Agricultural response analysis in a longer term framework

Issues of long term soil fertility decline and sustainability are becoming more important for cropping industries in Australia. Helping to manage the level of soil fertility in this context is an aim of economic response analysis. This paper reviews the theory and methods used by economists to derive the optimal level of an input to be used in a production process. In particular, response functions generated by a crop simulation model are used as a basis for the analysis. The use of such models is becoming widespread in the research and extension community. A variety of methods are presented, in increasing order of complexity, to account for the real world characteristics of the production environment in this context.

[1]  John O.S. Kennedy,et al.  Applications of Dynamic Programming to Agriculture, Forestry and Fisheries: Review and Prognosis , 1981 .

[2]  The Value of Stabilizing Fertilizer under Carry-Over Conditions , 1989 .

[3]  Jack A. Meyer,et al.  Choice among distributions , 1977 .

[4]  C. R. Taylor.  Certainty Equivalence for Determination of Optimal Fertilizer Application Rates with Carry-over , 1983 .

[5]  R. Just,et al.  Estimation of farmers' risk attitude: an econometric approach , 1997 .

[6]  P. Waggoner,et al.  Fitting the Law of the Minimum to Fertilizer Applications and Crop Yields 1 , 1979 .

[7]  B. McCarl.  Preference Among Risky Prospects Under Constant Risk Aversion , 1988, Journal of Agricultural and Applied Economics.

[8]  J. Lowenberg‐DeBoer,et al.  Modelling stochastic crop response to fertilisation when carry-over matters , 1991 .

[9]  Peter Hayman,et al.  A survey of farmer practices and attitudes to nitrogen management in the northern New South Wales grains belt , 1999 .

[10]  .. CentroInternacionaldeMejoramientodeMaízyTrigo.  From agronomic data to farmer recommendations : an economics training manual , 1988 .

[11]  R. Dalal,et al.  Long-term trends in fertility of soils under continuous cultivation and cereal cropping in southern queensland. I overall changes in soil properties and trends in winter cereal yields , 1986 .

[12]  K. Parton,et al.  Stochastic dominance and mean-standard deviation analysis: some critical issues , 1995 .

[13]  Satya N. Yadav,et al.  Dynamic Optimization of Nitrogen Use When Groundwater Contamination is Internalized at the Standard in the Long Run , 1997 .

[14]  P. Bardsley,et al.  An Approach To The Econometric Estimation Of Attitudes To Risk In Agriculture , 1987 .

[15]  Quinn Weninger,et al.  Are Crop Yields Normally Distributed? , 1999 .

[16]  J. Pratt.  RISK AVERSION IN THE SMALL AND IN THE LARGE11This research was supported by the National Science Foundation (grant NSF-G24035). Reproduction in whole or in part is permitted for any purpose of the United States Government. , 1964 .

[17]  Wesley N. Musser,et al.  Makeham, J. P., and L. R. Malcolm. The Farming Game. Armidale, N.S.W., Australia: Gill Publications, 1981, 560 pp., $30.00 , 1983 .

[18]  G. Sain,et al.  Continuous economic analysis of crop response to fertilizer in on-farm research , 1992 .

[19]  Eli Feinerman,et al.  Dynamic Optimisation of Nitrogen Fertilisation of Citrus and the Value of Information from Leaf Tissue Analysis , 1995 .

[20]  Jock R. Anderson.  One more or less cheer for optimality , 1975 .

[21]  John O.S. Kennedy,et al.  Optimal fertilizer carryover and crop recycling policies for a tropical grain crop , 1973 .

[22]  John O.S. Kennedy,et al.  An Alternative Method for Deriving Optimal Fertilizer Rates: Comment and Extension , 1981 .

[23]  Jerald J. Fletcher,et al.  Incorporating Stochastic Variables in Crop Response Models: Implications for Fertilization Decisions , 1993 .

[24]  C. S. Kim,et al.  Policy Implications of a Water Quality-constrained Dynamic Model of Nitrogen Fertilizer Use , 1991 .

[25]  J. Pratt.  RISK AVERSION IN THE SMALL AND IN THE LARGE11This research was supported by the National Science Foundation (grant NSF-G24035). Reproduction in whole or in part is permitted for any purpose of the United States Government. , 1964 .

[26]  John L. Dillon,et al.  The Analysis of Response in Crop and Livestock Production , 1977 .

[27]  Jock R. Anderson.  Economic Interpretation of Fertilizer Response Data , 1967 .

[28]  Oscar R. Burt,et al.  An Economic Evaluation of Nitrogen Fertilization of Grasses When Carry-over is Significant , 1975 .

[29]  David J. Pannell,et al.  UTILITY‐EFFICIENT PROGRAMMING FOR WHOLE‐FARM PLANNING , 1988 .

[30]  J. Dillon,et al.  Agricultural Decision Analysis , 1977 .

[31]  Graeme L. Hammer,et al.  APSIM: a novel software system for model development, model testing and simulation in agricultural systems research , 1996 .

[32]  Q. Paris,et al.  A New Analytical Framework for the Fertilization Problem , 1981 .

[33]  J. Thornley.  Mathematical models in agriculture : a quantitative approach to problems in agriculture and related sciences , 1985 .

[34]  A. Onken,et al.  Nitrogen Carry-over Impacts in Irrigated Cotton Production, Southern High Plains , 1989 .

[35]  J. Hammond.  Simplifying the Choice between Uncertain Prospects Where Preference is Nonlinear , 1974 .

[36]  Wm Strong,et al.  Nitrogen requirements of irrigated wheat on the Darling Downs , 1981 .