AN ECONOMIC ANALYSIS OF THE ON-FARM GRAIN HANDLING DECISION PROBLEM

RICHARD MATTHEW KLEMME, Purdue University

Abstract

The decision to build on-farm grain handling facilities is a complex multi-period problem. The expected life of the facility extend over many years. Certain production, cost, or marketing conditions may result in less than full use of the facility. The complexity of the problem increases with the realization that these future economic and technical conditions are not easily predictable. The problems investigated in this research involve the determination of the production, cost, and marketing gains to the on-farm grain handling facility and the determination of the factors that influence the demand for these facilities, particularly the dryer and storage capacity. The individual gains result from reduced harvest delays, reduced costs of handling the grain, and increased grain price from marketing to many facilities. The factors that influence the demand for on-farm facilities over commercial facilities include the decision-maker's aversion to uncertain incomes, the level of harvest delay, the gain in price from marketing to other locations, and changes in the combine size. This study attempts to model the decision-making environment surrounding the selection of optimal dryer and storage capacity. The environment includes the production, cost, and marketing conditions that aid in the determination of the benefits to the investment over time. An annual farm planning equilibrium model is used to conduct this study. The costs of the investment activities are annualized, and the benefits determined within the modeling framework are also annualized. Annualization enables the time framework of the problem to be reduced to a single production period. The farm planning model is adapted in order to include the sources of income uncertainty and to better describe the investment decision-making environment. The sources of income uncertainty are divided into two components, or sections of the model. The price source is included in the marketing component and is modeled by the Minimization of Total Negative Deviations approach. The harvest source (yields, moisture contents, and good field days) is located in the production component. This component is modeled by the Discrete Stochastic Programming (DSP) approach, which involves creating states of nature that, in this case, describe different harvest season scenarios. The model then selects the optimal dryer and storage capacity based on the overview of these harvest scenarios. The harvest source of uncertainty is modeled by using a linear approximation of Quadratic Programming as it is applied to the DSP component. The results of this study indicate that there are positive gains to production, cost, and marketing from the on-farm grain handling facility. The marketing gain is generally larger than the production gain which exceeds the cost gain. The order of these gains is consistent across the many modeling situations used in this research. The demand for dryer and storage capacity is responsive to changes in the decision-making environment. The demand is particularly responsive to different levels of aversion to income uncertainty. Increases in the model's aversion to price-induced income uncertainty cause the demand for storage to decrease. This result occurs because increased aversion leads to sales diversification. Some of the sales activities deliver grain at harvest resulting in the reduction in storage demanded. Increases in the model's aversion to production-induced income uncertainty, however, lead to increases in the demand for storage. This occurs as a result of the state of nature incomes being forced together as the model becomes more averse to income variation. Other results were found in subsequent analysis. The combination drying system was found to be economically superior to the continuous flow system. The model seemed to be receptive to the introduction of a grain reserve program.

Degree

Ph.D.

Subject Area

Agricultural economics

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