 How predictable is technological progress?Research Policy, 2016, vol. 45, issue 3, 647-665 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 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:respol:v:45:y:2016:i:3:p:647-665 DOI: 10.1016/j.respol.2015.11.001 Access Statistics for this article Research Policy is currently edited by M. Bell, B. Martin, W.E. Steinmueller, A. Arora, M. Callon, M. Kenney, S. Kuhlmann, Keun Lee and F. Murray More articles in Research Policy from Elsevier |
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