How predictable is technological progress?

J. Farmer and François Lafond

Papers from arXiv.org

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.

Date: 2015-02, Revised 2015-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Published in Research Policy, Volume 45, Issue 3, Pages 647-665 (April 2016)

Downloads: (external link)
http://arxiv.org/pdf/1502.05274 Latest version (application/pdf)

Related works:
Journal Article: How predictable is technological progress? (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1502.05274

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().