IDEAS home Printed from https://ideas.repec.org/a/oup/ajagec/v96y2014i4p1117-1135..html
   My bibliography  Save this article

Tails Curtailed: Accounting for Nonlinear Dependence in Pricing Margin Insurance for Dairy Farmers

Author

Listed:
  • Marin Bozic
  • John Newton
  • Cameron S. Thraen
  • Brian W. Gould

Abstract

Livestock Gross Margin Insurance for Dairy Cattle (LGM-Dairy) is a risk management tool for protecting milk income over feed cost margins. In this article, we examine the assumptions underpinning the method used to determine LGM-Dairy premiums. Analysis of the milk-feed dependence structure is conducted using copula methods, a rich set of tools that allow modelers to capture nonlinearities in dependence among variables of interest. We find a significant relationship between milk and feed prices that increases with time-to-maturity and severity of negative price shocks. Extremal, or tail, dependence is the propensity of dependence to concentrate in the tails of a distribution. A common theme in financial and actuarial applications and in agricultural crop revenue insurance is that tail dependence increases the risk to the underwriter and results in higher insurance premiums. We present, to our knowledge, the first case in which tail dependence may actually reduce actuarially fair premiums for an agricultural risk insurance product. We examine hedging effectiveness with LGM-Dairy and show that, even in the absence of basis or production risk, hedging horizon plays an important role in the ability of this tool to smooth farm income over feed cost margins over time. Rating methodology that accounts for tail dependence between milk and feed prices extends the optimal hedging horizon and increases hedging effectiveness of the LGM-Dairy program.

Suggested Citation

  • Marin Bozic & John Newton & Cameron S. Thraen & Brian W. Gould, 2014. "Tails Curtailed: Accounting for Nonlinear Dependence in Pricing Margin Insurance for Dairy Farmers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(4), pages 1117-1135.
  • Handle: RePEc:oup:ajagec:v:96:y:2014:i:4:p:1117-1135.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/ajae/aau033
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Seyyed Ali Zeytoon Nejad Moosavian & Barry K. Goodwin, 2021. "Flexible modelling of multivariate risks in pricing margin protection insurance: modelling portfolio risks with mixtures of mixtures," Applied Economics, Taylor & Francis Journals, vol. 53(4), pages 411-440, January.
    2. Miao, Ruiqing & Khanna, Madhu, 2017. "Costs of meeting a cellulosic biofuel mandate with perennial energy crops: Implications for policy," Energy Economics, Elsevier, vol. 64(C), pages 321-334.
    3. Eddie Anderson & Artem Prokhorov & Yajing Zhu, 2020. "A Simple Estimator of Two‐Dimensional Copulas, with Applications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1375-1412, December.

    More about this item

    Statistics

    Access and download statistics

    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:oup:ajagec:v:96:y:2014:i:4:p:1117-1135.. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.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.