An Economic-Linear Programming Model of the U.S. Petroleum Refining Industry

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Abstract
The linking of statistically estimated relationships with an engineering linear programming model offers important potentials for simulation and forecasting models of industries. This article describes such a model of the U.S. petroleum refining industry. Econometric techniques are used to specify product demands, prices, and some technical adjustments. A linear programming specification of the production function, assuming cost minimization, determines crude oil input requirements, the output of by-products, and the utilization of capacity. As applications of the model, a sample period calculation and a five-year forecast are presented along with a discussion of alternative cases and forecast error.

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