IDEAS home Printed from https://ideas.repec.org/a/ags/jlaare/31189.html
   My bibliography  Save this article

On Choosing A Base Coverage Level For Multiple Peril Crop Insurance Contracts

Author

Listed:
  • Ker, Alan P.
  • Coble, Keith H.

Abstract

For multiple peril crop insurance, the U.S. Department of Agriculture's Risk Management Agency estimates the premium rate for a base coverage level and then uses multiplicative adjustment factors to recover rates at other coverage levels. Given this methodology, accurate estimation of the base coverage level from 65% to 50%. The purpose of this analysis was to provide some insight into whether such a change should or should not be carried out. Not surprisingly, our findings indicate that the higher coverage level should be maintained as the base.

Suggested Citation

  • Ker, Alan P. & Coble, Keith H., 1998. "On Choosing A Base Coverage Level For Multiple Peril Crop Insurance Contracts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(2), pages 1-18, December.
    • Handle: RePEc:ags:jlaare:31189
    DOI: 10.22004/ag.econ.31189
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/31189/files/23020427.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.31189?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. Keith H. Coble & Thomas O. Knight & Rulon D. Pope & Jeffery R. Williams, 1996. "Modeling Farm-Level Crop Insurance Demand with Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 439-447.
    2. Bruce A. Babcock & David A. Hennessy, 1996. "Input Demand under Yield and Revenue Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 416-427.
    3. David A. Bessler, 1980. "Aggregated Personalistic Beliefs on Yields of Selected Crops Estimated Using ARIMA Processes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(4), pages 666-674.
    4. Charles B. Moss & J. S. Shonkwiler, 1993. "Estimating Yield Distributions with a Stochastic Trend and Nonnormal Errors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1056-1062.
    5. Myers, Robert J. & Jayne, Thomas S., 1997. "Regime shifts and technology diffusion in crop yield growth paths with an application to maize yields in Zimbabwe," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 41(3), pages 1-19.
    6. Carl H. Nelson & Paul V. Preckel, 1989. "The Conditional Beta Distribution as a Stochastic Production Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 370-378.
    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. Ker, Alan P. & McGowan, Pat, 2000. "Weather-Based Adverse Selection And The U.S. Crop Insurance Program: The Private Insurance Company Perspective," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-25, December.

    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. Makki Shiva S. & Somwaru Agapi L., 2007. "Assessing Adverse Selection in Crop Insurance Markets: An Application of Parametric and Nonparametric Methods," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 2(1), pages 1-22, May.
    2. Arora, Gaurav & Agarwal, Sandip K., 2020. "Agricultural input use and index insurance adoption: Concept and evidence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304508, Agricultural and Applied Economics Association.
    3. Chen, Xiaomei & Wang, H. Holly & Makus, Larry D., 2007. "Production Risk and Crop Insurance Effectiveness: Organic Versus Conventional Apples," SCC-76 Meeting, 2007, March 15-17, Gulf Shores, Alabama 9381, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    4. Park, Eunchun & Brorsen, B. Wade & Harri, Ardian, 2016. "Using Bayesian Spatial Smoothing and Extreme Value Theory to Develop Area-Yield Crop Insurance Rating," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235754, Agricultural and Applied Economics Association.
    5. Ramirez, Octavio A. & McDonald, Tanya U., 2006. "The Expanded Johnson System: A Highly Flexible Crop Yield Distribution Model," 2006 Annual meeting, July 23-26, Long Beach, CA 21455, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Agarwal, Sandip Kumar, 2017. "Subjective beliefs and decision making under uncertainty in the field," ISU General Staff Papers 201701010800006248, Iowa State University, Department of Economics.
    7. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2005. "Elicitation of Subjective Crop Yield PDF for DSS Implementation," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24561, European Association of Agricultural Economists.
    8. 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.
    9. 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).
    10. Norwood, F. Bailey & Roberts, Matthew C. & Lusk, Jayson L., 2002. "How Are Crop Yields Distributed?," 2002 Annual meeting, July 28-31, Long Beach, CA 19733, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    12. Li, Lisha, 2015. "Three essays on crop yield, crop insurance and climate change," ISU General Staff Papers 201501010800005371, Iowa State University, Department of Economics.
    13. Makki, Shiva S. & Somwaru, Agapi, 2002. "Asymmetric Information In Cotton Insurance Markets: Evidence From Texas," 2002 Annual meeting, July 28-31, Long Beach, CA 19827, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Coleman, Jane A. & Shaik, Saleem, 2009. "Time-Varying Estimation of Crop Insurance Program in Altering North Dakota Farm Economic Structure," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49516, Agricultural and Applied Economics Association.
    15. Zhou, Wei & Babcock, Bruce A., 2017. "Using the competitive storage model to estimate the impact of ethanol and fueling investment on corn prices," Energy Economics, Elsevier, vol. 62(C), pages 195-203.
    16. Makus, Larry D. & Wang, H. Holly & Chen, Xiaomei, 2003. "Evaluating Risk Management Strategies For Non-Irrigated Small Grain Producers," 2003 Annual meeting, July 27-30, Montreal, Canada 22257, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    18. Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, vol. 121(4), pages 689-700, December.
    19. Lichtenberg, Erik, 2002. "Agriculture and the environment," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 2, chapter 23, pages 1249-1313, Elsevier.
    20. Alberto Garrido & David Zilberman, 2008. "Revisiting the demand for agricultural insurance: the case of Spain," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 68(1), pages 43-66, May.

    More about this item

    Keywords

    Risk and Uncertainty;

    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:jlaare:31189. 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/waeaaea.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.