006. "Time series decomposition and measurement of business cycles, trends and growth cycles," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1717-1739, October.
    7. Burnside, Craig, 1998. "Detrending and business cycle facts: A comment," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 513-532, May.
    8. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, January.
    9. Knut Lehre Seip & Yunus Yilmaz & Michael Schröder, 2019. "Comparing Sentiment- and Behavioral-Based Leading Indexes for Industrial Production: When Does Each Fail?," Economies, MDPI, vol. 7(4), pages 1-18, October.
    10. Hilde Christiane BjÛrnland, 2000. "Detrending methods and stylized facts of business cycles in Norway - an international comparison," Empirical Economics, Springer, vol. 25(3), pages 369-392.
    11. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    12. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    13. Morten O. Ravn & Harald Uhlig, 2002. "On adjusting the Hodrick-Prescott filter for the frequency of observations," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 371-375.
    14. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
    15. 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.
    16. Park, Gonyung, 1996. "The role of detrending methods in a model of real business cycles," Journal of Macroeconomics, Elsevier, vol. 18(3), pages 479-501.
    17. Baxter, Marianne, 1991. "Business cycles, stylized facts, and the exchange rate regime: evidence from the United States," Journal of International Money and Finance, Elsevier, vol. 10(1), pages 71-88, March.
    18. Andrew Hallett & Christian Richter, 2006. "Measuring the Degree of Convergence among European Business Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 229-259, May.
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    More about this item

    Keywords

    Detrending methods; Forecasting; Recessions; LOESS filter; HP-filter; Hamilton-filter;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • G01 - Financial Economics - - General - - - Financial Crises

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