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

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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 filtersâ€) 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.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 250.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:250

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Keywords: output gap; real time; multivariate filters;

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References

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  1. Cayen, Jean-Philippe & van Norden, Simon, 2004. "The reliability of Canadian output gap estimates," Discussion Paper Series 1: Economic Studies 2004,29, Deutsche Bundesbank, Research Centre.
  2. Athanasios Orphanides & Simon Van_Norden, 2000. "The Reliability of Output Gap Estimates in Real Time," Econometric Society World Congress 2000 Contributed Papers 0768, Econometric Society.
  3. Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  4. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-27, June.
  5. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  6. Jaromir Benes & Papa M'B. P. 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.
  7. Athanasios Orphanides & Simon van Norden, 2004. "The reliability of inflation forecasts based on output gap estimates in real time," Finance and Economics Discussion Series 2004-68, Board of Governors of the Federal Reserve System (U.S.).
  8. 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.
  9. Pete Richardson & Laurence Boone & Claude Giorno & Mara Meacci & David Rae & David Turner, 2000. "The Concept, Policy Use and Measurement of Structural Unemployment: Estimating a Time Varying NAIRU Across 21 OECD Countries," OECD Economics Department Working Papers 250, OECD Publishing.
  10. 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.
  11. 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.
  12. Clark, Peter K, 1987. "The Cyclical Component of U.S. Economic Activity," The Quarterly Journal of Economics, MIT Press, vol. 102(4), pages 797-814, November.
  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. 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.
  15. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-68, July.
  16. 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.
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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 Paper 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.

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