The Geography of Complex Knowledge

By Pierre-Alexandre Balland, David L. Rigby. 2017

486 citations recorded by the source corpus.

abstract There is consensus among scholars and policy makers that knowledge is one of the key drivers of long-run economic growth. It is also clear from the literature that not all knowledge has the same value. However, too often in economic geography and cognate fields we have been obsessed with counting knowledge inputs and outputs rather than assessing the quality of knowledge produced. In this article we measure the complexity of knowledge, we map the distribution and the evolution of knowledge complexity in US cities, and we explore how the spatial diffusion of knowledge is linked to complexity. Our knowledge complexity index rests on the bimodal network models of Hidalgo and Hausmann. Analysis is based on more than two million patent records from the US Patent and Trademark Office that identify the technological structure of US metropolitan areas in terms of the patent classes in which they are most active between 1975 and 2010. We find that knowledge complexity is unevenly distributed across the United States and that cities with the most complex technological structures are not necessarily those with the highest rates of patenting. Citation data indicate that more complex patents are less likely to be cited than less complex patents when citing and cited patents are located in different metropolitan areas.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/3cc0d44909db4e9eceac2736a0bf6564a62e6efa

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Citations in the corpus

Smart specialization policy in the European Union: relatedness, knowledge complexity and regional diversification (2019, methodology): “The EU complexity ranking is consistent with that in the United States described by Balland and Rigby (2017).”
Climbing the Ladder of Technological Development (2017, unknown): “We follow Hidalgo and Hausmann (2009) and Balland and Rigby (2017) to measure the complexity of technologies.”
Global networks, local specialisation and regional patterns of innovation (2020, background): “While regional internal specialisation and the establishment of external linkages are theoretically considered as complementary elements for local innovativeness within the academic debate, the empirical evidence on their joint role and their interplay remains scant, as most academic contributions t”
Specialisation, diversification and the ladder of green technology development (2020, unknown): “, 2013), industries or technologies (Balland and Rigby, 2017).”
Complementary interregional linkages and Smart Specialisation: an empirical study on European regions (2020, background): “Therefore, knowledge diffusion is often geographically bounded (Jaffe et al. 1993; Balland and Rigby, 2017).”