Derived Demand and Capacity Planning Under Uncertainty

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Abstract
This paper is concerned with the derivation of demand functions for primary resources in an economic environment with uncertainty. This issue is critical when resource markets must decide, in the face of uncertainty, whether to expand capacity and/or to introduce new technologies. The models proposed are primarily data oriented. They explore two alternative behavioral models of action under uncertainty: here-and-now and wait-and-see. We present an application to the U.S. energy sector's demand for coal and the related expansion of capacity of coal-fired electricity generation plants.

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