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A Complete Model-Based Interpretation of the Hodrick-Prescott Filter: Spuriousness Reconsidered

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Author Info

  • Regina Kaiser

    ()
    (Universidad Carlos III de Madrid)

  • Agustín Maravall

    ()
    (Banco de España)

Abstract

The Hodrick-Prescott filter applied to seasonally adjusted series has become a paradigm for business-cycle estimation at many economic agencies and institutions. We show that the filter can be obtained from MMSE estimation of the components in an unobserved component model, where the original series is decomposed into (long-term) trend, cyclical, seasonal, and (highlytransitory) irregular components. The component models are sensible and combine desirable “ad-hoc” features with series-dependent features that guarantee consistency with the data. The model-based framework provides improvements having to do with the precision of end-point estimation and the stability of the cyclical signal.

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File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/02/Fic/dt0208e.pdf
File Function: First version, March 2002
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Bibliographic Info

Paper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 0208.

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Length: 31 pages
Date of creation: Mar 2002
Date of revision:
Handle: RePEc:bde:wpaper:0208

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Related research

Keywords: Business-cycle estimation; Stochastic cycles and trends; Unobserved Component Models; ARIMA models;

References

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  1. Agustín Maravall, 1996. "Unobserved Components in Economic Time Series," Banco de Espa�a Working Papers 9609, Banco de Espa�a.
  2. 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 231-47, July-Sept.
  3. Claude Giorno & Pete Richardson & Deborah Roseveare & Paul van den Noord, 1995. "Estimating Potential Output, Output Gaps and Structural Budget Balances," OECD Economics Department Working Papers 152, OECD Publishing.
  4. Timothy Cogley & James M. Nason, 1993. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series: implications for business cycle research," Working Papers in Applied Economic Theory 93-01, Federal Reserve Bank of San Francisco.
  5. David A. Pierce, 1978. "Seasonal adjustment when both deterministic and stochastic seasonality are present," Special Studies Papers 107, Board of Governors of the Federal Reserve System (U.S.).
  6. Víctor Gómez & Pilar Bengoechea, 2000. "The quarterly national accounts trend-cycle filter versus model-based filters," Spanish Economic Review, Springer, vol. 2(1), pages 29-48.
  7. Pierce, David A., 1980. "Data revisions with moving average seasonal adjustment procedures," Journal of Econometrics, Elsevier, vol. 14(1), pages 95-114, September.
  8. Regina Kaiser & Agustín Maravall, 1999. "Estimation of the Business Cycle: a Modified Hodrick-Prescott Filter," Banco de Espa�a Working Papers 9912, Banco de Espa�a.
  9. Maravall, Agustin, 1985. "On Structural Time Series Models and the Characterization of Components," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 350-55, October.
  10. David A. Pierce, 1978. "Seasonal Adjustment When Both Deterministic and Stochastic Seasonality Are Present," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 242-280 National Bureau of Economic Research, Inc.
  11. Regina Kaiser & Agustín Maravall, 1999. "Estimation of the Business Cycle: a Modified Hodrick-Prescott Filter," Banco de Espa�a Working Papers 9912, Banco de Espa�a.
  12. Agustín Maravall & Ana del Río, 2001. "Time Aggregation and the Hodrick-Prescott Filter," Banco de Espa�a Working Papers 0108, Banco de Espa�a.
  13. 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.
  14. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  15. Harvey, Andrew, 1997. "Trends, Cycles and Autoregressions," Economic Journal, Royal Economic Society, vol. 107(440), pages 192-201, January.
  16. Gomez, Victor, 1999. "Three Equivalent Methods for Filtering Finite Nonstationary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 109-16, January.
  17. 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 365-73, July.
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Citations

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Cited by:
  1. Michael Artis & Toshihiro Okubo, 2008. "Globalization and Business Cycle Transmission," Discussion Paper Series 232, Research Institute for Economics & Business Administration, Kobe University.
  2. Artis, Michael J & Okubo, Toshihiro, 2008. "The Intranational Business Cycle: Evidence from Japan," CEPR Discussion Papers 6686, C.E.P.R. Discussion Papers.
  3. Martin Fukac & Adrian Pagan, 2009. "Structural macro-wconometric modelling in a policy environment," Reserve Bank of New Zealand Discussion Paper Series DP2009/16, Reserve Bank of New Zealand.
  4. Michael J. Artis & Toshihiro Okubo, 2011. "Business Cycle, Currency and Trade, Revisited," Keio/Kyoto Joint Global COE Discussion Paper Series 2011-019, Keio/Kyoto Joint Global COE Program.
  5. Martin Fukac & Adrian Pagan, 2010. "Limited information estimation and evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 55-70.

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