IDEAS home Printed from https://ideas.repec.org/a/psc/journl/v12y2020i3p251-272.html
   My bibliography  Save this article

Real-Time vs. Full-Sample Performance of One-Sided and Two-Sided HP Filters. An Application to 27 EU Member States’ GDP Data

Author

Listed:
  • Kaloyan Ganev

    (Sofia University “St. Kliment Ohridski”)

Abstract

The paper makes a comparison of the results of the application of two-sided and one-sided versions of the Hodrick-Prescott filter on GDP data concerning 27 EU Member States. Based on the results, the overall finding is that, contrary to its assumed advantages, the one-sided filter does not help overcome endpoint unbiasedness. Quite the opposite, it rather spreads and consolidates the endpoint bias that plagues the two-sided version over the entire filtered data. In addition, regression-based results on the influence of the second, third, and fourth moments of the GDP acceleration rates on the differences between onesided and two-sided HP trends are presented.

Suggested Citation

  • Kaloyan Ganev, 2020. "Real-Time vs. Full-Sample Performance of One-Sided and Two-Sided HP Filters. An Application to 27 EU Member States’ GDP Data," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(3), pages 251-272, September.
    • Handle: RePEc:psc:journl:v:12:y:2020:i:3:p:251-272
    as

    Download full text from publisher

    File URL: http://cejeme.org/publishedarticles/2020-38-10-637353347160124750-4751.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Blix, Mårten, 1999. "Forecasting Swedish Inflation With a Markov Switching VAR," Working Paper Series 76, Sveriges Riksbank (Central Bank of Sweden).
    2. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    3. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    4. Thorsten Thadewald & Herbert Buning, 2007. "Jarque-Bera Test and its Competitors for Testing Normality - A Power Comparison," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(1), pages 87-105.
    5. 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.
    6. 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.
    7. Mehra Yash P, 2004. "The Output Gap, Expected Future Inflation and Inflation Dynamics: Another Look," The B.E. Journal of Macroeconomics, De Gruyter, vol. 4(1), pages 1-19, December.
    8. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    9. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    10. Yash P. Mehra, 2004. "The output gap, expected future inflation and inflation dynamics: another look," Working Paper 04-06, Federal Reserve Bank of Richmond.
    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. Josefine Quast & Maik H. Wolters, 2022. "Reliable Real-Time Output Gap Estimates Based on a Modified Hamilton Filter," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 152-168, January.
    2. Katsuyuki Shibayama, 2015. "Trend Dominance in Macroeconomic Fluctuations," Studies in Economics 1518, School of Economics, University of Kent.
    3. Peter C. B. Phillips & Sainan Jin, 2021. "Business Cycles, Trend Elimination, And The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 469-520, May.
    4. Wolf, Elias & Mokinski, Frieder & Schüler, Yves, 2020. "On adjusting the one-sided Hodrick-Prescott filter," Discussion Papers 11/2020, Deutsche Bundesbank.
    5. Omoshoro-Jones, Oyeyinka Sunday, 2021. "Asymmetry in Okun’s Law Revisited: New evidence on cyclical unemployment–cyclical output trade-off in the Free State Province using NARDL model," MPRA Paper 107126, University Library of Munich, Germany.
    6. Jalles, Joao Tovar & Ge, Jun, 2020. "Emissions and economic development in commodity exporting countries," Energy Economics, Elsevier, vol. 85(C).
    7. Ugo Panizza, 2022. "Do Countries Default in Bad Times? The Role of Alternative Detrending Techniques," IHEID Working Papers 06-2022, Economics Section, The Graduate Institute of International Studies.
    8. Carnazza, Giovanni & Liberati, Paolo & Sacchi, Agnese, 2020. "The cyclically-adjusted primary balance: A novel approach for the euro area," Journal of Policy Modeling, Elsevier, vol. 42(5), pages 1123-1145.
    9. Joseph G. Haubrich, 2020. "How Cyclical Is Bank Capital?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 58(1), pages 27-38, August.
    10. Vadim Kufenko, 2020. "Hide-and-Seek with time-series filters: a model-based Monte Carlo study," Empirical Economics, Springer, vol. 59(5), pages 2335-2361, November.
    11. João T. Jalles, 2022. "Do credit rating agencies reward fiscal prudence?," International Finance, Wiley Blackwell, vol. 25(1), pages 2-22, April.
    12. 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.
    13. Schüler, Yves S. & Hiebert, Paul P. & Peltonen, Tuomas A., 2020. "Financial cycles: Characterisation and real-time measurement," Journal of International Money and Finance, Elsevier, vol. 100(C).
    14. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    15. João Tovar Jalles, 2020. "The impact of financial crises on the environment in developing countries," Annals of Finance, Springer, vol. 16(2), pages 281-306, June.
    16. Kaiser, Regina & Maravall, Agustin, 2005. "Combining filter design with model-based filtering (with an application to business-cycle estimation)," International Journal of Forecasting, Elsevier, vol. 21(4), pages 691-710.
    17. Baffigi, Alberto & Bontempi, Maria Elena & Felice, Emanuele & Golinelli, Roberto, 2015. "The changing relationship between inflation and the economic cycle in Italy: 1861–2012," Explorations in Economic History, Elsevier, vol. 56(C), pages 53-70.
    18. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 869-889, August.
    19. Melina Dritsaki & Chaido Dritsaki, 2022. "Comparison of HP Filter and the Hamilton’s Regression," Mathematics, MDPI, vol. 10(8), pages 1-18, April.
    20. Steven Cook & Alan Speight, 2005. "A deeper look at asymmetries in UK consumers' expenditure: the nonparametric analysis of 100 disaggregates," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 893-900.

    More about this item

    Keywords

    one-sided and two-sided Hodrick-Prescott filters; endpoint bias;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:psc:journl:v:12:y:2020:i:3:p:251-272. 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: Damian Jelito (email available below). General contact details of provider: http://cejeme.org/ .

    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.