Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-03T00:23:56.617Z Has data issue: false hasContentIssue false
  • English
  • Français

A Case Study of Timeliness in the Selection of Risk-Efficient Machinery Complements

Published online by Cambridge University Press:  09 September 2016

Michael E. Wetzstein ,
Wesley N. Musser ,
Ronald W. McClendon  and
David M. Edwards
Michael E. Wetzstein
Affiliation:
Department of Agricultural Economics at the, University of Georgia
Wesley N. Musser
Affiliation:
Department of Agricultural Economics at, Pennsylvania State University
Ronald W. McClendon
Affiliation:
Department of Agricultural Engineering at the, University of Georgia
David M. Edwards
Affiliation:
Model Development at Dun and Bradstreet
Get access Rights & Permissions [Opens in a new window]

Abstract

The importance of timeliness is investigated in the selection of machinery complements for double-crop wheat and soybean production in the southeastern coastal plain. An intertemporal stochastic simulation model was developed to generate probability distributions that were evaluated with stochastic dominance analysis. This research investigated the importance of intertemporal production linkages and inadequate soil moisture on machinery selection. Failure to include these dimensions can result in erroneous machinery choices.

Keywords

double-croppingwheatsoybeansstochastic simulation
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 22 , Issue 2 , December 1990 , pp. 165 - 177
Copyright
Copyright © Southern Agricultural Economics Association 1990

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

Agricultural Engineers Yearbook. American Society of Agricultural Engineers. St. Joseph, MI, 1983.Google Scholar
Baker, T.G. and McCarl, B.A.. “Representing Farm Resource Availability Over Time in Linear Programs: A Case Study”. No. Cent. J. Agr. Econ. 4(1982):59–68.Google Scholar
Boggess, W.G. Cardelli, D.T., and Barfield, C.S.. “A Bioeconomic Simulation Approach to Multi-Species Insect Management”. So. J. Agr. Econ. 17(1985):43–56.Google Scholar
Boggess, W.G. Lynne, G.D., Jones, J.W., and Swanny, D.P.. “Risk-Return Assessment of Irrigation Decisions in Humid Regions”. So. J. Agr. Econ. 15(1983): 135–143.Google Scholar
Brink, L. and McCarl, B.A.. “The Adequacy of a Crop Planning Model for Determining Income, Income Change, and Crop Mix”. Canadian J. Agr. Econ. 27(1979):13–25.Google Scholar
Castle, E.N. Becker, M.H., and Nelson, A.G.. Farm Business Management. 3rd edition. New York: Mac-Millian Publishing Company, 1987.Google Scholar
Chen, L.H. and McClendon, R.W.. “Selection of Planting Schedule for Soybeans via Simulation”. Transactions of the ASAE, 27(1984):29-32,35.Google Scholar
Chen, L.H. and McClendon, R.W.. “Soybean and Wheat Double Cropping Simulation Model”. Transactions of the ASAE, 28(1985):65–69.CrossRefGoogle Scholar
Clements, A.M. Mapp, H.P., and Eidman, V.R.. A Procedure for Correlating Events in Farm Firm Simulation Models. Oklahoma Agricultural Experiment Station Bulletin T-131, 1971.Google Scholar
Danok, A.B. McCarl, B.A., and White, T.K.. “Machinery Selection and Crop Planning on a State Farm in Iraq”. Am. J. Agr. Econ. 60(1978):544–549.Google Scholar
Danok, A.B. McCarl, B.A., and White, T.K.. “Machinery Selection Modeling Incorporation of Weather Variability”. Am. J. Agr. Econ. 62(1980):700–708.Google Scholar
Dillon, J.L. The Analysis of Response in Crop and Livestock Production. 2nd edition. Oxford: Pergamon, 1977.Google Scholar
Edwards, W. and Boehlje, M.. “Machinery Selection Considering Timeliness Losses”. Transactions of the ASAE, 23(1980):810–915, 821.Google Scholar
Erbach, B.C. and Lovely, W.G.. “Machinery Adaptation for Multiple Cropping”. In Multiple Cropping. ASA Special Publication No. 29. American Society of Agronomy, Madison, WI, (1976):339.Google Scholar
Farm Economics Information Center. Crop Enterprise Budgets. Department of Agricultural Economics, University of Georgia, 1977-1983.Google Scholar
Georgia Crop Reporting Service. Georgia Agricultural Facts. 1973-1983.Google Scholar
Hargrove, W.L. and Radcliffe, D.E.. Personal Communication. Department of Agronomy, University of Georgia, Athens, GA, 1984.Google Scholar
Heady, E.O. Economics of Agricultural Production and Resource Use. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1952.Google Scholar
Johnson, S.R. and Rausser, G.C.. “Systems Analysis and Simulation: A Survey of Applications in Agricultural and Resource Economics”. Survey of Agricultural Economics Literature, Vol. 2. ed. Judge, G.G. et al. Minneapolis: University of Minneapolis Press, 1977.Google Scholar
Kletke, D.D. Operations Manual for the Oklahoma State University Enterprise Budget Generator. Oklahoma Agricultural Experiment Station Research Report P1979, August, 1979.Google Scholar
Lewis, W.M. and Phillips, J.A.. “Double Cropping in the Eastern United States”. In Multiple Cropping. ASA Special Publication No. 29. American Society of Agronomy, Madison, WI, (1976):41–50.Google Scholar
Marra, M.C. and Carlson, G.A.. “Examining Double Cropping with Utility Theory”. Selected paper presented at the 1984 American Agricultural Economics Meetings in Ithaca, NY.Google Scholar
Miller, B.R. “Minimum Cost Machinery Complement for Various Farm Situations”. Presented paper at the 1980 American Society of Agricultural Engineers Summer Meetings, San Antonio, Texas.Google Scholar
Musser, W.N. McCarl, B.A., and Smith, G.S.. “An Investigation of the Relationship Between Constraint Omission and Risk Aversion Firm Risk Programming Models”. So. J. Agr. Econ. 18(1986): 147–154.Google Scholar
Parker, M.B. Marchant, W.H., and Mullinix, B.J.. “Date of Planting and Row Spacing Effects on Four Soybean Cultivars”. Agronomy J. 73(1981):759–762.CrossRefGoogle Scholar
Reid, D.W. and Bradford, G.. “On Optimal Replacement of Farm Tractors”. Am. J. Agr. Econ. 65(1983):326–331.Google Scholar
Russell, N.P. LaDue, E.L., and Milligan, R.A.. “Choice Criteria in Farm Management Models—A Comparative Study of Machinery Complement Selection”. No. Cent. J. Agr. Econ. 6(1984):136–141.CrossRefGoogle Scholar
Tew, B.V. Musser, W.N., and Smith, G.S.. “Using Non-Contemporaneous Data to Specify Risk Programming Models”. N. E. J. Agr. & Res. Econ. 17(1988):30–35.Google Scholar
Threadgill, E.D. Personal Communication. Department of Agricultural Engineering, Coastal Plain Experiment Station, University of Georgia, Tifton, Georgia, 1984.Google Scholar
Ungar, P.W. and Stewart, B.A.. “Land Preparation and Seeding Establishment Practices in Multiple Cropping Systems”. In Multiple Cropping. ASA Special Publication No. 29. American Society of Agronomy, Madison, WI, 1976.Google Scholar
Wetzstein, M.E. Edwards, D.M., Musser, W.N., and McClendon, R.W.. An Economic Simulation of Risk Efficiency Among Alternative Double Crop Machinery Selections, University of Georgia Agricultural Experiment Station, Research Bulletin Number 342, 1986.Google Scholar