Impact of weather and crop price information on grain marketing decisions under risk and uncertainty
Abstract
The purpose of this study was to determine the extent to which grain marketing strategies which are conditional on realized weather and price movements, are superior to the marketing strategies decided just once at the beginning of the decision period and implemented at appropriate times, regardless of the random events that occur during the crop season. Farmers with different risk preferences and debt commitments were chosen for the analysis. The effects of decision-makers' risk attitudes, debt commitments and government program participation decisions on their use of futures contracts and put options were also examined. A nonlinear optimization model was developed to analyze the problem on hand. Corn prices and yield, and soybean revenues were random in the study. Discrete approximations of the random variables were obtained using Gaussian Quadrature procedure, and incorporated into the optimization model. Farmers were allowed to react to new information received, by choosing appropriate levels of futures contracts and put options at each period. This was achieved using special reaction functions. Results of the study indicated that there were no significant gains to farmers in using grain marketing strategies that are conditional on the realized weather and price movements. The moderately risk averse individuals did not react to the dynamics of price or weather movements along the decision period, whereas the highly risk averse decision-makers reacted to weather information in making their hedging decisions. Optimal solutions for the 'reactive' and the 'non-reactive' models indicated that (i) the hedge positions increased with the relative risk aversion coefficients, and (ii) the quantities hedged increased (decreased) with debt levels of the moderate (highly) risk averse decision-makers. Farmers' optimal hedge positions decreased substantially when government program participation alternatives were included in the model.
Degree
Ph.D.
Advisors
Preckel, Purdue University.
Subject Area
Agricultural economics
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