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Potential errors when fitting experience curves by means of spreadsheet software

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  • van Sark, W.G.J.H.M.
  • Alsema, E.A.

Abstract

Progress ratios (PRs) are widely used in forecasting development of many technologies; they are derived from historical data represented in experience curves. Fitting the double logarithmic graphs is easily done with spreadsheet software like Microsoft Excel, by adding a trend line to the graph. However, it is unknown to many that these data are transformed to linear data before a fit is performed. This leads to erroneous results or a transformation bias in the PR, as we demonstrate using the experience curve for photovoltaic technology: logarithmic transformation leads to overestimates of progress ratios and underestimates of goodness of fit. Therefore, other graphing and analysis software is recommended.

Suggested Citation

  • van Sark, W.G.J.H.M. & Alsema, E.A., 2010. "Potential errors when fitting experience curves by means of spreadsheet software," Energy Policy, Elsevier, vol. 38(11), pages 7508-7511, November.
    • Handle: RePEc:eee:enepol:v:38:y:2010:i:11:p:7508-7511
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    1. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
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    3. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
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    Cited by:

    1. Kim, Dong Wook & Chang, Hyun Joon, 2012. "Experience curve analysis on South Korean nuclear technology and comparative analysis with South Korean renewable technologies," Energy Policy, Elsevier, vol. 40(C), pages 361-373.
    2. Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.

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