The Geography of Complex Knowledge. (1st January 2017)

• Record Type: Journal Article
• Authors: Balland, Pierre-Alexandre; Rigby, David
• Is Part Of: Economic geography. Volume 93:Number 1(2017:Jan.)
• Page Start: 1
• Page End: 23
• Publication Date: 2017-01-01
• Subjects: knowledge complexity and flow -- cities -- patents -- network analysis -- economic geography -- United States; O33 -- R11 -- L65 -- D83; Economic geography -- Periodicals; 330.9
• DOI: 10.1080/00130095.2016.1205947
• Languages: English
• ISSNs: 0013-0095

Abstract

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.