2020/03/01 by Pichler, Anton, Lafond, François, Farmer, J. Doyne · 1 citation
#FOS: Economics and business #FOS: Physical sciences #General Economics (econ.GN) #Physics and Society (physics.soc-ph)
paper · doi:10.48550/arxiv.2003.00580
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 find that the predictability of innovation rates can be boosted substantially when network effects are taken into account. In the case where a technology's neighborhood future innovation rates are known, the average predictability gain is 28% compared to simpler time series model which 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.