The DOI matches its Crossref record.
Experience Curves for Energy Technology Policy
Abstract
The fact that market experience improves performance and reduces prices is well known and widely exploited in technology-intensive industries, but sparsely used in analysis for energy technology policy. Knowledge of the "experience effect" can help in the design of efficient programmes for deploying of environment-friendly technologies. The effect must be taken into account when estimating the future costs of achieving targets, including targets for carbon dioxide reduction. This book discusses issues raised by the "experience effect", such as price-cost cycles, competition for learning opportunities in the market, risk of "technology lockout" and the effects of research, development and deployment policies on technology learning. Case studies illustrate how experience curves can be used to set policy targets and to design policy measures that will encourage both investment in and use of environment-friendly energy technologies. Low-cost paths to stabilising CO2 emissions are explored.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Technological change in economic models of environmental policy: a survey
Löschel, A. (2002) · Ecological Economics · doi:10.1016/s0921-8009(02)00209-4 · Cited by 527
CLUMSY SOLUTIONS FOR A COMPLEX WORLD: THE CASE OF CLIMATE CHANGE
VERWEIJ, M., DOUGLAS, M., ELLIS, R., ENGEL, C., HENDRIKS, F., LOHMANN, S., NEY, S., RAYNER, S., & THOMPSON, M. (2006) · Public Administration · doi:10.1111/j.1540-8159.2005.09566.x-i1 · Cited by 398
Ethanol learning curve—the Brazilian experience
Goldemberg, J., Coelho, S. T., Nastari, P. M., & Lucon, O. (2004) · Biomass and Bioenergy · doi:10.1016/s0961-9534(03)00125-9 · Cited by 379
Neij, L. (2008) · Energy Policy · doi:10.1016/j.enpol.2008.02.029 · Cited by 366
Cost-effectiveness of renewable electricity policies
Palmer, K., & Burtraw, D. (2005) · Energy Economics · doi:10.1016/j.eneco.2005.09.007 · Cited by 344
Metadata
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Experience Curves for Energy Technology Policy. https://app.cochat.ai/papers/10.1787/9789264182165-en
- The paper
- International Energy Agency. (2000). Experience Curves for Energy Technology Policy. OECD eBooks. https://doi.org/10.1787/9789264182165-en
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.