Urban Density and the Rate of Invention

Abstract

Economists, beginning with Alfred Marshall, have studied the significance of cities in the production and exploitation of information externalities that, today, we call knowledge spillovers. This paper presents robust evidence of those effects. We show that patent intensitythe per capita invention rate-is positively related to the density of employment in the highly urbanized portion of MAs. All else equal, a city with twice the employment density (jobs per square mile) of another city will exhibit a patent intensity (patents per capita) that is 20 percent higher. Patent intensity is maximized at an employment density of about 2,200 jobs per square mile. A city with a more competitive market structure or one that is not too large (a population less than 1 million) will also have a higher patent intensity. These findings confirm the widely held view that the nation's densest locations play an important role in creating the flow of ideas that generate innovation and growth.

The Complementary Effects of Proximity Dimensions on Knowledge Spillovers

“…Comparing our results for the lagged dependent variable coefficient with previous studies, it turns out that the coefficient of the geographical proximity matrix goes from 0.09 for EU regions in Moreno et al (2005), to 0.18 in Usai (2011) which refers to both US and EU, to a much higher value of 0.4 for the US in Carlino et al (2007). For the technological proximity previous comparable studies are Moreno et al (2005) with a lag coefficient equal to 0.05 and Greunz (2003) with an estimate of 0.25 who also reports that technological association is stronger than the geographical one.…”

Entrepreneurs and cities: Complexity, thickness and balance

“…Specifically, the vast body of evidence establishing the innovativeness of cities speaks to agglomeration's temporal advantages. This literature shows more patenting in cities (Carlino et al (2007)), the spatial localization of patenting (Jaffe et al (1993)), and the spatial localization of new product introductions (Audretsch and Feldman (1996)). 8…”

Obsolescence in Urban Energy Infrastructures: The Influence of Scaling Laws on Consumption Forecasting

“…Having a central role in modern human economies and considering the permanent and positive relationship of energy consumption with any form of economic growth (Smil, 2008), electricity consumption scaling with population can strongly constrain the particular dynamics involved in productivity and economic growth in cities. The relationship between urban size and productivity is indeed a central fact of urban economics (Glaeser and Resseger, 2010) but from a global environmental accounting point of view energy consumption can effectively restrain economic, social and environmental sustainability, and might counterbalance advantages coming from technological innovations and agglomeration economies (Carlino et al, 2007;Rauch, 1993). In this particular case of energy related variables in cities, superlinear scaling exponents can be very significant.…”