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Potenzielle Auswirkungen des Klimawandels auf Risiko und Kosten der Weizenernte


  • Markus Lips

    () (Agroscope)

  • Robert Finger

    (Gruppe Agrar-, Lebensmittel- und Umweltökonomie, ETH Zürich)

  • Pierluigi Calanca



Landwirte sind bei der Weizenernte mit einem beachtlichen Wetterrisiko in Form von Ernteverlusten konfrontiert. Dem kann mit einer höheren Maschinendichte entgegengewirkt werden, was jedoch zu höheren Maschinenkosten führt. Der vorliegende Tradeoff zwischen Maschinenkosten und Ernterisiken ist Gegenstand dieser Arbeit, in der mittels Monte-Carlo-Simulation optimale Grösse des Maschinenparks und optimale, d.h. minimale, Erntekosten bestimmt werden. Insbesondere wird der Einfluss des Klimawandels auf die oben beschriebenen Prozesse anhand einer Beispielregion im Schweizer Mittelland analysiert. Unsere Analyse zeigt, dass Klimawandel zu deutlich besseren Erntebedingungen führt und eine Reduktion der optimalen Maschinendichte ermöglicht. Verglichen mit heutigen Klimaverhältnissen führt dies zu einer Verringerung der Kosten bei der Weizenernte um bis zu 23 %. Die Ergebnisse dieser Arbeit können verwendet werden, um bestehende Analysen zu den Auswirkungen des Klimawandels auf den Getreideanbau zu komplettieren.

Suggested Citation

  • Markus Lips & Robert Finger & Pierluigi Calanca, 2008. "Potenzielle Auswirkungen des Klimawandels auf Risiko und Kosten der Weizenernte," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 1(1), pages 219-323.
  • Handle: RePEc:cha:ysa001:v:1:y:2008:i:1:p:219-323

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    References listed on IDEAS

    1. Robert Finger & Stéphanie Schmid, 2008. "Modeling agricultural production risk and the adaptation to climate change," Agricultural Finance Review, Emerald Group Publishing, vol. 68(1), pages 25-41, May.
    2. G. F. Donaldson, 1968. "Allowing for Weather Risk in Assessing Harvest Machinery Capacity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 50(1), pages 24-40.
    3. Isabelle Huault & V. Perret & S. Charreire-Petit, 2007. "Management," Post-Print halshs-00337676, HAL.
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    Cited by:

    1. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 61(1).

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets


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