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 R 2 is frequently used to show the quality of the fit and accuracy of PR. Although this is instructive, we recommend using the error σ PR 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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