IDEAS home Printed from https://ideas.repec.org/p/ags/aes008/36865.html
   My bibliography  Save this paper

Sophisticated Program Planning Approaches Generate Large Benefits in High Risk Crop Farming

Author

Listed:
  • Musshoff, Oliver
  • Hirschauer, Norbert

Abstract

Agricultural production relies to a great extent on biological processes in natural environments. In addition to volatile prices, it is thus heavily exposed to risks caused by the variability of natural conditions such as rainfall, temperature and pests. With a view to the apparently lacking support of risky farm production program decisions through formal planning models, the objective of this paper is to examine whether, and eventually by how much, farmers’ “intuitive” program decisions can be improved through formal statistical analyses and stochastic optimization models. In this performance comparison, we use the results of the formal planning approach that are generated in a quasi ex-ante analysis as a normative benchmark for the empirically observed ones. To avoid benchmark solutions that would possibly exceed the respective farmer’s risk tolerance, we limit the formal search to a subset of solutions that are second- degree stochastically dominant compared to the farmer’s own decision. We furthermore compare the suitability of different statistical (time series) models to forecast the uncertainty of single gross margins.

Suggested Citation

  • Musshoff, Oliver & Hirschauer, Norbert, 2008. "Sophisticated Program Planning Approaches Generate Large Benefits in High Risk Crop Farming," 82nd Annual Conference, March 31 - April 2, 2008, Royal Agricultural College, Cirencester, UK 36865, Agricultural Economics Society.
  • Handle: RePEc:ags:aes008:36865
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/36865
    Download Restriction: no

    References listed on IDEAS

    as
    1. K. J. Arrow, 1964. "The Role of Securities in the Optimal Allocation of Risk-bearing," Review of Economic Studies, Oxford University Press, vol. 31(2), pages 91-96.
    2. P. B. R. Hazell, 1971. "A Linear Alternative to Quadratic and Semivariance Programming for Farm Planning under Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(1), pages 53-62.
    3. Rulon D. Pope, 2003. "Agricultural Risk Analysis: Adequacy of Models, Data, and Issues," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(5), pages 1249-1256.
    4. Okunev, John & Dillon, John L., 1988. "A linear programming algorithm for determining mean-Gini efficient farm plans," Agricultural Economics, Blackwell, vol. 2(3), pages 273-285, November.
    5. D. Sornette & P. Simonetti & J. V. Andersen, 1999. ""Nonlinear" covariance matrix and portfolio theory for non-Gaussian multivariate distributions," Papers cond-mat/9903203, arXiv.org.
    6. Adams, Richard M. & Menkhaus, Dale J. & Woolery, Bruce A., 1980. "Alternative Parameter Specification In E, V Analysis: Implications For Farm Level Decision Making," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 5(01), July.
    7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    8. Brekke, Kjell Arne & Moxnes, Erling, 2003. "Do numerical simulation and optimization results improve management?: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 50(1), pages 117-131, January.
    9. B. Curtis Eaves, 1971. "On Quadratic Programming," Management Science, INFORMS, vol. 17(11), pages 698-711, July.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Jolly, Robert W., 1983. "Risk Management in Agricultural Production," Staff General Research Papers Archive 11459, Iowa State University, Department of Economics.
    12. Joyce T. Chen & C. B. Baker, 1974. "Marginal Risk Constraint Linear Program for Activity Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 56(3), pages 622-627.
    13. Okunev, John & Dillon, John L., 1988. "A Linear Programming Algorithm for Determining Mean-Gini Efficient Farm Plans," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 2(3), November.
    14. Darren Hudson & Keith Coble & Jayson Lusk, 2005. "Consistency of risk premium measures," Agricultural Economics, International Association of Agricultural Economists, vol. 33(1), pages 41-49, July.
    15. J. Brian Hardaker & Louise H. Patten & David J. Pannell, 1988. "Utility‐Efficient Programming For Whole‐Farm Planning," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 32(2-3), pages 88-97, 08-12.
    16. Steen Koekebakker & Gudbrand Lien, 2004. "Volatility and Price Jumps in Agricultural Futures Prices—Evidence from Wheat Options," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1018-1031.
    17. Paul V. Preckel & Eric DeVuyst, 1992. "Efficient Handling of Probability Information for Decision Analysis under Risk," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(3), pages 655-662.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    stochastic optimization; stochastic processes; production risk; program planning; time series analysis; C1; C61; M11; Q12;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

    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:aes008:36865. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aesukea.html .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.