  While great emphasis has been placed on the role of social interactions as
driver of innovation growth, very few empirical studies have explicitly
investigated the impact of social network structures on the innovation
performance of cities. Past research has mostly explored scaling laws of
socio-economic outputs of cities as determined by, for example, the single
predictor of population. Here, by drawing on a publicly available dataset of
the startup ecosystem, we build the first Workforce Mobility Network among US
metropolitan areas. We found that node centrality computed on this network
accounts for most of the variability observed in cities' innovation performance
and significantly outperforms other predictors such as population size or
density, suggesting that policies and initiatives aiming at sustaining
innovation processes might benefit from fostering professional networks
alongside other economic or systemic incentives. As opposed to previous
approaches powered by census data, our model can be updated in real-time upon
open databases, opening up new opportunities both for researchers in a variety
of disciplines to study urban economies in new ways, and for practitioners to
design tools for monitoring such economies in real-time.
