IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v68y2019i5p1207-1232.html
   My bibliography  Save this article

Are actuarial crop insurance rates fair?: an analysis using a penalized bivariate B‐spline method

Author

Listed:
  • Michael J. Price
  • Cindy L. Yu
  • David A. Hennessy
  • Xiaodong Du

Abstract

In this paper, we investigate whether the yield insurance premium rates given by the US Department of Agriculture's Risk Management Agency are actuarially fair by comparing the conditional yield density inferred from premium data with the conditional yield density inferred from yield data. A procedure is developed to estimate the conditional yield density by using premium data through partial derivatives of the premium rate function, as fitted by penalized bivariate tensor product B‐splines. We study the asymptotic properties of partial derivatives of a penalized bivariate tensor product B‐spline estimator and provide variance estimates. The conditional yield density inferred from premium data and its variance estimator are evaluated through simulation studies. The procedure is also applied to a crop insurance data set from the state of Iowa to examine the actuarial fairness of the premium rates. On average, premium rates are close to our estimates and this is true for each coverage level. However, premiums for low productivity land are generally too low whereas those for high productivity land are generally too high. Even after subsidies, premiums for the more productive land are generally substantially higher than are our estimates of the corresponding actuarially fair rates.

Suggested Citation

  • Michael J. Price & Cindy L. Yu & David A. Hennessy & Xiaodong Du, 2019. "Are actuarial crop insurance rates fair?: an analysis using a penalized bivariate B‐spline method," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(5), pages 1207-1232, November.
    • Handle: RePEc:bla:jorssc:v:68:y:2019:i:5:p:1207-1232
    DOI: 10.1111/rssc.12363
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssc.12363
    Download Restriction: no
    File URL: https://libkey.io/10.1111/rssc.12363?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
    ---><---

    Citations

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


    Cited by:

    1. Matthew Stuart & Cindy Yu & David A. Hennessy, 2023. "The Impact of Stocks on Correlations between Crop Yields and Prices and on Revenue Insurance Premiums using Semiparametric Quantile Regression," Papers 2308.11805, arXiv.org, revised Jun 2024.
    2. Jisang Yu & Edward D. Perry, 2024. "Premium subsidies and selection in the federal crop insurance program," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(1), pages 280-297, February.
    3. Yuyuan Che & Hongli Feng & David A. Hennessy, 2020. "Recency effects and participation at the extensive and intensive margins in the U.S. Federal Crop Insurance Program," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 52-85, January.
    4. Hongli Feng & Xiaodong Du & David A. Hennessy, 2020. "Depressed demand for crop insurance contracts, and a rationale based on third generation Prospect Theory," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 59-73, January.

    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:bla:jorssc:v:68:y:2019:i:5:p:1207-1232. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.