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

F. Lafond, A. Bailey, J. Bakker, D. Rebois, R. Zadourian, P. McSharry, D. Farmer

Technological Forecasting and Social Change 128, 104 (2018)

#technology#innovation#economics

LQ placeholderWe presented a method to test the accuracy and validity of experience curve forecasts.

We presented a method to test the accuracy and validity of experience curve forecasts.

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 the experience curve method often gives similar results to simply assuming that costs decrease exponentially. To illustrate our method we make a distributional forecast for prices of solar photovoltaic modules.

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

F. Lafond, A. Bailey, J. Bakker, D. Rebois, R. Zadourian, P. McSharry, D. Farmer

Technological Forecasting and Social Change

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Grand canonical validation of the bipartite international trade network

M. Straka, G. Caldarelli, F. Saracco

Physical Review E

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Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics

G. Ranco, I. Bordino, G. Bormetti, G. Caldarelli, F. Lillo, M. Treccani

PLoS ONE

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The effects of Twitter sentiment on stock price returns

G. Ranco, D. Aleksovski, G. Caldarelli, M. Grčar, I. Mozetič

PLoS ONE

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Self-organization of knowledge economies

F. Lafond

Journal of Economic Dynamics and Control

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How the taxonomy of products drives the economic development of countries

A. Zaccaria, M. Cristelli, A. Tacchella, L. Pietronero

PLOS ONE

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Credit default swaps networks and systemic risk

M. Puliga, G. Caldarelli, S. Battiston

Scientific Reports

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The rise of China in the international trade network: a community core detection approach

Z. Zhu, F. Cerina, A. Chessa, G. Caldarelli, M. Riccaboni

PLoS ONE

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A new metric for countries’ fitness and products’ complexity

A. Tacchella, M. Cristelli, G. Caldarelli, A. Gabrielli, L. Pietronero

Scientific Reports

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