Technological interdependencies predict innovation dynamics

Anton Pichler, François Lafond and J. Farmer

INET Oxford Working Papers from Institute for New Economic Thinking at the Oxford Martin School, University of Oxford

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.

Keywords: innovation; technology; network; forecasting; patents; spacial econometrics (search for similar items in EconPapers)
Pages: 26 pages
Date: 2020-03
New Economics Papers: this item is included in nep-ino and nep-isf
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Citations: View citations in EconPapers (4)

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Working Paper: Technological interdependencies predict innovation dynamics (2020)
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