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Lassen sich Ertragsrisiken in der Landwirtschaft global diversifizieren?

Author

Listed:
  • Liu, X.
  • Xu, W.
  • Odening, M.

Abstract

In dieser Arbeit wird die Stochastizität landwirtschaftlicher Ernteerträge in wichtigen Erzeugerregionen der Welt am Beispiel von Winterweizen untersucht. Besondere Aufmerksamkeit wird der stochastischen Abhängigkeit der Erträge in den verschiedenen Regionen gewidmet. Damit verbindet sich die Frage, ob und in welchem Maße Ertragsschwankungen durch globalen Handel ausgeglichen werden können. Während statistische Zusammenhangsanalysen üblicherweise auf linearen Korrelationen basieren, werden in diesem Beitrag Copulas verwendet. Im Vergleich zu linearen Korrelationen ist die Anwendung von Copulas an weniger restriktive Voraussetzungen gebunden. Insbesondere das gemeinsame Auftreten extremer zufälliger Ereignisse lässt sich mit Copulas genauer modellieren. Unsere Berechnungen zeigen, dass eine Angebotskonstellation, wie sie in 2007 aufgetreten ist, kein Jahrhundertereignis darstellt, sondern sich c.p. etwa alle 15 Jahre wiederholen kann.
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Suggested Citation

  • Liu, X. & Xu, W. & Odening, M., 2011. "Lassen sich Ertragsrisiken in der Landwirtschaft global diversifizieren?," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 46, March.
    • Handle: RePEc:ags:gewipr:260267
    DOI: 10.22004/ag.econ.260267
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    References listed on IDEAS

    as
    1. Vedenov, Dmitry V., 2008. "Application of Copulas to Estimation of Joint Crop Yield Distributions," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6264, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Wei Xu & Guenther Filler & Martin Odening & Ostap Okhrin, 2010. "On the systemic nature of weather risk," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 267-284, August.
    3. Sarris, A., 2009. "Factors Affecting Recent and Future Price Volatility of Food Commodities," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 44, March.
    4. Upadhyay, Bharat Mani & Smith, Elwin G., 2005. "Modeling Crop Yield Distributions from Small Samples," Annual Meeting, 2005, July 6-8, San Francisco, CA 34161, Canadian Agricultural Economics Society.
    5. Niall Whelan, 2004. "Sampling from Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 339-352.
    6. Härdle, Wolfgang Karl & Okhrin, Ostap & Okhrin, Yarema, 2008. "Modeling dependencies in finance using copulae," SFB 649 Discussion Papers 2008-043, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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    Cited by:

    1. Schulte-Geers, Matthias & Berg, Ernst, 2011. "Modelling farm production risk with copulae instead of correlations," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115996, European Association of Agricultural Economists.

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