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On the identification of multivariate correlated unobserved components models

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  • Trenkler, Carsten
  • Weber, Enzo

Abstract

This letter analyses identification for multivariate unobserved components models with correlated trend and cycle innovations. We address both the order as well as the rank criteria. Identification is shown for lag structures with lengths larger than one. We also discuss UC models with common features and with cycles that allow for dynamic spillovers.

Suggested Citation

  • Trenkler, Carsten & Weber, Enzo, 2016. "On the identification of multivariate correlated unobserved components models," Economics Letters, Elsevier, vol. 138(C), pages 15-18.
    • Handle: RePEc:eee:ecolet:v:138:y:2016:i:c:p:15-18
    DOI: 10.1016/j.econlet.2015.11.009
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    8. Nathan S. Balke & Mark E. Wohar, 2002. "Low-Frequency Movements in Stock Prices: A State-Space Decomposition," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 649-667, November.
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    11. Richard Startz & Kwok Ping Tsang, 2010. "An Unobserved Components Model of the Yield Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(8), pages 1613-1640, December.
    12. Oh, Kum Hwa & Zivot, Eric & Creal, Drew, 2008. "The relationship between the Beveridge-Nelson decomposition and other permanent-transitory decompositions that are popular in economics," Journal of Econometrics, Elsevier, vol. 146(2), pages 207-219, October.
    13. Christoph Schleicher, 2003. "Structural Time-Series Models with Common Trends and Common Cycles," Computing in Economics and Finance 2003 108, Society for Computational Economics.
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    Cited by:

    1. Melolinna, Marko & Tóth, Máté, 2019. "Trend and cycle shocks in Bayesian unobserved components models for UK productivity," Bank of England working papers 826, Bank of England.
    2. Ivan Mendieta-Munoz & Mengheng Li, 2019. "The Multivariate Simultaneous Unobserved Compenents Model and Identification via Heteroskedasticity," Working Paper Series, Department of Economics, University of Utah 2019_06, University of Utah, Department of Economics.
    3. Tobias Hartl & Rolf Tschernig & Enzo Weber, 2020. "Fractional trends and cycles in macroeconomic time series," Papers 2005.05266, arXiv.org, revised May 2020.
    4. Klinger, Sabine & Weber, Enzo, 2019. "GDP-Employment decoupling and the slow-down of productivity growth in Germany," IAB-Discussion Paper 201912, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Klinger, Sabine & Weber, Enzo, 2016. "Detecting unemployment hysteresis: A simultaneous unobserved components model with Markov switching," Economics Letters, Elsevier, vol. 144(C), pages 115-118.
    6. Trenkler, Carsten & Weber, Enzo, 2016. "On the identification of multivariate correlated unobserved components models," Economics Letters, Elsevier, vol. 138(C), pages 15-18.
    7. Max Soloschenko & Enzo Weber, 2021. "Trend-Cycle Interactions and the Subprime Crisis: Analysis of US and Canadian Output," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 109-128, November.
    8. Sabine Klinger & Enzo Weber, 2016. "Decomposing Beveridge Curve Dynamics By Correlated Unobserved Components," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 877-894, December.
    9. Gehrke, Britta & Weber, Enzo, 2018. "Identifying asymmetric effects of labor market reforms," European Economic Review, Elsevier, vol. 110(C), pages 18-40.
    10. Klinger, Sabine & Weber, Enzo, 2020. "GDP-employment decoupling in Germany," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 82-98.
    11. James McNeil & Gregor W. Smith, 2023. "The All‐Gap Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 269-282, April.

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    More about this item

    Keywords

    Unobserved components models; Identification; VARMA;
    All these keywords.

    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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