Technological evolution and economic growth

Research publications

Lennart Baumgärtner , Rupert Way , Matthew Ives , and J. Doyne Farmer. ‘The need for better statistical testing in data-driven energy technology modeling,’ Joule (2024)

Peter Barbrook-Johnson, Simon Sharpe, Roberto Pasqualino, Fernanda Senra de Moura, Femke Nijsee, Pim Vercoulen, Alex Clark, Cristina Penasco, Laura Diaz Anadon, Jean-Francois Mercure, Cameron Hepburn, J. Doyne Farmer, and Timothy M. Lenton. ‘New economic models of energy innovation and transition,’ Report (2023).

J. McNerney, C. Savoie, F. Caravelli, V.M. Carvalho, J.D. Farmer. ‘How production networks amplify economic growth’, Proceedings of the National Academy of Sciences (January 2022).

Rupert Way, Penny Mealy and J. Doyne Farmer. ‘Estimating the costs of energy transition scenarios using probabilistic forecasting methods’, INET Oxford Working Paper No. 2021-01, (2020).
A. Pichler, F. Lafond and J. D. Farmer, ‘Technological interdependencies predict innovation dynamics’, arXiv:2003.00580 (February 2020).
J. D. Farmer, F. Markopoulou, E. Beinhocker and S. Rasmussen, ‘Collaborators in creation’, Aeon (February 11 2020).
F. Lafond, D. S. Greenwald and J. D. Farmer, ‘Can Stimulating Demand Drive Costs Down? World War II as a Natural Experiment’, (January 15, 2020).

J. Yang, T. Heinrich, J. Winkler, F. Lafond, P. Koutroumpis and J. D. Farmer, 'Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution'. INET Oxford Working Paper No. 2019-14 (2019).
Rupert Way, Francois Lafond, Fabrizio Lillo, Valentyn Panchenko and J. Doyne Farmer, “Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves”, Journal of Economic Dynamics and Control, 101(April), pp.211-238, (2019).

F. Lafond, A. G. Bailey, J. D. Bakker, D. Rebois, R. Zadourian, P. McSharry, & J. D. Farmer, “How well do experience curves predict technological progress? A method for making distributional forecasts”, Technological Forecasting and Social Change, 128 (March), pp.104-117 (2018).
James McNerney, Charles Savoie, Francesco Caravelli and J. Doyne Farmer, “How production networks amplify economic growth”, arXiv.org (2018).

J. Doyne Farmer and Francois Lafond, “How Predictable Is Technological Progress?” Research Policy 45, 647 – 655 (2016).

R. V. Sole, S. Valverde, M.R. Casals, S.A. Kauffman, J.D. Farmer and N. Eldredge, “The Evolutionary Ecology Of Technological Innovations”, Complexity 18 (4), 15-27 (2013).
B. Nagy, J. D. Farmer, Q. M. Bui and J. E. Trancik, "Statistical Basis for Predicting Technological Progress", PLoS ONE 8(2): e52669. (2013).

Aimee Gotway Bailey, Quan Minh Bui, J. Doyne Farmer, Robert M. Margolis and Ramamoorthy Ramesh, "Forecasting Technological Innovation", in ARCS Workshops (ARCS), 2012, pp. 1-6. IEEE, 2012. (Book chapter)

James McNerney, J. Doyne Farmer, Sid Redner and Jessika Trancik, “Role of Design Complexity in Technology Improvement", PNAS 108(22) (2011): 9008-9013.
James McNerney, J. Doyne Farmer and Jessika Trancik, “Historical Costs of Coal-Fired Electricity and Implications for the Future," Energy Policy 39(6) (2011): 3042-3054.
Béla Nagy, J. Doyne Farmer, Jessika E. Trancik and John Paul Gonzales, “Superexponential Long-Term Trends in Information Technology", Journal of Technological Forecasting and Social Change 73 (2011): 1061-1083.

J. Doyne Farmer and Jessika Trancik, “Dynamics of Technological Development in the Energy Sector”, In London Accord Final Publication. Eds. J-P. Onstwedder and M. Mainelli. (2007). (Book chapter)

J. D. Farmer and A. d’A. Belin,“Artificial Life: The Coming Evolution”, in Artificial Life II, eds. C. Langton, C. Taylor, J. D. Farmer and S. Rasmussen, 815-840. Santa Fe Institute Studies in the Sciences of Complexity. Redwood City, CA: Addison-Wesley, 1991. (Book chapter)