How Predictable is Technological Progress?

27 Pages Posted: 20 Feb 2015 Last revised: 26 Nov 2015

See all articles by J. Doyne Farmer

J. Doyne Farmer

University of Oxford

Francois Lafond

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School; University of Oxford - Mathematical Institute

Date Written: November 25, 2015

Abstract

Recently it has become clear that many technologies follow a generalized version of Moore's law, i.e. costs tend to drop exponentially, at different rates that depend on the technology. Here we formulate Moore's law as a correlated geometric random walk with drift, and apply it to historical data on 53 technologies. We derive a closed form expression approximating the distribution of forecast errors as a function of time. Based on hind-casting experiments we show that this works well, making it possible to collapse the forecast errors for many different technologies at different time horizons onto the same universal distribution. This is valuable because it allows us to make forecasts for any given technology with a clear understanding of the quality of the forecasts. As a practical demonstration we make distributional forecasts at different time horizons for solar photovoltaic modules, and show how our method can be used to estimate the probability that a given technology will outperform another technology at a given point in the future.

Keywords: forecasting, technological progress, Moore's law, solar energy

JEL Classification: C53, O30, Q47

Suggested Citation

Farmer, J. Doyne and Lafond, Francois, How Predictable is Technological Progress? (November 25, 2015). Available at SSRN: https://ssrn.com/abstract=2566810 or http://dx.doi.org/10.2139/ssrn.2566810

J. Doyne Farmer

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

Francois Lafond (Contact Author)

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School ( email )

Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

University of Oxford - Mathematical Institute ( email )

Andrew Wiles Building
Radcliffe Observatory Quarter (550)
Oxford, OX2 6GG
United Kingdom

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