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Technological interdependencies predict innovation dynamics

Author

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  • Pichler, Anton
  • Lafond, François
  • Farmer, J. Doyne

Abstract

We propose a simple model where the innovation rate of a technological domain depends on the innovation rate of the technological domains it relies on. Using data on US patents from 1836 to 2017, we make out-of-sample predictions and fond that the predictability of innovation rates can be boosted substantially when network effects are taken into account. In the case where a technology's neighbourhood further innovation rates are known, the average predictability gain is 28% compared to simpler time series model with do not incorporate network effects. Even when nothing is known about the future, we find positive average predictability gains of 20%. The results have important policy implications, suggesting that the effective support of a given technology must take into account the technological ecosystem surrounding the targeted technology.

Suggested Citation

  • Pichler, Anton & Lafond, François & Farmer, J. Doyne, 2020. "Technological interdependencies predict innovation dynamics," INET Oxford Working Papers 2020-04, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    • Handle: RePEc:amz:wpaper:2020-04
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    Cited by:

    1. Hötte, Kerstin & Jee, Su Jung, 2022. "Knowledge for a warmer world: A patent analysis of climate change adaptation technologies," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    2. Hidalgo, César & Stojkoski, Viktor, 2025. "The Theory of Economic Complexity," TSE Working Papers 1648, Toulouse School of Economics (TSE), revised Aug 2025.
    3. Lafond, François, 2025. "Forecasting technological progress," INET Oxford Working Papers 2025-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, revised Dec 2025.
    4. Hötte, Kerstin & Pichler, Anton & Lafond, François, 2021. "The rise of science in low-carbon energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    5. Ward, S.H. & Lopes Cardozo, N.J., 2025. "Value-led fusion technology: A framework for guiding fusion commercialisation strategy," Energy Policy, Elsevier, vol. 203(C).
    6. Michael P. Weinold & Sergey Kolesnikov & Laura Díaz Anadón, 2025. "Rapid technological progress in white light-emitting diodes and its source in innovation and technology spillovers," Nature Energy, Nature, vol. 10(5), pages 616-629, May.
    7. Barbieri, Nicolò & Marzucchi, Alberto & Rizzo, Ugo, 2023. "Green technologies, interdependencies, and policy," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    8. Nicolo Barbieri & Alberto Marzucchi & Ugo Rizzo, 2021. "Green technologies, complementarities, and policy," SPRU Working Paper Series 2021-08, SPRU - Science Policy Research Unit, University of Sussex Business School.

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