Working papers

Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution (with Jangho Yang, Torsten Heinrich and Julian Winkler, Pantelis Koutroumpis, and J. Doyne Farmer), INET WP 2014-19
Labor productivity levels and growth are highly heterogenous among firms. We show that the Lévy alpha-stable distribution, a heavy-tail distribution with infinite variance, is a good fit to these distributions. This provides a richer perspective on dispersion.

Does stimulating demand drive costs down? World War II as a natural experiment (with Diana Greenwald and J. Doyne Farmer)
During WWII, the demand for weapons was not driven by prices. Yet, to some extent faster growth of experience was associated with faster productivity improvements.

Automation and occupational mobility: a data-driven network model (with R. Maria del Rio-Chanona, Penny Mealy, Mariano Beguerisse, J. Doyne Farmer), arXiv 1906.04086.
We develop a labor market model based on the occupational mobility network, and use it to assess the effects of the next wave of automation.

Why is productivity slowing down? (with Ian Goldin, Pantelis Koutroumpis and Julian Winkler), submitted
We comprehensively review the various explanations for the current productivity slowdown

Disruptive technologies and regional innovation policy (with Pantelis Koutroumpis), Background paper for an OECD/EC Workshop on 22 November 2018 within the workshop series “Broadening innovation policy: New insights for regions and cities”, Paris.

Journal articles

Early identification of important patents: design and validation of citation network metrics, with Manuel Mariani and Matúš Medo, Technological Forecasting and Social Change 146, pp. 644-654, 2019Publisher. 
A citation network-based indicator, time rescaled PageRank, can be used to detect important patents a few years only after that they are granted.

Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves  (with Rupert Way, Valentyn Panchenko, Fabrizio Lillo, and J. Doyne Farmer), Journal of Economic Dynamics & Control 101, pp. 211-238, 2019, Open access at publisher
When there are increasing returns to investment, there may be multiple locally optimal diversified portfolios.

Long-run dynamics of the U.S. patent classification system (with Daniel Kim). Journal of Evolutionary Economics 29(2), pp. 631–664, 2019, Open access at PublisherData.
Patent classification systems change frequently and reflect the dynamics of technological change

How well do experience curves predict technological progress? A method for making distributional forecasts (with Aimee G. Bailey, Jan D. Bakker, Dylan Rebois, Rubina Zadourian, Patrick McSharry, and J. Doyne Farmer), Technological Forecasting and Social Change  128, pp 104-117, 2018. arXiv, Publisher, Data.
We test and apply a simple method to make distributional forecasts for technological progress conditional on the growth of experience.

How predictable is technological progress? (with J. Doyne Farmer), Research Policy 45(3), 647–665, 2016.   Open access at PublisherData.
We test and apply a simple method to make distributional forecasts for technological progress.

Self-organisation of knowledge economies, Journal of Economic Dynamics and Control 52, 150-165, 2015. Publisher.
The structure of agents-ideas networks depends on the innovation/diffusion trade-off.

Advanced work in progress

Predicting innovation dynamics in technological ecosystems (with Anton Pichler and J. Doyne Farmer)

Uncovering technological eras (with Yuki Asano, Simon Vary, Mariano Beguerisse Díaz and J. Doyne Farmer)

Origins and evolution of technological domains (with Vilhelm Verendel and J. Doyne Farmer)

Input-Output Linkages and Economic Growth (with Jangho Yang, Advait Rajagopal,  Luis Daniel Torres Gonzalez, and J. Doyne Farmer)

PhD Thesis

The evolution of knowledge systems, 2014, Maastricht University Press. PDF

Resting working papers

The size of patent categories: USPTO 1976-2006 (2014), UNU-MERIT WP #2014-060. Updated as “Long-run dynamics of the U.S. patent classification system”, with Daniel Kim.

Learning and the structure of citations networks (2012), UNU-MERIT WP #2012-071. Partly published as “Self-organization of knowledge economies”, and updated as “Knowledge diffusion and the structure of citations networks”, 2014.