IDEAS home Printed from https://ideas.repec.org/p/man/cgbcrp/159.html
   My bibliography  Save this paper

Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts

Author

Listed:
  • Jaqueson K. Galimberti
  • Marcelo L. Moura

Abstract

Incorporating survey forecasts to a forecast-augmented Hodrick-Prescott filter, we evidence a considerable improvement to the reliability of US output-gap estimation in realtime. Odds of extracting wrong signals of output-gap estimates are found to reduce by almost a half, and the magnitude of revisions to these estimates accounts to only three fifths of the output-gap average size, usually an one-by-one ratio. We further analyze how this end-of-sample uncertainty evolves as time goes on and observations accumulate, showing that a 90% rate of correct assessments of the output-gap sign can be attained with five quarters of delay using survey forecasts.

Suggested Citation

  • Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The University of Manchester.
    • Handle: RePEc:man:cgbcrp:159
    as

    Download full text from publisher

    File URL: https://hummedia.manchester.ac.uk/schools/soss/cgbcr/discussionpapers/dpcgbcr159.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Prescott, Edward C., 1986. "Theory ahead of business-cycle measurement," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 11-44, January.
    2. Danthine, Jean-Pierre & Girardin, Michel, 1989. "Business cycles in Switzerland : A comparative study," European Economic Review, Elsevier, vol. 33(1), pages 31-50, January.
    3. Michael Graff & Jan-Egbert Sturm, 2010. "The information content of capacity utilisation rates for output gap estimates," KOF Working papers 10-269, KOF Swiss Economic Institute, ETH Zurich.
    4. Christophe Planas & Alessandro Rossi, 2004. "Can inflation data improve the real-time reliability of output gap estimates?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 121-133.
    5. Marcellino, Massimiliano & Musso, Alberto, 2011. "The reliability of real-time estimates of the euro area output gap," Economic Modelling, Elsevier, vol. 28(4), pages 1842-1856, July.
    6. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    7. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
    8. Tommaso Proietti, 2009. "On the Model-Based Interpretation of Filters and the Reliability of Trend-Cycle Estimates," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 186-208.
    9. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    10. Canova, Fabio, 1998. "Detrending and business cycle facts: A user's guide," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 533-540, May.
    11. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not as Bad as You Think," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441, National Bureau of Economic Research, Inc.
    12. Canova, Fabio, 1998. "Detrending and business cycle facts," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 475-512, May.
    13. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    14. Mise, Emi & Kim, Tae-Hwan & Newbold, Paul, 2005. "On suboptimality of the Hodrick-Prescott filter at time series endpoints," Journal of Macroeconomics, Elsevier, vol. 27(1), pages 53-67, March.
    15. Regina Kaiser & Agustín Maravall, 1999. "Estimation of the business cycle: A modified Hodrick-Prescott filter," Spanish Economic Review, Springer;Spanish Economic Association, vol. 1(2), pages 175-206.
    16. Ager, P. & Kappler, M. & Osterloh, S., 2009. "The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach," International Journal of Forecasting, Elsevier, vol. 25(1), pages 167-181.
    17. Andrew C. Harvey & Thomas M. Trimbur, 2003. "General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 244-255, May.
    18. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    19. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.
    20. 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.
    21. Anthony Garratt & Kevin Lee & Emi Mise & Kalvinder Shields, 2008. "Real-Time Representations of the Output Gap," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 792-804, November.
    22. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    23. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    24. Mark W. Watson, 2007. "How accurate are real-time estimates of output trends and gaps?," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 93(Spr), pages 143-161.
    25. 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.
    26. Cayen, Jean-Philippe & van Norden, Simon, 2005. "The reliability of Canadian output-gap estimates," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 373-393, December.
    27. Pedersen, Torben Mark, 2001. "The Hodrick-Prescott filter, the Slutzky effect, and the distortionary effect of filters," Journal of Economic Dynamics and Control, Elsevier, vol. 25(8), pages 1081-1101, August.
    28. Keith Blackburn & Felipe Orduna & Martin Sola, 1995. "Exponential smoothing and spurious correlation: a note," Applied Economics Letters, Taylor & Francis Journals, vol. 2(3), pages 76-79.
    29. Gomez, Victor, 1999. "Three Equivalent Methods for Filtering Finite Nonstationary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 109-116, January.
    30. Isiklar, Gultekin & Lahiri, Kajal, 2007. "How far ahead can we forecast? Evidence from cross-country surveys," International Journal of Forecasting, Elsevier, vol. 23(2), pages 167-187.
    31. Sylvain Leduc & Keith Sill, 2013. "Expectations and Economic Fluctuations: An Analysis Using Survey Data," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1352-1367, October.
    32. Fabio Milani, 2011. "Expectation Shocks and Learning as Drivers of the Business Cycle," Economic Journal, Royal Economic Society, vol. 121(552), pages 379-401, May.
    33. Stark, Tom & Croushore, Dean, 2002. "Reply to the comments on 'Forecasting with a real-time data set for macroeconomists'," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 563-567, December.
    34. Ehlgen, Jurgen, 1998. "Distortionary effects of the optimal Hodrick-Prescott filter," Economics Letters, Elsevier, vol. 61(3), pages 345-349, December.
    35. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    36. Gomez, Victor, 2001. "The Use of Butterworth Filters for Trend and Cycle Estimation in Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 365-373, July.
    37. Roy Batchelor, 2001. "How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 225-235.
    38. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2010. "New Eurocoin: Tracking Economic Growth in Real Time," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1024-1034, November.
    39. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    40. Valle e Azevedo, Joao & Koopman, Siem Jan & Rua, Antonio, 2006. "Tracking the Business Cycle of the Euro Area: A Multivariate Model-Based Bandpass Filter," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 278-290, July.
    41. 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.
    42. Ince, Onur & Papell, David H., 2013. "The (un)reliability of real-time output gap estimates with revised data," Economic Modelling, Elsevier, vol. 33(C), pages 713-721.
    43. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
    44. 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.
    45. João Valle e Azevedo, 2011. "A multivariate band‐pass filter for economic time series," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 60(1), pages 1-30, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
    2. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.

    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. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
    2. 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.
    3. 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.
    4. de Carvalho, Miguel & Rua, António, 2017. "Real-time nowcasting the US output gap: Singular spectrum analysis at work," International Journal of Forecasting, Elsevier, vol. 33(1), pages 185-198.
    5. Álvarez, Luis J. & Gómez-Loscos, Ana, 2018. "A menu on output gap estimation methods," Journal of Policy Modeling, Elsevier, vol. 40(4), pages 827-850.
    6. Ince, Onur & Papell, David H., 2013. "The (un)reliability of real-time output gap estimates with revised data," Economic Modelling, Elsevier, vol. 33(C), pages 713-721.
    7. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    8. Tawadros, George B., 2011. "The stylised facts of Australia's business cycle," Economic Modelling, Elsevier, vol. 28(1), pages 549-556.
    9. Carlos A. Medel, 2018. "Forecasting Inflation with the Hybrid New Keynesian Phillips Curve: A Compact-Scale Global VAR Approach," International Economic Journal, Taylor & Francis Journals, vol. 32(3), pages 331-371, July.
    10. João Valle e Azevedo, 2007. "A Multivariate Band-Pass Filter," Working Papers w200717, Banco de Portugal, Economics and Research Department.
    11. Cayen, Jean-Philippe & van Norden, Simon, 2005. "The reliability of Canadian output-gap estimates," The North American Journal of Economics and Finance, Elsevier, vol. 16(3), pages 373-393, December.
    12. Miroslav Plašil, 2011. "Potenciální produkt, mezera výstupu a míra nejistoty spojená s jejich určením při použití Hodrick-Prescottova filtru [Potential Product, Output Gap and Uncertainty Rate Associated with Their Determ," Politická ekonomie, Prague University of Economics and Business, vol. 2011(4), pages 490-507.
    13. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Measuring output gap nowcast uncertainty," International Journal of Forecasting, Elsevier, vol. 30(2), pages 268-279.
    14. Mark Meyer & Peter Winker*, 2005. "Using HP Filtered Data for Econometric Analysis: Some Evidence from Monte Carlo Simulations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 89(3), pages 303-320, August.
    15. Valle e Azevedo, João, 2007. "Interpretation of the Effects of Filtering Integrated Time Series," MPRA Paper 6574, University Library of Munich, Germany.
    16. Valle e Azevedo, João & Pereira, Ana, 2013. "Approximating and forecasting macroeconomic signals in real-time," International Journal of Forecasting, Elsevier, vol. 29(3), pages 479-492.
    17. Fukuda, Kosei, 2012. "Illustrating extraordinary shocks causing trend breaks," Economic Modelling, Elsevier, vol. 29(4), pages 1045-1052.
    18. Rünstler, Gerhard & Balfoussia, Hiona & Burlon, Lorenzo & Buss, Ginters & Comunale, Mariarosaria & De Backer, Bruno & Dewachter, Hans & Guarda, Paolo & Haavio, Markus & Hindrayanto, Irma & Iskrev, Nik, 2018. "Real and financial cycles in EU countries - Stylised facts and modelling implications," Occasional Paper Series 205, European Central Bank.
    19. Viv B. Hall & Peter Thomson, 2022. "A boosted HP filter for business cycle analysis:evidence from New Zealand's small open economy," CAMA Working Papers 2022-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    20. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.

    More about this item

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:man:cgbcrp:159. 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: Patrick Macnamara (email available below). General contact details of provider: https://edirc.repec.org/data/semanuk.html .

    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.