IDEAS home Printed from https://ideas.repec.org/a/ags/gjagec/97605.html
   My bibliography  Save this article

Hedging von Mengenrisiken in der Landwirtschaft – Wie teuer dürfen „ineffektive“ Wetterderivate sein?

Author

Listed:
  • Musshoff, Oliver
  • Hirschauer, Norbert

Abstract

Since the mid-nineties, agricultural economists discuss the suitability of “weather derivatives” as hedging instruments for volumetric risks in agriculture. Contrary to traditional insurance contracts, the payoffs of such derivatives are linked to weather indices (e.g. accumulated rainfall or temperature over a certain period) that are measured objectively at a defined meteorological station. While weather derivatives thus circumvent the problem of moral hazard and adverse selection, weather derivative markets for the agricultural sector are still in their infancy all-over the world. Some economists attribute this to theoretical valuation problems and the lack of a pricing method which is accepted by all market participants. Others think that the low hedging effectiveness of (standardized and noncustomized) weather contracts cripple the market. Motivated by the question of how weather derivatives should be priced to agricultural firms, this paper describes a risk programming model which can be used to determine farmers’ willingness-to-pay (demand function) for weather derivatives. The model considers both the derivative’s farmspecific risk reduction capacity and the individual farmer’s risk acceptance. Applying it to the exemplary case of a Brandenburg farm reveals that even a highly standardized contract which is based on the accumulated rainfall at the capital’s meteorological station in Berlin-Tempelhof generates a relevant willingness-to-pay. We find that a potential underwriter could even add a loading on the actuarially fair price that exceeds the loading level of traditional insurances. Since transaction costs are low compared to insurance contracts, this indicates that there may be a significant trading potential.

Suggested Citation

  • 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.
  • Handle: RePEc:ags:gjagec:97605
    DOI: 10.22004/ag.econ.97605
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/97605/files/4_Mu_hoff.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.97605?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
    ---><---

    References listed on IDEAS

    as
    1. Martin Odening & Oliver Musshoff & Wei Xu, 2007. "Analysis of rainfall derivatives using daily precipitation models: opportunities and pitfalls," Agricultural Finance Review, Emerald Group Publishing, vol. 67(1), pages 135-156, May.
    2. Turvey, Calum G., 2002. "Insuring Heat Related Risks In Agriculture With Degree-Day Weather Derivatives," 2002 Annual meeting, July 28-31, Long Beach, CA 19896, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Cao, M. & Wei, J., 1999. "Pricing Weather Derivative : An Equilibrium Approach," Rotman School of Management - Finance 99-002, Rotman School of Management, University of Toronto.
    4. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    5. 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.
    6. Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "Pricing Weather Derivatives," Working Papers 28536, Arizona State University, Morrison School of Agribusiness and Resource Management.
    7. Jewson,Stephen & Brix,Anders With contributions by-Name:Ziehmann,Christine, 2005. "Weather Derivative Valuation," Cambridge Books, Cambridge University Press, number 9780521843713, February.
    8. Vedenov, Dmitry V. & Barnett, Barry J., 2004. "Efficiency of Weather Derivatives as Primary Crop Insurance Instruments," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-17, December.
    9. Peter Alaton & Boualem Djehiche & David Stillberger, 2002. "On modelling and pricing weather derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 1-20.
    10. 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.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2021. "Weather derivatives to mitigate meteorological risks in tourism management: An empirical application to celebrations of Comunidad Valenciana (Spain)," Tourism Economics, , vol. 27(4), pages 591-613, June.
    3. 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.
    4. 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.
    5. Zhang, Li, 2008. "Three essays on agricultural risk and insurance," ISU General Staff Papers 2008010108000016857, Iowa State University, Department of Economics.
    6. Wolfgang Karl Härdle & Brenda López Cabrera, 2012. "The Implied Market Price of Weather Risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(1), pages 59-95, February.
    7. Chung, Wonho, 2013. "Reducing the Social Cost of Federal Crop Insurance: A Role for US Government Hedging with Weather Derivatives," Journal of Rural Development/Nongchon-Gyeongje, Korea Rural Economic Institute, vol. 36(2), pages 1-26, August.
    8. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    9. Prabakaran, Sellamuthu & Garcia, Isabel C. & Mora, Jose U., 2020. "A temperature stochastic model for option pricing and its impacts on the electricity market," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 58-77.
    10. Musshoff, Oliver & Odening, Martin & Xu, Wei, 2005. "Zur Bewertung von Wetterderivaten als innovative Risikomanagementinstrumente in der Landwirtschaft," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 54(04), pages 1-13.
    11. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    12. 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.
    13. Doms, Juliane, 2017. "Put, call or strangle? About the challenges in designing weather index insurances to hedge performance risk in agriculture," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 261990, German Association of Agricultural Economists (GEWISOLA).
    14. Andrea Martínez Salgueiro & Maria-Antonia Tarrazon-Rodon, 2020. "Approaching rainfall-based weather derivatives pricing and operational challenges," Review of Derivatives Research, Springer, vol. 23(2), pages 163-190, July.
    15. Turvey, Calum G. & Weersink, Alfons, 2005. "Pricing Weather Insurance with a Random Strike Price: An Application to the Ontario Ice Wine Harvest," 2005 Annual meeting, July 24-27, Providence, RI 19255, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Leif Erec Heimfarth & Oliver Musshoff, 2011. "Weather index-based insurances for farmers in the North China Plain: An analysis of risk reduction potential and basis risk," Agricultural Finance Review, Emerald Group Publishing, vol. 71(2), pages 218-239, August.
    17. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811.
    18. Ahmet Göncü, 2013. "Comparison of temperature models using heating and cooling degree days futures," Journal of Risk Finance, Emerald Group Publishing, vol. 14(2), pages 159-178, February.
    19. Andrea Barth & Fred Espen Benth & Jurgen Potthoff, 2011. "Hedging of Spatial Temperature Risk with Market-Traded Futures," Applied Mathematical Finance, Taylor & Francis Journals, vol. 18(2), pages 93-117.
    20. Sun, Baojing, 2017. "Financial Weather Derivatives for Corn Production in Northeastern China: Modelling the Underlying Weather Index," Working Papers 257083, University of Victoria, Resource Economics and Policy.

    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:gjagec:97605. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/iahubde.html .

    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/iahubde.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.