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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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Suggested Citation

  • Tommaso PROIETTI, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Economics Working Papers ECO2002/23, European University Institute.
    • Handle: RePEc:eui:euiwps:eco2002/23
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    Cited by:

    1. de Silva, Ashton & Hyndman, Rob J. & Snyder, Ralph, 2009. "A multivariate innovations state space Beveridge-Nelson decomposition," Economic Modelling, Elsevier, vol. 26(5), pages 1067-1074, September.
    2. 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.
    3. de Silva, Ashton, 2008. "Forecasting macroeconomic variables using a structural state space model," MPRA Paper 11060, University Library of Munich, Germany.
    4. Hafiz Hoque & Sarkar Humayun Kabir & El Khamlichi Abdelbari & Viktor Manahov, 2016. "Islamic and Conventional Equity Market Movements During and After the Financial Crisis: Evidence from the Newly Launched MSCI Indices," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 25(4), pages 217-252, November.
    5. Cliff L.F. Attfield & Jonathan R.W. Temple, 2003. "Measuring trend output: how useful are the Great Ratios?," Bristol Economics Discussion Papers 03/555, School of Economics, University of Bristol, UK.
    6. Julien Garnier, 2004. "UK in or UK Out? A Common Cycle Analysis Between the UK and the Euro Zone," Working Papers 2004-17, CEPII research center.
    7. 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.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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