Skip to main content

Improving Energy Demand Analysis (1984) / Chapter Skim
Currently Skimming:

1 Formal Modeling and Problem-Oriented Research
Pages 1-26

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 1...
... For example, projections from detailed formal models of the energy system have often been as far wrong as the intuitive judgments of experts or forecasts from simpler models (e.g., Ascher, 1978; McNees, 1979; Zarnowitz, 1979)
From page 2...
... Simple economic models, even those that track past experience well in the aggregate, do not completely describe the bases of consumers' responses. Such models treat consumers in general -- and energy users in particular -- as rational economic actors operating in an environment roughly describable as a market.
From page 3...
... by such institutional factors as regulatory constraints on energy prices; the split incentives that operate when the owner and the user of energy-using equipment and buildings are not the same (e.g., rental housing) ; and the power of manufacturers, standard-setting groups, lenders, and professional organizations to limit the range of investment alternatives available to energy users.
From page 4...
... To the extent that factors such as those noted above determine behavior, the principles that govern the behavior of energy users do not lead to economically rational action as this concept is realized in existing models of energy demand. Thus, the most readily Whether all the relevant nonmonetary variables are measurable in principle and whether the behavior that flows from them can all be construed as rational under some noncircular definition of utility are two issues we do not address.
From page 5...
... Behavioral research on energy users and their environment, including small-scale controlled experiments, can probably improve understanding of energy use in ways that will be useful for policy-related demand analyses, including formal energy modeling, and that may have policy applications. For example, laboratory experiments with different energy-efficiency labels for appliances can help determine the features of energy information that make the most difference in appliance purchase decisions.
From page 6...
... In these chapters, we pay particular attention to qualitative factors that have not been given careful consideration in formal models but that behavioral research has shown may have major effects on demand. For example, we explore the possibility that consumers respond to changes in price and not only to price levels; we consider the impact of qualitative differences among types of incentives, such as tax credits, rebates, and loan subsidies; and we examine the role of word-of-mouth communication in the adoption of energy-efficient technologies.
From page 7...
... FORMAL MODELS OF ENERGY DEMAND Formal policy models are analytic tools that are built to provide quantitative projections of energy demand and to provide answers to questions about how demand might respond to alternative political and economic events or to policy choices. Formal models are often used to answer such questions as: "What will be the price of natural gas after full decontrol in the United States?
From page 8...
... For all these reasons, formal models are likely to remain the dominant tools for policy analysis in the area of energy demand. Types of Models Three frequently used approaches to building formal energy demand models are econometrics, system dynamics, and engineering process modeling.
From page 9...
... Compared with econometric models, in which causal relationships can also be postulated by the modeler, system dynamics modelers are less likely to check their postulated functional forms and parameters against data. The reliance of econometricians on time-series data acts as a
From page 10...
... Once the variables are chosen, coefficients for them are chosen to make the model fit the data. In selecting the variables, however, econometric models are constrained to choose among those variables for which data exist; systems dynamics models can postulate new variables.
From page 11...
... To make projections, engineering models rely on assumptions from economic and demographic projections about such factors as household formation, building stock replacement, and the rate of improvement in the energy efficiency Of available technologies. The chief strength of engineering process models in comparison with other types of models is that they can describe the technological trade-offs in more detail.
From page 12...
... He also argues that as policy analysis comes to rely on more and more technically complex models, the public tends to be closed out of policy debates. Still other criticisms emphasize the consequences of taking energy models seriously despite their flaws.
From page 13...
... The phenomena that result from such influences are, of course, encompassed by formal demand models, but they appear under other labels and so may be misconceived in important ways. The Place of Behavioral Variables in Formal Demand Models In energy demand models, behavioral variables are usually subsumed under other broad concepts that are vague with respect to their behavioral basis.
From page 14...
... The magnitude of the discount rate is often simply postulated in formal models, but some empirical methods have been suggested for estimating discount rates. The methods usually used involve analysis of data on consumer choices among alternatives that vary in energy efficiency and investment cost (e.g., for appliance purchases, Hausman, 1979)
From page 15...
... Because time-discounting is implicitly a psychological process of the consumer, it is easy to interpret empirically calculated implicit discount rates as representing an attribute of energy users.s But when implicit discount rates are calculated from data on purchases, the resulting number reflects a collection of variables -- not only the degree of preference for present value -- that may affect the level of investment. The calculated discount rate is affected, for example, by the extent to which information is imperfect, mistrusted, or ignored; by energy users' persistence in old habits; by the fact that consumers with limited capital do not always purchase what they would if they had more capital; and by various other factors that might change the rate of adoption of energy-efficient technology.
From page 16...
... Investments in energy efficiency in response to new conditions occur slowly over time. Formal models commonly estimate the rate of investment a priori, using an assumption that the rate follows price changes or other stimuli with a time lag described by a particular mathematical function.
From page 17...
... The coefficient should be based on an understanding of the ways various environmental factors, including behavioral ones, affect rates of response. 7 Formal demand models tend to address behavior through concepts that cover the outcomes of behavioral phenomena but offer little or no insight into the determinants of the phenomena.
From page 18...
... Such surveys would use a nationally representative sample of energy users. If repeated, surveys can gather time-series data essential for empirically estimating formal demand models, particularly econometric models.8 National surveys are not, however, useful for all types of policy analysis.
From page 19...
... . Specialized surveys are valuable because they can look closely at variables, including many of those not included explicitly in formal policy models, that may affect important consumer actions.
From page 20...
... Such natural experiments 9Existing data can be analyzed in various ways. One of these involves using the same econometric techniques that are sometimes used for building detailed formal models.
From page 21...
... Experimentation was the method of choice in those studies because there was no empirical basis for estimating the effect of prices based on time of use and because the experimental rates were so far from most energy users' past experience that self-reported intentions could not be relied upon. The same rationale suggests that experiments could provide the most valid answers to questions about the design of energy conservation programs, particularly for assessing the effects of interventions that are nonfinancial n character and for which, as a result, existing models are particularly inadequate.
From page 22...
... Incentive programs-such as the federal and state tax credits for conservation and solar energy -- have also been inadequately studied. And thousands of local energy programs, public and private (see Center for Renewable Resources, 1980)
From page 23...
... Problem-oriented studies can also be used to address issues that arise in constructing policy models. When data are not available for estimating discount rates, surveys to assess consumer choices among hypothetical technologies may, despite the limitations of such surveys, be the best available source of estimates.
From page 24...
... In addition, some methods of problemoriented research, particularly experimental ones, provide more convincing evidence than modeling data can offer. Experiments, and even well-conceived quasi-experiments, are relatively free of the problems of spurious correlation that haunt econometric models and of the unsubstantiated causal assumptions that leave system dynamics models open to serious question.
From page 25...
... energy system. It offers ways to validate assumptions, to estimate the parameters of models, to see if variables that have not yet been considered may be important, and to explore in detail the behavioral phenomena that underlie such broad concepts as price elasticity, time lags, and implicit discount rate.
From page 26...
... Rather, we expect that improved knowledge will bring about changes in existing models and that such changes will lead to improved analysis of energy demand. This report is a beginning effort to show how different analytic methods can be used in a complementary fashion to improve understanding of energy demand.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.