IDEAS home Printed from https://ideas.repec.org/a/ags/joaaec/15486.html

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, Southern Agricultural Economics Association, vol. 32(2), pages 1-15, August.
    • Handle: RePEc:ags:joaaec:15486
    DOI: 10.22004/ag.econ.15486
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/15486/files/32020283.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.15486?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
    ---><---

    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. 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.
    2. 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.
    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. Zanini, Fabio C. & Irwin, Scott H. & Schnitkey, Gary D. & Sherrick, Bruce J., 2000. "Estimating Farm-Level Yield Distributions For Corn And Soybeans In Illinois," 2000 Annual meeting, July 30-August 2, Tampa, FL 21720, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. 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.
    5. Parsch, Lucas D. & Loewer, Otto J., 1986. "Risk-Efficiency of Beef-Forage Rotational Grazing Under Weather Uncertainty," 1986 Annual Meeting, July 27-30, Reno, Nevada 278411, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. 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).
    7. Yangxuan Liu & Michael R. Langemeier & Ian M. Small & Laura Joseph & William E. Fry & Jean B. Ristaino & Amanda Saville & Benjamin M. Gramig & Paul V. Preckel, 2018. "A Risk Analysis of Precision Agriculture Technology to Manage Tomato Late Blight," Sustainability, MDPI, vol. 10(9), pages 1-19, August.
    8. Phillips Peter J. & Pohl Gabriela, 2018. "The Deferral of Attacks: SP/A Theory as a Model of Terrorist Choice when Losses Are Inevitable," Open Economics, De Gruyter, vol. 1(1), pages 71-85, February.
    9. Hardaker, J. Brian & Lien, Gudbrand D., 2003. "Stochastic Efficiency Analysis With Risk Aversion Bounds: A Simplified Approach," Working Papers 12954, University of New England, School of Economics.
    10. David J. Pannell, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, International Association of Agricultural Economists, vol. 5(4), pages 361-383, August.
    11. Tabesh, Hamid, 1987. "Hedging price risk to soybean producers with futures and options: a case study," ISU General Staff Papers 1987010108000010306, Iowa State University, Department of Economics.
    12. 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.
    13. Larson, James A. & Roberts, Roland K. & Tyler, Donald D. & Duck, Bob N. & Slinsky, Stephen P., 1998. "Nitrogen-Fixing Winter Cover Crops and Production Risk: A Case Study for No-Tillage Corn," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 30(1), pages 163-174, July.
    14. 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.
    15. M. J. McGregor & P. K. Thornton, 1990. "Information Systems For Crop Management: Prospects And Problems," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(2), pages 172-183, May.
    16. Flaten, O. & Lien, G., 2007. "Stochastic utility-efficient programming of organic dairy farms," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1574-1583, September.
    17. 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.
    18. Jack Meyer & James W. Richardson & Keith D. Schumann, 2009. "Stochastic efficiency analysis with risk aversion bounds: a correction," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(4), pages 521-525, October.
    19. 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.
    20. Lien, Gudbrand, 2003. "Assisting whole-farm decision-making through stochastic budgeting," Agricultural Systems, Elsevier, vol. 76(2), pages 399-413, May.

    More about this item

    Keywords

    ;
    ;

    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:joaaec:15486. 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/saeaaea.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.