Technological Interdependencies Predict Innovation Dynamics

25 Pages Posted: 27 Mar 2020

See all articles by Anton Pichler

Anton Pichler

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School; University of Oxford - Mathematical Institute; Complexity Science Hub Vienna

Francois Lafond

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School; University of Oxford - Mathematical Institute

J. Doyne Farmer

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School; Santa Fe Institute

Date Written: March 2, 2020

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 spatial econometrics

JEL Classification: O30 O31 O32 O33 C31

Suggested Citation

Pichler, Anton and Lafond, Francois and Farmer, J. Doyne, Technological Interdependencies Predict Innovation Dynamics (March 2, 2020). Available at SSRN: https://ssrn.com/abstract=3547474 or http://dx.doi.org/10.2139/ssrn.3547474

Anton Pichler (Contact Author)

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School ( email )

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HOME PAGE: http://www.anton-pichler.com

University of Oxford - Mathematical Institute ( email )

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Complexity Science Hub Vienna ( email )

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Francois Lafond

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School ( email )

Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

University of Oxford - Mathematical Institute ( email )

Andrew Wiles Building
Radcliffe Observatory Quarter (550)
Oxford, OX2 6GG
United Kingdom

J. Doyne Farmer

University of Oxford - Institute for New Economic Thinking at the Oxford Martin School ( email )

Eagle House
Walton Well Road
Oxford, OX2 6ED
United Kingdom

HOME PAGE: http://www.inet.ox.ac.uk/people/view/4

Santa Fe Institute ( email )

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