IDEAS home Printed from https://ideas.repec.org/p/ags/aaea03/21942.html
   My bibliography  Save this paper

Development Of A Stochastic Model To Evaluate Plant Growers' Enterprise Budgets

Author

Listed:
  • Ludena, Carlos E.
  • McNamara, Kevin T.
  • Hammer, P. Allen
  • Foster, Kenneth A.

Abstract

Increased domestic concentration and international competition in the floricultural industry are forcing growers to improve resource management efficiency. Cost management and cost accounting methods are becoming key tools as growers attempt to reduce costs. These tools allow growers to allocate costs for each crop, increasing their greenhouse planning abilities. Growers have a relative high degree of risk due to potential crop and market failure. Individual growers have different tolerance for risk and risk bearing capacity. Growers need a cost accounting system that incorporates production and market risk, a system that allows them to make informed business decisions. The research reported in this paper developed a greenhouse budgeting model that incorporated risk to allow growers to compare production costs for flowers with different genetics and production technologies. This enables greenhouse growers to make production management decisions that incorporate production and market risk. The model gives growers the option of imputing their own production data to evaluate how various yield and price assumptions influence income and expense projections, and ultimately, profit. The model allows growers to compare total production cost and revenue varying grower type, production time, geographical location, operation size, and cost structure. The model evaluates budgets for growers who market to mass-market retail operations or wholesale intermediaries who sell to merchandisers or flower shops distribution channels. The model was demonstrated with sample data to illustrate how incorporating risk analysis into a grower's greenhouse budget model effects resource allocation and production decisions as compare to a budget model that does not incorporate risk. Deterministic and stochastic models were used to demonstrate differences in production decisions under various assumptions. The stochastic model introduced prices and flowering characteristics variability. The @Risk software was used to generate the random number simulation of the stochastic model, and stochastic dominance analysis was used to rank the alternatives. The result for both the deterministic and stochastic models identified the same cultivar as most profitable. However, there were differences in crop profits levels and rankings for subsequent cultivars that could influence growers' production choice decisions. The grower's risk aversion level influenced his/her choice of the most profitable cultivars in the stochastic model. The model summarizes the sources of variability that affect cost and revenue. The model enables the grower to measure effects that change in productivity might have on profit. Growers can identify items in their budget that have a greater effect on profitability, and make adjustments. The model can be used to allocate cost across activities, so the grower would be able to measure the economic impact of an item on the budget.

Suggested Citation

  • Ludena, Carlos E. & McNamara, Kevin T. & Hammer, P. Allen & Foster, Kenneth A., 2003. "Development Of A Stochastic Model To Evaluate Plant Growers' Enterprise Budgets," 2003 Annual meeting, July 27-30, Montreal, Canada 21942, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea03:21942
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/21942
    Download Restriction: no

    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," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 20(02), December.
    2. Wilson, Paul N. & Eidman, Vernon R., 1983. "An Empirical Test Of The Interval Approach For Estimating Risk Preferences," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 8(02), December.
    Full references (including those not matched with items on IDEAS)

    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:aaea03:21942. 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/aaeaaea.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.