An Applied Procedure for Estimating and Simulating Multivariate Empirical (MVE) Probability Distributions In Farm-Level Risk Assessment and Policy Analysis

Simulation as an analytical tool continues to gain popularity in industry, government, and academics. For agricultural economists, the popularity is driven by an increased interest in risk management tools and decision aids on the part of farmers, agribusinesses, and policy makers. Much of the recent interest in risk analysis in agriculture comes from changes in the farm program that ushered in an era of increased uncertainty. With increased planting flexibility and an abundance of insurance and marketing alternatives farmers face the daunting task of sorting out many options in managing the increased risk they face. Like farmers, decision makers throughout the food and fiber industry are seeking ways to understand and manage the increasingly uncertain environment in which they operate. The unique abilities of simulation as a tool in evaluating and presenting risky alternatives together with an expected increase in commodity price risk, as projected by Ray, et al., will likely accelerate the interest in simulation for years to come.

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

[2]  D. G. de la Torre Ugarte,et al.  Estimating Price Variability in Agriculture: Implications for Decision Makers , 1998, Journal of Agricultural and Applied Economics.

[3]  James W. Richardson,et al.  Description of FLIPSIM V: a General Firm Level Policy Simulation Model. , 1986 .

[4]  C. R. Taylor Two Practical Procedures for Estimating Multivariate Nonnormal Probability Density Functions , 1990 .

[5]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[6]  Robert P. King,et al.  THE AGRICULTURAL RISK MANAGEMENT SIMULATOR MICROCOMPUTER PROGRAM , 1988 .

[7]  Paul L. Fackler,et al.  Modeling Interdependence: An Approach to Simulation and Elicitation , 1991 .

[8]  Wayne L. Winston Simulation Modeling Using Risk , 1995 .

[9]  J. Richardson,et al.  Farm Size Evaluation in the El Paso Valley: A Survival/Success Approach , 1981 .

[10]  James W. Richardson,et al.  Empirical Distributions and Production Analysis: A Documentation Using Meteorological Data , 1989 .

[11]  Joseph L. Hammond,et al.  Generation of Pseudorandom Numbers with Specified Univariate Distributions and Correlation Coefficients , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[12]  R. Huirne,et al.  Coping with Risk in Agriculture , 1997 .

[13]  R. D. Smet Simulation modeling and analysis (2nd edition): Averill M. Law and W. David Kelton McGraw-Hill, Inc., New York, 1991, xxii + 759 pages, £31.05, ISBN 0 07 036698 5 , 1993 .

[14]  Earl O. Heady,et al.  Operations research methods for agricultural decisions , 1972 .

[15]  Robert P. King,et al.  Operational Techniques for Applied Decision Analysis Under Uncertainty , 1979 .