Matching and learning in cities: urban density and the rate of invention
Gerald Carlino (),
Satyajit Chatterjee () and
Robert Hunt ()
No 04-16, Working Papers from Federal Reserve Bank of Philadelphia
This paper examines the role local labor markets play in the production of innovations. The authors appeal to a labor market matching model (á la Berliant, Reed, and Wang 2004) to argue that in dense urban areas, workers are more selective in their matches and are therefore more productive. They find that, all else equal, patent intensity (patents per capita) is 20 percent higher in a metropolitan area with an employment density (jobs per square mile) twice that of another metropolitan area. Since local employment density doubles nearly four times across their sample, the implied gains in inventive output are substantial. In addition, the authors find evidence of an optimal employment density, i.e., one that maximizes patent intensity, of about 2,150 jobs per square mile–roughly the level of Baltimore or Philadelphia. They also find that, all else equal, a city with a more competitive market structure, or one that is not too large (a population less than 1 million) will 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. ; Superseded by Working Paper 06-14
Keywords: Patents; Urban economics; Employment (Economic theory) (search for similar items in EconPapers)
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Working Paper: Matching and Learning in Cities: Urban Density and the Rate of Invention (2005)
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