Ordinary least squares regression analysis is used to develop a model to forecast the Permian Basin rig count. Comparative analyses of various independent variables in linear, logarithmic and rate-of-change form indicate that approximately ninety percent of the variation in rig count can be explained using four independent variables. These variables represent Windfall Profits Tax, the maximum marginal personal income tax rate, crude oil price, and hourly wages of production workers in oil and gas extraction.

Keywords:
artificial intelligence, oil price, tax variable, drilling activity, autocorrelation, coefficient, rig count, spe 12602, hourly earnings, variation
Subjects:
Information Management and Systems
Copyright 1984, Society of Petroleum Engineers of AIME
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