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Some Reflections on Trend-Cycle Decompositions with Correlated Components

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  • Tommaso PROIETTI

Abstract

This paper discusses a few interpretative issues arising from trend- cycle decompositions with correlated components. We determine the conditions under which correlated components may originate from: underestimation of the cyclical component; a cycle in growth rates, rather than in the levels; the hysteresis phenomenon; permanent- transitory decompositions, where the permanent component has richer dynamics than a pure random walk. Moreover, the consequences for smoothing and signal extraction are discussed: in particular, we establish that a negative correlation implies that future observations carry most of the information needed to assess cyclical stance. As a result, the components will be subject to high revisions. The overall conclusion is that the characterisation of economic fluctuations in macroeconomic time series largely remains an open issue.

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Bibliographic Info

Paper provided by European University Institute in its series Economics Working Papers with number ECO2002/23.

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Date of creation: 2002
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Handle: RePEc:eui:euiwps:eco2002/23

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  1. 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.
  2. Andrew Harvey & Siem Jan Koopman, 2000. "Signal extraction and the formulation of unobserved components models," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 84-107.
  3. Lippi, Marco & Reichlin, Lucrezia, 1992. "On persistence of shocks to economic variables : A common misconception," Journal of Monetary Economics, Elsevier, vol. 29(1), pages 87-93, February.
  4. James C. Morley & Charles Nelson & Eric Zivot, 2000. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers 0013, University of Washington, Department of Economics.
  5. Proietti, Tommaso & Harvey, Andrew, 2000. "A Beveridge-Nelson smoother," Economics Letters, Elsevier, vol. 67(2), pages 139-146, May.
  6. Jurgen A Doornik & Henrik Hansen, . "An omnibus test for univariate and multivariate normalit," Economics Papers W4&91., Economics Group, Nuffield College, University of Oxford.
  7. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
  8. Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
  9. Jaeger, Albert & Parkinson, Martin, 1994. "Some evidence on hysteresis in unemployment rates," European Economic Review, Elsevier, vol. 38(2), pages 329-342, February.
  10. Harvey, Andrew, 2001. "Testing in Unobserved Components Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(1), pages 1-19, January.
  11. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
  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.
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Cited by:
  1. Riccardo Corradini, 2005. "An Empirical Analysis of Permanent Income Hypothesis Applied to Italy using State Space Models with non zero correlation between trend and cycle," Computing in Economics and Finance 2005 28, Society for Computational Economics.
  2. Attfield, Clifford & Temple, Jonathan, 2004. "Measuring Trend Output: How Useful Are the Great Ratios?," CEPR Discussion Papers 4796, C.E.P.R. Discussion Papers.
  3. de Silva, Ashton, 2007. "A multivariate innovations state space Beveridge Nelson decomposition," MPRA Paper 5431, University Library of Munich, Germany.
  4. de Silva, Ashton, 2008. "Forecasting macroeconomic variables using a structural state space model," MPRA Paper 11060, University Library of Munich, Germany.
  5. Jonathan Temple & Cliff Attfield, 2004. "Measuring trend growth: how useful are the great ratios?," Money Macro and Finance (MMF) Research Group Conference 2003 101, Money Macro and Finance Research Group.

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