IDEAS home Printed from https://ideas.repec.org/p/ags/gaae08/52657.html
   My bibliography  Save this paper

Risikomanagementinstrumente Im Vergleich: Sollte Man Landwirtschaftliche Ernteversicherungen Subventionieren? – Gute Alte Argumente In Einem Neuen Streit

Author

Listed:
  • Hirschauer, Norbert
  • Musshoff, Oliver

Abstract

Sowohl Ernteversicherungen als auch „Wetterderivate“ sind neuartige Risikomanagementinstrumente, die eine Absicherung gegen Schäden aus nichtkatastrophalen Wetterereignissen ermöglichen, in Deutschland aber bisher nicht verbreitet sind. Im vorliegenden Beitrag wird mit Hilfe eines gesamtbetrieblichen Risikoprogrammierungsansatzes untersucht, welchen Nutzen neuartige Hedginginstrumente für Landwirte haben. Das Besondere des verwendeten Ansatzes besteht darin, dass sowohl das betriebsspezifische Risikoreduzierungspotenzial des jeweiligen Instruments als auch die individuelle Risikoakzeptanz des Landwirts berücksichtigt wird. Seine exemplarische Anwendung auf einen nordostdeutschen Marktfruchtbetrieb zeigt, dass standardisierte Wetterderivate einen erheblichen betrieblichen Nutzen und damit eine Zahlungsbereitschaft generieren können. Angesichts der gegenüber schadensbezogenen Versicherungen deutlich geringeren Transaktionskosten deutet dies auf ein Handelspotenzial für Wetterderivate hin. Gleichzeitig verdeutlichen die Berechnungen, dass die aktuell diskutierte Subventionierung von Hofertrags- bzw. Hoferlösversicherungen nicht sinnvoll ist. Im Beispielbetrieb käme es dadurch zu einer unter 50% liegenden Transfereffizienz. Eine Umwidmung von Direktzahlungen für die Subventionierung von Versicherungsprämien ist deshalb auch aus Sicht landwirtschaftlicher Partikularinteressen nicht sinnvoll.

Suggested Citation

  • Hirschauer, Norbert & Musshoff, Oliver, 2008. "Risikomanagementinstrumente Im Vergleich: Sollte Man Landwirtschaftliche Ernteversicherungen Subventionieren? – Gute Alte Argumente In Einem Neuen Streit," 48th Annual Conference, Bonn, Germany, September 24-26, 2008 52657, German Association of Agricultural Economists (GEWISOLA).
    • Handle: RePEc:ags:gaae08:52657
    DOI: 10.22004/ag.econ.52657
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/52657/files/hirshauer.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.52657?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jewson,Stephen & Brix,Anders With contributions by-Name:Ziehmann,Christine, 2005. "Weather Derivative Valuation," Cambridge Books, Cambridge University Press, number 9780521843713.
    2. Berg, Ernst & Schmitz, Bernhard, 2007. "Weather-based instruments in the context of whole farm risk management," 101st Seminar, July 5-6, 2007, Berlin Germany 9269, European Association of Agricultural Economists.
    3. Musshoff, Oliver & Hirschauer, Norbert, 2007. "What benefits are to be derived from improved farm program planning approaches? - The role of time series models and stochastic optimization," Agricultural Systems, Elsevier, vol. 95(1-3), pages 11-27, December.
    4. Jerry R. Skees & Barry J. Barnett, 2006. "Enhancing microfinance using index-based risk-transfer products," Agricultural Finance Review, Emerald Group Publishing, vol. 66(2), pages 235-250, September.
    5. Garrido, Alberto & Bielza, Maria, 2008. "Income Stabilisation in a Changing Agricultural World: Policy and Tools," 108th Seminar, February 8-9, 2008, Warsaw, Poland 48108, European Association of Agricultural Economists.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Musshoff, Oliver & Hirschauer, Norbert, 2008. "Hedging von Mengenrisiken in der Landwirtschaft – Wie teuer dürfen „ineffektive“ Wetterderivate sein?," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 57(05), pages 1-12.
    2. Markus Stowasser, 2011. "Modelling rain risk: a multi-order Markov chain model approach," Journal of Risk Finance, Emerald Group Publishing, vol. 13(1), pages 45-60, December.
    3. Evarest Emmanuel & Berntsson Fredrik & Singull Martin & Yang Xiangfeng, 2018. "Weather derivatives pricing using regime switching model," Monte Carlo Methods and Applications, De Gruyter, vol. 24(1), pages 13-27, March.
    4. Kellner, Ulla & Musshoff, Oliver, 2011. "Precipitation or water capacity indices? An analysis of the benefits of alternative underlyings for index insurance," Agricultural Systems, Elsevier, vol. 104(8), pages 645-653, October.
    5. Pelka, Niels & Weber, Ron & Musshoff, Oliver, 2015. "Does weather matter? How rainfall shocks affect credit risk in agricultural micro-finance," 2015 Conference, August 9-14, 2015, Milan, Italy 212617, International Association of Agricultural Economists.
    6. Xu, Wei & Odening, Martin & Musshoff, Oliver, 2007. "Indifference Pricing of Weather Insurance," 101st Seminar, July 5-6, 2007, Berlin Germany 9267, European Association of Agricultural Economists.
    7. Zhang, Li, 2008. "Three essays on agricultural risk and insurance," ISU General Staff Papers 2008010108000016857, Iowa State University, Department of Economics.
    8. Mußhoff, O. & Odenin, M. & Wei, X., 2007. "Zur Quantifizierung des Basisrisikos von Wetterderivaten," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 42, March.
    9. Möllmann, Johannes & Buchholz, Matthias & Kölle, Wienand & Musshoff, Oliver, 2020. "Do remotely-sensed vegetation health indices explain credit risk in agricultural microfinance?," World Development, Elsevier, vol. 127(C).
    10. Leif Erec Heimfarth & Oliver Musshoff, 2011. "Weather index‐based insurances for farmers in the North China Plain," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(2), pages 218-239, August.
    11. Turvey, Calum G. & Chantarat, Sommarat, 2006. "Weather-Linked Bonds," 2006 Agricultural and Rural Finance Markets in Transition, October 2-3, 2006, Washington, DC 133091, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
    12. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
    13. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    14. Jewson Stephen & Penzer Jeremy, 2006. "Estimating Trends in Weather Series: Consequences for Pricing Derivatives," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-17, September.
    15. Jean-Louis Bertrand & Xavier Brusset, 2018. "Managing the financial consequences of weather variability," Journal of Asset Management, Palgrave Macmillan, vol. 19(5), pages 301-315, September.
    16. Buchholz, Matthias & Musshoff, Oliver, 2014. "The role of weather derivatives and portfolio effects in agricultural water management," Agricultural Water Management, Elsevier, vol. 146(C), pages 34-44.
    17. Soraya Tanure & Carlos Nabinger & João Luiz Becker, 2015. "Bioeconomic Model of Decision Support System for Farm Management: Proposal of a Mathematical Model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(6), pages 658-671, November.
    18. Turvey, Calum G. & Norton, Michael, 2008. "An Internet-Based Tool for Weather Risk Management," Agricultural and Resource Economics Review, Cambridge University Press, vol. 37(1), pages 63-78, April.
    19. Hotopp, Henning & Mußhoff, Oliver, 2012. "Can rent adjustment clauses reduce the income risk of farms?," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 1(4), pages 1-10, July.
    20. Jr‐Wei Huang & Sharon S. Yang & Chuang‐Chang Chang, 2018. "Modeling temperature behaviors: Application to weather derivative valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1152-1175, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:gaae08:52657. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/gewisea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.