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Do so-called multivariate filters have better revision properties? An empirical analysis

Author

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  • L Christopher Plantier
  • Ozer Karagedikli

Abstract

The output gap plays a crucial role in thinking and actions of many central banks but real time measurements undergo substantial revisions as more data become available (Orphanides (2001), Orphanides and van Norden (forthcoming)). Some central banks augment, such as the Bank of Canada and the Reserve Bank of New Zealand, the Hodrick and Prescott (1997) filter with conditioning structural information to mitigate the impact of revisions to the output gap estimates. In this paper, we use a state space Kalman filter framework to examine whether the augmented (so-called “multivariate filters†) achieve this objective. We find that the multivariate filters are no better than the Hodrick-Prescott filter for real-time NZ data. The addition of structural equations increase the number of signal equations, but at the same time adds more unobserved trend/equilibrium variables to the system. We find that how these additional trends/equilibrium values are treated matters a lot, and they increase the uncertainty around the estimates. In addition, the revisions from these models can be as large as a univariate Hodrick-Prescott filter.

Suggested Citation

  • L Christopher Plantier & Ozer Karagedikli, 2005. "Do so-called multivariate filters have better revision properties? An empirical analysis," Computing in Economics and Finance 2005 250, Society for Computational Economics.
  • Handle: RePEc:sce:scecf5:250
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    File URL: http://repec.org/sce2005/up.21881.1107137722.pdf
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    References listed on IDEAS

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    1. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    2. 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.
    3. 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.
    4. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    5. Laurence Boone, 2000. "Comparing Semi-Structural Methods to Estimate Unobserved Variables: The HPMV and Kalman Filters Approaches," OECD Economics Department Working Papers 240, OECD Publishing.
    6. 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.
    7. Tim Robinson & Andrew Stone & Marileze van Zyl, 2003. "The Real-time Forecasting Performance of Phillips Curves," RBA Research Discussion Papers rdp2003-12, Reserve Bank of Australia.
    8. 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.
    9. Jaromir Benes & Papa M N'Diaye, 2004. "A Multivariate Filter for Measuring Potential Output and the NAIRU Application to the Czech Republic," IMF Working Papers 04/45, International Monetary Fund.
    10. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-368, July.
    11. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    12. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, Oxford University Press, vol. 102(4), pages 797-814.
    13. Alasdair Scott, 2000. "A multivariate unobserved components model of cyclical activity," Reserve Bank of New Zealand Discussion Paper Series DP2000/04, Reserve Bank of New Zealand.
    14. Paul Conway & Ben Hunt, 1997. "Estimating potential output: a semi-structural approach," Reserve Bank of New Zealand Discussion Paper Series G97/9, Reserve Bank of New Zealand.
    15. Michael Graff, 2004. "Estimates of the output gap in real time: how well have we been doing?," Reserve Bank of New Zealand Discussion Paper Series DP 2004/04, Reserve Bank of New Zealand.
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    Cited by:

    1. Hjelm, Göran & Jönsson, Kristian, 2010. "In Search of a Method for Measuring the Output Gap of the Swedish Economy," Working Papers 115, National Institute of Economic Research.
    2. Aaron Drew, 2007. "New Zealand's productivity performance and prospects," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 70, March.
    3. Kam Leong Szeto, 2013. "Estimating New Zealand’s Output Gap Using a Small Macro Model," Treasury Working Paper Series 13/18, New Zealand Treasury.

    More about this item

    Keywords

    output gap; real time; multivariate filters;

    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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