Emergency Government Interventions: Case Study of Natural Gas Shortages

Abraham Charnes, William W. Cooper, Wilpen L. Gorr, Cheng Hsu and Burkhard von Rabenau
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Abraham Charnes: College of Business Administration, University of Texas, Austin, Texas 78712
William W. Cooper: College of Business Administration, University of Texas, Austin, Texas 78712
Wilpen L. Gorr: School of Urban & Public Affairs, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213
Cheng Hsu: School of Management, Rensselaer Polytechnic Institute, Troy, New York 12181
Burkhard von Rabenau: Department of City and Regional Planning, The Ohio State University, Columbus, Ohio 43210

Management Science, 1986, vol. 32, issue 10, 1242-1258

Abstract: We present a framework, decision models, and supporting methods to improve government's decisions on a class of intervention problems. The example used is on natural gas shortages. We provide three decision models that move progressively from regulated market mechanisms as a means of gas allocation to nonprice-based directives as shortages become more serious. A critical aspect of this framework is government's timing in switching decision models and changing levels of decision variables. We provide new results on chance constraints that enable time series forecasting as the basis for triggering intervention decisions. In particular, we show that the forecasted regression quantile function for the underlying stochastic process of a chance constraint is the deterministic equivalent for the constraint. Lastly, we evaluate some government decisions on the 1976/77 natural gas shortage in Ohio by applying our methods in a simulation of the conditions of that time. One finding is that some of the emergency actions taken were probably unnecessary.

Keywords: chance constrained programming; forecasting applications; petroleum/natural gas (search for similar items in EconPapers)
Date: 1986
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