IDEAS home Printed from https://ideas.repec.org/p/ags/aaea14/170173.html
   My bibliography  Save this paper

An Application of Kernel Density Estimation via Diffusion to Group Yield Insurance

Author

Listed:
  • Ramsey, Ford

Abstract

The recent priority given to Federal Crop Insurance as an agricultural policy instrument has increased the importance of rate making procedures. Actuarial soundness requires rates that are actuarially fair: the premium is set equal to expected loss. Formation of this expectation depends, in the case of group or area yield insurance, on precise estimation of the probability density of the crop yield in question. This paper applies kernel density estimation via diffusion to the estimation of crop yield probability densities and determines ensuing premium rates. The diffusion estimator improves on existing methods by providing a cogent answer to some of the issues that plague both parametric and nonparametric techniques. Application shows that premium rates can vary significantly depending on underlying distributional assumptions; from a practical point of view there is value to be had in proper specification.

Suggested Citation

  • Ramsey, Ford, 2014. "An Application of Kernel Density Estimation via Diffusion to Group Yield Insurance," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170173, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea14:170173
    DOI: 10.22004/ag.econ.170173
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/170173/files/diffusion_aaea.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.170173?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. Chen, Shu-Ling & Miranda, Mario J., 2004. "Modeling Multivariate Crop Yield Densities With Frequent Extreme Events," 2004 Annual meeting, August 1-4, Denver, CO 19970, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    3. Joseph W. Glauber, 2013. "The Growth Of The Federal Crop Insurance Program, 1990--2011," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 482-488.
    4. Richard E. Just & Quinn Weninger, 1999. "Are Crop Yields Normally Distributed?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(2), pages 287-304.
    5. Bruce J. Sherrick & Fabio C. Zanini & Gary D. Schnitkey & Scott H. Irwin, 2004. "Crop Insurance Valuation under Alternative Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 406-419.
    6. Alan P. Ker & Barry K. Goodwin, 2000. "Nonparametric Estimation of Crop Insurance Rates Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(2), pages 463-478.
    7. Joseph Atwood & Saleem Shaik & Myles Watts, 2003. "Are Crop Yields Normally Distributed? A Reexamination," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 888-901.
    8. Mario J. Miranda, 1991. "Area-Yield Crop Insurance Reconsidered," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(2), pages 233-242.
    9. Zhu, Ying & Goodwin, Barry K. & Ghosh, Sujit K., 2011. "Modeling Yield Risk Under Technological Change: Dynamic Yield Distributions and the U.S. Crop Insurance Program," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(1), pages 1-19, April.
    10. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    11. Carl H. Nelson, 1990. "The Influence of Distributional Assumptions on the Calculation of Crop Insurance Premia," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 12(1), pages 71-78.
    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. Ker, Alan. P & Tolhurst, Tor & Liu, Yong, 2015. "Rating Area-yield Crop Insurance Contracts Using Bayesian Model Averaging and Mixture Models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205211, Agricultural and Applied Economics Association.
    2. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Douadia Bougherara & Laurent Piet, 2018. "On the role of probability weighting on WTP for crop insurance with and without yield skewness," Working Papers hal-02790605, HAL.
    4. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    5. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    6. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
    7. Lanoue, Christopher & Sherrick, Bruce J. & Woodard, Joshua D. & Paulson, Nicholas D., 2010. "Evaluating Yield Models for Crop Insurance Rating," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61761, Agricultural and Applied Economics Association.
    8. Phoebe Koundouri & Nikolaos Kourogenis, 2011. "On the Distribution of Crop Yields: Does the Central Limit Theorem Apply?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(5), pages 1341-1357.
    9. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2008. "Shape Persistence in Elicited Subjective Crop Yield Probability Density Functions," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44128, European Association of Agricultural Economists.
    10. Gerlt, Scott & Westhoff, Patrick, 2013. "Analysis of the Supplemental Coverage Option," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 156704, Agricultural and Applied Economics Association.
    11. Gerlt, Scott & Westhoff, Patrick, "undated". "Comparison of County ARC and SCO," 2014 AAEA: Crop Insurance and the 2014 Farm Bill Symposium: Implementing Change in U.S. Agricultural Policy, October 8-9, 2014, Louisville, KY 184289, Agricultural and Applied Economics Association.
    12. Ghahremanzadeh, Mohammad & Mohammadrezaei, Rassul & Dashti, Ghader & Ainollahi, Moharram, 2018. "Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 17(02), January.
    13. Tor N. Tolhurst & Alan P. Ker, 2015. "On Technological Change in Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 137-158.
    14. Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2014. "Yield Trend Estimation in the Presence of Farm Heterogeneity and Non-linear Technological Change," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 53(2), pages 1-20, May.
    15. Gerlt, Scott & Thompson, Wyatt & Miller, Douglas, 2014. "Exploiting the Relationship between Farm-Level Yields and County-Level Yields for Applied Analysis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-18.
    16. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1605-1634, September.
    17. David A. Hennessy, 2009. "Crop Yield Skewness Under Law of the Minimum Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 197-208.
    18. Zheng, Qiujie & Wang, H. Holly & Shi, Qinghua, 2008. "Estimating Farm Level Multivariate Yield Distribution Using Nonparametric Methods," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6509, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Ramirez, Octavio A. & Shonkwiler, J. Scott, 2017. "A Probabilistic Model of Crop Insurance Purchase Decision," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(1), pages 1-17, January.
    20. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.

    More about this item

    Keywords

    Agricultural and Food Policy; Research Methods/ Statistical Methods; Risk and Uncertainty;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:aaea14:170173. 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/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.