Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-26T17:10:10.038Z Has data issue: false hasContentIssue false
  • English
  • Français

An Application of Safety-First Probability Limits in a Discrete Stochastic Farm Management Programming Model

Published online by Cambridge University Press:  05 September 2016

Upton Hatch ,
Joseph Atwood  and
James Segar
Upton Hatch
Affiliation:
Department of Agricultural Economics and Rural Sociology, Auburn University
Joseph Atwood
Affiliation:
Department of Agricultural Economics and Economics, Montana State University
James Segar
Affiliation:
Pacific Fishery Management Council, Portland, Oregon
Get access Rights & Permissions [Opens in a new window]

Abstract

A sequential decision-making model was developed, and data from farm-raised catfish production were used to demonstrate its use. Outcomes of sequences of decisions which satisfied chance constraints on ending cash balances were traced through a specified time period. Discrete choice variables were specified due to the fixed nature of pond facilities. Recourse actions specified were sale of production in excess of endogenously determined transfer levels or purchase of inputs to supplement needs of the next production stage. Production activities cannot be changed during the planning period. Only yield variability was considered due to its impact on relative competitiveness among growth stages. Deviations were calculated from endogenously determined target levels based on goal and probability limits.

Keywords

chance constraintsdiscrete stochastic programminglimited recourse
Type
Submitted Articles
Information
Journal of Agricultural and Applied Economics , Volume 21 , Issue 1 , July 1989 , pp. 65 - 72
Copyright
Copyright © Southern Agricultural Economics Association 1989

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alabama Crop and Livestock Reporting Service. “Alabama Farm Facts.” Alabama Department of Agriculture, Montgomery, Alabama, monthly reports, 1985-1987.Google Scholar
Anderson, J.R., Dillon, J.L., and Hardaker, B.. Agricultural Decision Analysis. Iowa State University Press, 1977.Google Scholar
Atwood, J. “Demonstration of the Use of Lower Partial Moments to Improve Safety-First Probability Limits.” Amer. J. Agr. Econ., 67(1985):787–793.CrossRefGoogle Scholar
Atwood, J.A., Watts, M.J., and Helmers, G.A.. “Chance-Constrained Financing as a Response to Financial Risk.” Amer. J. Agr. Econ., 70(1988):79–89.CrossRefGoogle Scholar
Barry, P.J., and Robison, L.J.. “A Practical Way to Select an Optimum Farm Plan Under Risk:Comment.” Amer. J. Agr. Econ., 58(1975):128–131.Google Scholar
Charnes, A., and Cooper, W.W.. “Chance—Constrained Programming.” Manage. Sci., 6(1959):73–79.CrossRefGoogle Scholar
De Janvry, A. “Optimal Levels of Fertilization Under Risk: The Potential for Corn and Wheat Fertilization Under Alternative Price Policies in Argentina.” Amer. J. Agr. Econ., 55 (1972):1–10.CrossRefGoogle Scholar
Gebremeskal, T., and Shumway, C.R. “Farm Planning and Calf Marketing Strategies for Risk Management: An Application of Linear Programming and Statistical Decision Theory.” Amer. J. Agr. Econ., 61(1979):363–370.Google Scholar
Hatch, U., Dunham, R., Hebicha, H., and Jensen, J.. “Economic Analysis of Channel Catfish Egg, Fry, Fingerling, and Food Fish Production in Alabama.” Alabama Agricultural Experiment Station Circular 291. Auburn University, Auburn, Alabama.Google Scholar
Hazell, B.P.R., “A Linear Alternative to Quadratic and Semivariance Programming for Farm Planning Under Uncertainty.” Amer. J. Agr. Econ., 53(1971):53–62.Google Scholar
Kataoka, S. “A Stochastic Programming Model.” Econometrica, 31(1963):181–196.CrossRefGoogle Scholar
Kennedy, J.O.S., and Francisco, E.M.. “On the Formulation of Risk Constraints for Linear Programming.” J. of Ag. Econ., 25(1974): 129-145.Google Scholar
Kim, C.S., Shane, R.L., and Yanagida, J.F.. “Alternative Approaches to Risk and Uncertainty in Evaluating Optimal Firm Behavior.” Department of Agricultural Economics. University of Nevada, Reno M.S. 130. 1981.Google Scholar
Mao, J.C.T. “Survey of Capital Budgeting: Theory and Practice.” Journal of Finance, 25, 2(1970):349–360.Google Scholar
Mapp, H.P., Hardin, M.L.. Walker, O.L., and Cersaud, T.. “Analysis of Risk Management Strategies for Agricultural Producers.” Amer. J. Agr. Econ., 61(1979): 1071-1077.CrossRefGoogle Scholar
Musser, W.N., Ohannesian, J., and Benson, F.J.. “A Safety First Model of Risk Management for Use in Extension Programs.” N. Cen. J. of.Agr. Econ., 3(1981):41–46.Google Scholar
Patrick, G., Wilson, P., Barry, P., Boggess, W., and Young, D.. “Risk Perceptions and Management Responses: Producer Generated Hypothesis for Risk Modeling.” So. J. Agr. Econ., 17(1985):231–238.Google Scholar
Pyle, D.H., and Turnovsky, S.J.. “Safety-First and Expected Utility Maximization in Mean-Standard Deviation Portfolio Analysis.” Rev. Econ. Stat, 23(1955):1–16.Google Scholar
Rae, A.N. “An Empirical Application and Evaluation of Discrete Stochastic Programming in Farm Management.” Amer. J. Agr. Econ., 53(1971):625–636.Google Scholar
Roy, A.D. “Safety-First and the Holding of Assets.” Econometrica, 20(1952):431–449.Google Scholar
Sengupta, J.K. “Safety-First Rules Under Chance-Constrained Linear Programming.” Operations Research, 17(1969):112–131.Google Scholar
Tauer, L. “Target MOTAD.” Amer. J. Agr. Econ., 65(1983):606–610.CrossRefGoogle Scholar
Telser, L.G. “Safety-First and Hedging.” Rev. Econ. Studies, 23(1955):1–16.Google Scholar