Predicting innovation dynamics in the technological ecosystem
Technological progress is a path-dependent process of recombining existing knowledge, motivating that the evolution of interdependent technologies should be coupled. We propose a simple model of innovation where the innovation rates for a technological domain depends on its location in the technological ecosystem. We test the model on the whole record of US patents from 1836 to 2017. We find strong dependence between patenting rates in technological domains and their respective knowledge base. As predicted by the model, we find that patenting growth rates in technological domains exhibit pronounced synchronization, if they form the supporting knowledge bases for each other. We use this insight to make out-of-sample predictions and find that the innovation rate of a technology is better predicted when accounting for the innovation rates of its knowledge base. The results have important policy implications, suggesting that the effective support of a given technology must take the technological ecosystem surrounding the focal technology into account. We discuss the example of green energy technologies, showing that their position in the technological ecosystem differs, thus explaining why some are making faster progress than others and how this can be accelerated by supporting their underlying knowledge base.
Date: 2 May 2019, 15:00 (Thursday, 1st week, Trinity 2019)
Venue: Manor Road Building, Manor Road OX1 3UQ
Venue Details: Seminar room B
Speaker: Anton Pichler (Complexity Economics, INET Oxford)
Organising department: Institute for New Economic Thinking
Organiser: Susan Mousley (INET Oxford Admin Team)
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Part of: INET Oxford Researcher Seminars
Booking required?: Required
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Audience: Members of the University only
Editor: Susan Mousley