Article ID Journal Published Year Pages File Type
897472 Technological Forecasting and Social Change 2008 11 Pages PDF
Abstract

Progress ratios (PRs) derived from historical data in experience curves are used for forecasting development of many technologies as a means to model endogenous technical change in for instance climate–economy models. These forecasts are highly sensitive to uncertainties in the progress ratio. As a progress ratio is determined from fitting data, a coefficient of determination R2 is frequently used to show the quality of the fit and accuracy of PR. Although this is instructive, we recommend using the error σPR in PR, which can be directly determined from fitting the data. In this paper we illustrate this approach for three renewable energy technologies, i.e., wind energy, bio-ethanol, and photovoltaics.

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Social Sciences and Humanities Business, Management and Accounting Business and International Management
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