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Investigating the Cyclical Properties of World Trade

  • Monika Ruschinski
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    The world economy in the last two decades is clearly marked by the integration of emerging countries in the international division of labor. To better understand the “globalization” effect, it is helpful to analyze the pattern and structure of world trade volume in the past, in order to draw conclusions for future development. An unobserved components model is used for decomposing world trade volume into trend, cycle, seasonal and irregular components. The analyses show that the process of the world trade volume is driven by the well-known fluctuations in form of the “Kitchin” and “Juglar Cycle”. Furthermore, there is one more cycle with a period between 4 and 5 years which improves the estimation results significantly. The information of the cyclical behavior of the time series is used for projections.

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    Paper provided by Ifo Institute for Economic Research at the University of Munich in its series Ifo Working Paper Series with number Ifo Working Paper No. 30.

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    Date of creation: 2006
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    Handle: RePEc:ces:ifowps:_30
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    1. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    2. Flaig, Gebhard, 2005. "Time series properties of the German production index," Munich Reprints in Economics 20377, University of Munich, Department of Economics.
    3. Gebhard Flaig, 2002. "Unoberserved Components Models for Quarterly German GDP," CESifo Working Paper Series 681, CESifo Group Munich.
    4. Agustín Maravall, 1996. "Unobserved Components in Economic Time Series," Banco de Espa�a Working Papers 9609, Banco de Espa�a.
    5. Gebhard Flaig, 2001. "Trend and Cycles in U.S. Real GDP," CESifo Working Paper Series 607, CESifo Group Munich.
    6. Erich Langmantel, 2005. "Identifying the German Inventory Cycle, A Multivariate Structural Time Series Approach Using Survey Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 225(6), pages 675-687, November.
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