The paper explains the sensitivity of different supply/demand forecasts in terms of assumptions about price, economic growth and government policies. It discusses the consequences of particular assumptions in each of these variables for dislocations in the other variables, when the joint assumptions lead to these key variables, for example a shift in supply of or demand for petroleum.


Cette communication expose la sensibilité de différentes prévisions sur l'offre et la demande de pétrole à partir d'hypothèses sur le prix, la croissance économique et la politique gouvernementale. Elle étudie les conséquences d'hypothèses particulières pour chacune de ces variables lorsque celles-ci provoquent des déséquilibres dans d'autres variables, lorsque l'ensemble des hypothèses aboutit aux déséquilibres de l'offre et de la demande. Elle étudie l'influence d'événements extèrieurs sur ces variables principales, par exemple une modification de l'offre ou de la demande de pétrole.


The purpose of this paper is to discuss energy balance analysis and its use in forecasting, policymaking and decision analysis, particularly in ‘notional gap’ cases where supply of and demand for fuels is not in balance. Discussion of the effects of the key variables of energy price, economic growth and government policy on energy supply and demand leads to the notion of comparability of energy balance analyses based on values of these variables. A discussion of recent developments in energy balance projections and the ‘notional gap’ consequences of these developments, together with a policy suggestion for overcoming the gap, concludes the paper.

Energy balance analyses have been used for many years to forecast supply-demand balances for oil, gas and other forms of energy. In early analyses of this kind, there were only loose functional relationships among variables, and no equilibrating mechanism to insure consistency among supply and demand in various markets. Rather, the main emphasis was on a richness of detail for industry planning, with separate projections of demand and supply, disaggregated by region and fuel type, and with careful attention to institutional detail. As analytic sophistication increased, many of these analyses become refined and mechanized to capture relationships between variables, to reflect particular approaches to production, processing, transportation and distribution (including cost minimization) and so on. But the basic approach continued to be an engineering/economic approach for systems planning, in which particular ‘scenario’ assumptions about major variables led to energy balance conclusions. Frequently, the major scenario variables that affected

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