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Decisionmakers, policy analysts, and the academic community

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Journal Article by John A. "Skip" Laitner and Alan Sanstad. Abstract: A growing literature is focusing on the phenomenon of "learning-by-doing" in the context of energy supply technologies: As new technologies enter the marketplace, and as experience is gained in both their production and use, costs tend to decline with each successive doubling of investment or production. This work builds both on the long-established literature on learning "curves" in production in a variety of industries and on the classic work by Arrow in a general equilibrium context. A number of studies have indicated that the effects of including learning-by-doing in energy forecasting and simulation modeling may be substantial relative to modeling with only "autonomous" or "exogenous" technical change. However, much less attention has been paid to the implications of learning-by-doing for demand-side technologies. Given that these are durable goods and thus subject to learning effects on production, there will be underlying cost declines that affect the end-use cost of energy services, and omitting such effects may introduce a bias into technology forecasts that incorporate learning-by-doing. This paper explores the implications of this observation through the application of a heuristic model that captures the anticipated electricity service demand within the United States over the next 30 years. We examine how including demand as well as supply-side learning could impact investment decisions within the U.S. electric utility industry.

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