IDEAS home Printed from https://ideas.repec.org/p/ags/aaea06/21455.html
   My bibliography  Save this paper

The Expanded Johnson System: A Highly Flexible Crop Yield Distribution Model

Author

Listed:
  • Ramirez, Octavio A.
  • McDonald, Tanya U.

Abstract

The expanded form of the Johnson system advanced in this paper can model any theoretically possible combination of the first four central moments of a random variable, i.e. any mean-variance-skewness-kurtosis combination exhibited by a yield, price or any other distribution that may be encountered in practice. None of the probability distribution models previously in the literature come close to achieving such property. An application involving Illinois farm-level corn yields is presented to illustrate the estimation, characteristics and use of the proposed system. Although the yield data analyzed is from the same state and crop, the skewness and kurtosis combinations implied by the best fitting non-normal models extend over a large region of the S-K plane, corresponding to both the SU and the SB families. Theoretically, it is known that several of these S-K combinations can not be accommodated by the most commonly used parametric models based on the Beta and the Gamma distributions, which corroborates the need for probability distribution models that can span larger areas of this space.

Suggested Citation

  • 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).
    • Handle: RePEc:ags:aaea06:21455
    DOI: 10.22004/ag.econ.21455
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/21455/files/sp06ra03.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.21455?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. Octavio A. Ramírez & Tanya McDonald, 2006. "Ranking Crop Yield Models: A Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(4), pages 1105-1110.
    2. Bailey Norwood & Matthew C. Roberts & Jayson L. Lusk, 2004. "Ranking Crop Yield Models Using Out-of-Sample Likelihood Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1032-1043.
    3. 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.
    4. Anderson, Jock R., 1974. "Simulation: Methodology and Application in Agricultural Economics," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 42(01), pages 1-53, March.
    5. 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.
    6. Alan P. Ker & Keith Coble, 2003. "Modeling Conditional Yield Densities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 291-304.
    7. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    8. Octavio A. Ramírez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
    9. 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.
    10. 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. 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.
    2. Tack, Jesse, 2013. "A Nested Test for Common Yield Distributions with Applications to U.S. Corn," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(01), pages 1-14, April.
    3. 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.

    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. Ramirez, Octavio & Shonkwiler, J. Scott, 2016. "Some Comparative Statics for Evaluating the Performance of the US Crop Insurance Program," SCC-76 Meeting, 2016, March 17-19, Pensacola, Florida 233761, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    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. 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).
    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. 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).
    6. Octavio A. Ramirez & Carlos A. Carpio, 2012. "Premium estimation inaccuracy and the actuarial performance of the US crop insurance program," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(1), pages 117-133, May.
    7. 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(01), pages 1-17, 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. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. Li, Shuang & Ker, Alan P., 2013. "An Assessment of the Canadian Federal-Provincial Crop Production Insurance Program under Future Climate Change Scenarios in Ontario," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151213, Agricultural and Applied Economics Association.
    17. 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.
    18. 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.
    19. 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(01), January.
    20. Jesse Tack & Ardian Harri & Keith Coble, 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1037-1054.

    More about this item

    Keywords

    Crop Production/Industries;

    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:aaea06:21455. 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.