Edited by Joanne Evans and Lester C. Hunt
For most genres of economic models, standard practice denominates all inputs, outputs, and other measures in a monetary currency. However, analysis of energy and environmental policy requires technological explicitness; the same end-use service can be provided by many different technologies using different fuels and having completely different emissions profiles, and yet cost roughly the same. To meet this requirement, a class of technology-oriented models, collectively known as ‘bottom-up’ models, developed in the 1970s. Since their inception, ongoing issues continue to drive development (Hoffman and Wood 1976; Hoffman and Jorgenson 1977; Manne et al. 1979): the inadequacy of standard money-denominated macroeconomic models, which do not usually differentiate technology stocks within overall invested capital, and eventual recognition of the need for models that explicitly represent the energyusing technology stock; technology data collection and availability and, in the early days at least, computing power; the challenge of finding methods to ‘run’ or ‘drive’ technology selection (capital investment) in a way that is useful and defensible to policy makers and consistent with economic theory; and the need to include dynamics to represent macroeconomic adjustments, specifically demand for end-use services that use energy. ‘Bottom-up’ modeling began with simple, single-sector accounting tools and has gradually evolved into an increasingly complex and dynamic set of optimization and simulation frameworks with varying scopes (from local to worldwide). More recent models, so called ‘hybrid’ frameworks, include greater levels of economic detail and the dynamic characteristics of ‘top-down’ models, thus, prompting speculation as to...
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