Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T22:08:11.383Z Has data issue: false hasContentIssue false
  • English
  • Français

Scheduling Inputs with Production Functions: Optimal Nitrogen Programs for Rice

Published online by Cambridge University Press:  28 April 2015

Ronald C. Griffin ,
M. Edward Rister ,
John M. Montgomery  and
Fred T. Turner
Ronald C. Griffin
Affiliation:
Department of Agricultural Economics, Texas A & M University
M. Edward Rister
Affiliation:
Department of Agricultural Economics, Texas A & M University
John M. Montgomery
Affiliation:
Department of Agricultural Economics, Texas A & M University
Fred T. Turner
Affiliation:
Soil and Crop Sciences, Texas A & M University
Get access Rights & Permissions [Opens in a new window]

Abstract

The problem of scheduling input applications can be examined by extending conventional production function analysis. Using appropriately designed agricultural experiments, it is possible to estimate production function parameters with alternative specifications for input timing (and amount). A study of nitrogen applications to rice is employed to illustrate scheduling via production functions. Alternative specifications and functional forms are simultaneously examined to determine the sensitivity of economic results to these factors. Sensitivity is found to be high, and this finding is hypothesized to be critical for other approaches to input scheduling as well.

Keywords

schedulingproduction functionssimulationnitrogenrice
Type
Submitted Articles
Information
Journal of Agricultural and Applied Economics , Volume 17 , Issue 1 , July 1985 , pp. 159 - 168
Copyright
Copyright © Southern Agricultural Economics Association 1985

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

Brandon, D. M., Wilson, F. E., Leonards,, W. J. and White, L. M. III. “Timing of Basal Nitrogen in Relation to Permanent Flood of Drill Seeded Labelle Rice (A Preliminary Report).” 72nd Annual Progress Report, Rice Experiment Station, pp. 76–83. Crowley: Louisiana State University Agricultural Experiment Station, 1980.Google Scholar
Debertin, D. L. and Freund, R. J.. “The Deletion of Variables from Regression Models Based on Tests of Significance: A Statistical and Moral Issue.” So. J. Agr. Econ., 7, 1(1975):211–216.Google Scholar
De Datta, S. K.Principles and Practices of Rice Production, New York: John Wiley and Sons, 1981.Google 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., 54(1972):1–10.CrossRefGoogle Scholar
Dillon, J. L.The Analysis of Response in Crop and Livestock Production, Oxford: Pergamon Press, 1979.Google Scholar
Evatt, N. S. “The Timing of Nitrogenous Fertilizer Applications on Rice.” The Mineral Nutrition of the Rice Plant, Proceedings of a Symposium at the International Rice Research Institute, pp. 243–253. Baltimore: Johns Hopkins Press, 1965.Google Scholar
Evatt, N. S. and Hodges, R. J.. “Developing Efficient Systems of Fertilization of Rice.” Six Decades of Rice Research in Texas. Texas Agricultural Experiment Station, Research Monograph 4; June, 1975.Google Scholar
Griffin, R. C., Montgomery, J. M. and Rister, M. E.. “Criteria for Selecting Functional Form in Production Function Analysis.” DIR 84-1, SP 4, Department of Agricultural Economics, Texas A & M University; July, 1984.Google Scholar
Matsushima, S.High-Yielding Rice Cultivation, Tokyo: University of Tokyo Press, 1976.Google Scholar
Mikkelsen, D. S. and De Datta, S. K.. “Rice Culture.” Rice Production and Utilization, pp. 147–234, Westport, Connecticut: AVI Publishing Co., 1980.Google Scholar
Montgomery, J. M. and Parker, M. R.. Supply Schedules for Aerial Fertilizer Application in the Texas Coast, DIR 84-1, SP 6, Department of Agricultural Economics, Texas A & M University; November, 1984.Google Scholar
Musser, W. N. and Tew, B. V.. “Use of Biophysical Simulation in Production Economics.” So. J. Agr. Econ., 16, 1(1984):77–86.Google Scholar
Roumasset, J. “Estimating the Risk of Alternate Techniques: Nitrogenous Fertilization of Rice in the Philippines.” Rev. of Marketing and Agr. Econ., 42,4(1974):257–294.Google Scholar
Ryan, J. G. and Perrin, R. K.. “Fertilizer Response Information and Income Gains: The Case of Potatoes in Peru.” Amer. J. Agr. Econ., 56(1974):337–343.CrossRefGoogle Scholar
Swanson, E. R., Taylor, C. R., and Welch, L. F.. “Economically Optimal Levels of Nitrogen Fertilizer for Corn: An Analysis Based on Experimental Data, 1966-1971.” Illinois Agr. Econ., (July 1974):16–25.Google Scholar
Wallace, T. D. “Pretest Estimation in Regression: A Survey.” Amer. J. Agr. Econ., 59(1977):431–443.CrossRefGoogle Scholar
Yoshida, S.Fundamentals of Rice Crop Science, Los Banos: International Rice Research Institute, 1981.Google Scholar
Ziemer, R. F. “Reporting Econometric Results: Believe It or Not?” Land Econ., 60(1984):122–127.CrossRefGoogle Scholar