Energy, the environment and US economic growth

Dale W. Jorgenson, Richard J. Goettle, Mun S. Ho, Peter J. Wilcoxen

Research output: Chapter in Book/Entry/PoemConference contribution

24 Scopus citations


The point of departure for the study of the impact of energy and environmental policies is the neoclassical theory of economic growth formulated by Cass (1965) and Koopmans (1967). The longrun properties of economic growth models are independent of energy and environmental policies. However, these policies affect capital accumulation and rates of productivity growth that determine the intermediate-run trends that are important for policy evaluation. Heterogeneity of different energy producers and consumers is critical for the evaluation of energy and environmental policies. To capture this heterogeneity it is necessary to distinguish among commodities, industries and households. Econometric methods are essential for summarizing information on different industries and consumer groups in a form suitable for general equilibrium modeling. In this chapter, we consider the application of econometric general equilibrium modeling to the US e the economy that has been studied most intensively. The framework for our analysis is provided by the Intertemporal General Equilibrium Model (IGEM) introduced by Jorgenson and Wilcoxen (1998). The new version of the IGEM presented in this paper is employed for the evaluation of proposed legislation on climate policy by the US Environmental Protection Agency (2012b).

Original languageEnglish (US)
Title of host publicationHandbook of Computable General Equilibrium Modeling SET, Vols. 1A and 1B, 2013
EditorsPeter B. Dixon, Dale W. Jorgenson
Number of pages76
ISBN (Print)9780444595683
StatePublished - 2013

Publication series

NameHandbook of Computable General Equilibrium Modeling
ISSN (Print)2211-6885


  • Econometric modeling
  • Energy
  • Environment
  • General equilibrium
  • Heterogeneity
  • Policy evaluation

ASJC Scopus subject areas

  • General Economics, Econometrics and Finance
  • Computer Science Applications
  • Modeling and Simulation


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