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Short-run and long-run comovement of GDP and some expenditure aggregates in Germany, France and Italy


  • Knetsch, Thomas A.


The paper presents empirical work on short-run and long-run comovement between the German, French and Italian aggregates of private consumption, business investment, exports, imports, GDP, and changes in inventories. In country-specific data sets, cointegration analyses are carried out both to identify long-run economic relationships and to remove the trend components from the nonstationary series. Analytically, this is done by reparametrizing the vector error correction model in its common trends representation. The resulting (Beveridge-Nelson) trend and cycle components as well as the series of changes in inventories are analyzed with a focus on synchronicity. To measure crosscountry comovement at different frequencies, "cohesion", a summary statistic developed by Croux et al. [2001], is applied. Sampling variability and parameter uncertainty are captured by bootstrapped confidence intervals.

Suggested Citation

  • Knetsch, Thomas A., 2005. "Short-run and long-run comovement of GDP and some expenditure aggregates in Germany, France and Italy," Discussion Paper Series 1: Economic Studies 2005,39, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdp1:4233

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    References listed on IDEAS

    1. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008. "In Search of Distress Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
    2. Slacalek, Jirka & Fritsche, Ulrich & Dovern, Jonas & Döpke, Jörg, 2005. "European inflation expectations dynamics," Discussion Paper Series 1: Economic Studies 2005,37, Deutsche Bundesbank.
    3. Falko Fecht & Kevin X. D. Huang & Antoine Martin, 2008. "Financial Intermediaries, Markets, and Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(4), pages 701-720, June.
    4. Koetter, M. & Bos, J.W.B. & Heid, F. & Kolari, J.W. & Kool, C.J.M. & Porath, D., 2007. "Accounting for distress in bank mergers," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3200-3217, October.
    5. Döpke, Jörg & Funke, Michael & Holly, Sean & Weber, Sebastian, 2005. "The cross-sectional dynamics of German business cycles: a bird's eye view," Discussion Paper Series 1: Economic Studies 2005,23, Deutsche Bundesbank.
    6. Kurozumi, Eiji, 2002. "Testing for stationarity with a break," Journal of Econometrics, Elsevier, vol. 108(1), pages 63-99, May.
    7. Hamerle, Alfred & Liebig, Thilo & Scheule, Harald, 2004. "Forecasting Credit Portfolio Risk," Discussion Paper Series 2: Banking and Financial Studies 2004,01, Deutsche Bundesbank.
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    Cited by:

    1. Dungey, Mardi & Jacobs, Jan & Tian, Jing & Norden, Simon van, 2012. "On trend-cycle decomposition and data revision," Research Report 12009-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Kilian, Lutz, 2005. "The Effects of Exogenous Oil Supply Shocks on Output and Inflation: Evidence from the G7 Countries," CEPR Discussion Papers 5404, C.E.P.R. Discussion Papers.

    More about this item


    cointegration; trend-cycle decomposition; cohesion; bootstrap;

    JEL classification:

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

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