IDEAS home Printed from https://ideas.repec.org/p/ags/rrsr94/307864.html
   My bibliography  Save this paper

New Procedures in Modeling Risk: Nihil Novum Sub Sol Est

Author

Listed:
  • Moss, Charles B.
  • Boggess, William G.

Abstract

No abstract is available for this item.

Suggested Citation

  • Moss, Charles B. & Boggess, William G., 1992. "New Procedures in Modeling Risk: Nihil Novum Sub Sol Est," 1992 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, March 22-25, 1992, Orlando, Florida 307864, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    • Handle: RePEc:ags:rrsr94:307864
    DOI: 10.22004/ag.econ.307864
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/307864/files/s-232-010.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.307864?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. King, Robert P. & Black, J. Roy & Benson, Fred J. & Pavkov, Patti A., 1988. "The Agricultural Risk Management Simulator Microcomputer Program," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 20(2), pages 165-171, December.
    2. C. Robert Taylor, 1990. "Two Practical Procedures for Estimating Multivariate Nonnormal Probability Density Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(1), pages 210-217.
    3. 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.
    4. Taylor, C. Robert, 1984. "A Flexible Method For Empirically Estimating Probability Functions," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(1), pages 1-11, July.
    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. 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.
    2. Ramirez, Octavio A. & Carpio, Carlos E. & Rejesus, Roderick M., 2011. "Can Crop Insurance Premiums Be Reliably Estimated?," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(1), pages 1-14, April.
    3. Coble, Keith H. & Heifner, Richard G. & Zuniga, Manuel, 2000. "Implications Of Crop Yield And Revenue Insurance For Producer Hedging," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-21, December.
    4. Lu, Yue & Ramirez, Octavio A. & Rejesus, Roderick M. & Knight, Thomas O. & Sherrick, Bruce J., 2008. "Empirically Evaluating the Flexibility of the Johnson Family of Distributions: A Crop Insurance Application," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), pages 1-13, April.
    5. 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.
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. Richardson, James W. & Klose, Steven L. & Gray, Allan W., 2000. "An Applied Procedure For Estimating And Simulating Multivariate Empirical (Mve) Probability Distributions In Farm-Level Risk Assessment And Policy Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 32(2), pages 1-17, August.
    11. 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.
    12. 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.
    13. Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogério Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná State," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(1), January.
    14. Kapiamba, Luabeya F., 2005. "Modeling Heteroskedasticity of Crop Yield Distributions: Implications for Normality," 2005 Annual meeting, July 24-27, Providence, RI 19475, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    15. 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).
    16. Qiujie Zheng & H. Holly Wang & Qing Hua Shi, 2014. "Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2108-2118, June.
    17. Moss, Charles B. & Shonkwiler, J. S., 1991. "Modeling Yield With Stochastic Trend And Nonnormal Errors," 1991 Annual Meeting, August 4-7, Manhattan, Kansas 271165, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogerio Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná Stats," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(1), pages 1-16, March.
    19. 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.
    20. VanTassell, L. W. & Richardson, J. W. & Conner, J. R., 1987. "Incorporating Environmental Uncertainties In A Ranch Simulation," 1987 Annual Meeting, August 2-5, East Lansing, Michigan 269979, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    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:rrsr94:307864. 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: .

    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.