IDEAS home Printed from https://ideas.repec.org/a/cup/jagaec/v32y2000i02p283-297_02.html
   My bibliography  Save this article

Parametric Modeling and Simulation of Joint Price-Production Distributions under Non-Normality, Autocorrelation and Heteroscedasticity: A Tool for Assessing Risk in Agriculture

Author

Listed:
  • Ramirez, Octavio A.

Abstract

This study presents a way to parametrically model and simulate multivariate distributions under potential non-normality, autocorrelation and heteroscedasticity and illustrates its application to agricultural risk analysis. Specifically, the joint probability distribution (pdf) for West Texas irrigated cotton, corn, sorghum, and wheat production and prices is estimated and applied to evaluate the changes in the risk and returns of agricultural production in the region resulting from observed and predicted price and production trends. The estimated pdf allows for time trends on the mean and the variance and varying degrees of autocorrelation and non-normality (kurtosis and right- or left-skewness) in each of the price and production variables. It also allows for any possible price-price, production-production, or price-production correlation.

Suggested Citation

  • Ramirez, Octavio A., 2000. "Parametric Modeling and Simulation of Joint Price-Production Distributions under Non-Normality, Autocorrelation and Heteroscedasticity: A Tool for Assessing Risk in Agriculture," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 32(2), pages 283-297, August.
  • Handle: RePEc:cup:jagaec:v:32:y:2000:i:02:p:283-297_02
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1074070800020368/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Meyer, Jack, 1977. "Choice among distributions," Journal of Economic Theory, Elsevier, vol. 14(2), pages 326-336, April.
    2. 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.
    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. Featherstone, Allen M. & Kastens, Terry L., 2000. "Non-Parametric and Semi-Parametric Techniques for Modeling and Simulating Correlated, Non-Normal Price and Yield Distributions: Applications to Risk Analysis in Kansas Agriculture," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 32(2), pages 267-281, August.
    2. Poudel, Mahadeb Prasad & Chen, Shwu-En & Ghimire, Raju, 2013. "Rice Yield Distribution and Risk Assessment in South Asian Countries: A Statistical Investigation," International Journal of Agricultural Management and Development (IJAMAD), Iranian Association of Agricultural Economics, vol. 3(1), March.
    3. Asci, Serhat & VanSickle, John J. & Cantliffe, Daniel J., 2013. "The Potential for Greenhouse Tomato Production Expansion in Florida," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143095, Southern Agricultural Economics Association.

    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 A. & Sosa, Romeo, 2000. "Risk Analysis Under Correlated, Non-Normal Price And Yield Probability Distributions," 2000 Annual meeting, July 30-August 2, Tampa, FL 21888, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Ramirez, Octavio A. & Somarriba, Eduardo, 1999. "Joint Modeling And Simulation Of Autocorrelated Non-Normal Time Series: An Application To Risk And Return Analysis," 1999 Annual meeting, August 8-11, Nashville, TN 21564, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Anderson, Kim B. & Mapp, Harry P., Jr., 1996. "Risk Management Programs In Extension," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 21(01), pages 1-8, July.
    4. J. Pannell, David, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, Blackwell, vol. 5(4), pages 361-383, August.
    5. Ramirez, Octavio A. & Carpio, Carlos E., 2015. "Are the Federal Crop Insurance Subsidies Equitably Distributed? Evidence from a Monte Carlo Simulation Analysis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 40(3), pages 1-19, September.
    6. Lien, Gudbrand D. & Flaten, Ola & Schumann, Keith D. & Richardson, James W. & Korsaeth, Audun & Eltun, Ragnar, 2005. "Comparison of Risk Between Cropping Systems in Eastern Norway," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24663, European Association of Agricultural Economists.
    7. Ardian Harri & Cumhur Erdem & Keith H. Coble & Thomas O. Knight, 2009. "Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 163-182.
    8. Rister, M. Edward & Skees, Jerry R., 1982. "The Value Of Outlook Information In Post-Harvest Marketing Strategies," 1982 Annual Meeting, August 1-4, Logan, Utah 279431, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Torkamani, Javad, 2005. "Using a whole-farm modelling approach to assess prospective technologies under uncertainty," Agricultural Systems, Elsevier, vol. 85(2), pages 138-154, August.
    10. 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(01), pages 1-14, April.
    11. Zapata, Hector O. & Maradiaga, David Isaias & Pujula, Aude Liliana & Dicks, Michael R., 2011. "Recent Developments in Unit Root Tests and Historical Crop Yields," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103871, Agricultural and Applied Economics Association.
    12. 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.
    13. Curtis, Kynda R. & Cowee, Margaret W. & Kim, Man-Keun & Harris, Thomas R., 2010. "Evaluating Returns to Cool Season Grass Quality Characteristics for Niche Equine Feed Markets," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 28(01).
    14. Shively, Gerald E., 1999. "Risks and returns from soil conservation: evidence from low-income farms in the Philippines," Agricultural Economics, Blackwell, vol. 21(1), pages 53-67, August.
    15. Love, Ross O. & Robison, Lindon J., 1984. "An Empirical Analysis Of The Intertemporal Stability Of Risk Preference," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 16(01), pages 1-7, July.
    16. Li, Jingyuan & Wang, Jianli & Zhou, Lin, 2024. "Correlation aversion and bivariate stochastic dominance with respect to reference functions," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 157-174.
    17. Kim, Kwansoo & Chavas, Jean-Paul, 2003. "Technological change and risk management: an application to the economics of corn production," Agricultural Economics, Blackwell, vol. 29(2), pages 125-142, October.
    18. Levan Elbakidze & Linda Highfield & Michael Ward & Bruce A. McCarl & Bo Norby, 2009. "Economics Analysis of Mitigation Strategies for FMD Introduction in Highly Concentrated Animal Feeding Regions," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(4), pages 931-950.
    19. Massey, Raymond E. & Williams, Joseph E., 1991. "Swine Breeding Systems: A Stochastic Evaluation With Implications For Emerging Technology," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 23(01), pages 1-9, July.
    20. Moshe Leshno & Haim Levy, 2002. "Preferred by "All" and Preferred by "Most" Decision Makers: Almost Stochastic Dominance," Management Science, INFORMS, vol. 48(8), pages 1074-1085, August.

    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:cup:jagaec:v:32:y:2000:i:02:p:283-297_02. 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/aae .

    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.