The Energy Journal

Manne and Richels (Manne and Richels, 1990) have developed a useful modelling framework for evaluating the potential economic impacts of alternative strategies for coping with greenhouse wanning. Their estimate is that the discounted present value of economic consumption losses arising from a 20% reduction in CO2 emissions through the next century is in the range of $0.8 to $3.6 trillion. This critique shows that the options for reducing C02 emissions through energy demand reduction and energy supply shifts are much broader than those considered by Manne and Richels in the initial run of their model. The possibilities are so diverse with both present and future technologies, that the minimum C02 emissions constraint penalty estimated by Manne and Richels may well prove to be too high - and the possibility of a negative penalty cannot be ruled out. Manne and Richels are correct in arguing that a vigorous R&D program is needed to keep economic consumption losses associated with constraints on C02 emissions at low levels, and that waiting for clarification of the scientific issues relating to the greenhouse warming before launching such R&D efforts would be unwise, but the priorities for R&D implicit in the initial run of their model are much too narrowly focused. As this analysis indicates, a much more broadly based energy R&D program is called for.

Conditional demand analysis (CDA) is a statistical method for allocating the total household electricity load, during a period, into its constituent components, each associated with a particular electricity-using appliance or end-use. This is an indirect approach to the estimation of end-use demand and, quite naturally, it often generates imprecise estimates. One of the possible methods for improving these estimates involves the incorporation of data obtained by directly metering specific appliances. It is argued that an extremely natural approach to the use of this extra information follows directly from a reformulation of the standard CDA model into a random coefficient framework. Some new results on the possible efficiency gains from such an approach are developed. Illustrations based on an empirical study of New South Wales (NSW) households are also provided.

The success of real-time pricing efforts will depend in large part upon the extent to which electricity consumers are able to alter their consumption patterns in response to the prices quoted by the utility. This article provides some original estimates of hourly price elasticity responses to real-time prices by large industrial energy consumers.

An econometric translog cost function methodology was adopted for this purpose. Using data for large industrial users in 1986, the estimated own-price elasticity response averaged -0.09, implying a small but significant reaction to the changing hourly prices. Design deficiencies in the particular rate program studied may have limited customer reaction.