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How well do experience curves predict technological progress? A method for making distributional forecasts

Abstract:

Experience curves are widely used to predict the cost benefits of increasing the deployment of a technology. But how good are such forecasts? Can one predict their accuracy a priori? In this paper we answer these questions by developing a method to make distributional forecasts for experience curves. We test our method using a dataset with proxies for cost and experience for 51 products and technologies and show that it works reasonably well. The framework that we develop helps clarify why th...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1016/j.techfore.2017.11.001

Authors


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Institution:
University of Oxford
Division:
SSD
Department:
SOGE; Smith School
Bailey, AG More by this author
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Institution:
University of Oxford
Division:
SSD
Department:
Economics
Zadourian, R More by this author
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Grant:
FP7-ICT-2013-611272
H2020-730427
Publisher:
Elsevier Publisher's website
Journal:
Technological Forecasting and Social Change Journal website
Volume:
128
Pages:
104-117
Publication date:
2017-12-26
Acceptance date:
2017-11-01
DOI:
ISSN:
0040-1625
Pubs id:
pubs:812971
URN:
uri:998827e5-c5c9-460c-97de-c663a641b6eb
UUID:
uuid:998827e5-c5c9-460c-97de-c663a641b6eb
Local pid:
pubs:812971

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