Agglomeration and Congestion in the Economics of Ideas and Technological Change

American Journal of Economics and Sociology, The,  Jan, 2001  by Norman Sedgley,  Bruce Elmslie

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VI

Conclusion

THERE IS NOT ENOUGH EFFORT directed at understanding the links between urbanization, cities, innovation and growth. One major goal of this paper, therefore, is to formulate a model that directly tests the potential importance of the ideas of urban agglomeration and congestion as they relate to innovation and the economics of ideas. Looking for evidence of agglomeration by accounting for the spatial density of economic activity we find strong evidence that rates of innovation are significantly higher when resource constraints are relaxed through a greater concentration of economic activity. More theoretical work concerning the mechanisms linking agglomeration, innovation, and economic growth is required.

It may be the case that evidence of scale effects has been eluding growth theorists because they have not fully appreciated what urban economists and economic geographers have known for some time--that space is economically important. We believe this to be the most reasonable and fruitful interpretation of the results presented in this chapter, and it suggests many fascinating avenues for future research. The evidence from many urban studies suggests that accounting for the density of economic activity might provide for further insights to the economics of innovation, technological change, and growth.

The empirical evidence suggests that, while congestion effects are present, agglomeration tends to dominate congestion up to a population density of approximately 10,000 persons per square mile. The only urban areas in the US with such a high level of density include New York City, Boston, San Francisco and Jersey City. Many of the areas typically thought of as being centers of innovation clearly benefit heavily from the urban agglomeration effects estimated in this paper. Again, Boston, San Francisco, New York, and Jersey City are good examples. This evidence fits in well with studies of agglomeration and congestion in productivity levels. Ciccone and Hall (1996) also report evidence of agglomeration and congestion using state level data. As in this study they report agglomeration effects that strongly outweigh congestion.

Extending models of innovation common to the new research on economic growth holds the most promise for understanding the nature of technological differences across economies and differences in economic growth. Combining this framework with the literature concerning economic geography and recognizing the importance of spatial considerations and urbanization in determining growth rates holds the greatest promise for understanding the economics of growth. Empirically understanding the forces at work in the so called "agglomeration effect", and linking these forces back to dynamic models of economic growth and innovation is an important next step.

An increased understanding of the nature and causes of growth, innovation, industry concentration, and the role of knowledge spillovers will require thoughtful theoretical extensions of endogenous innovation models. The literature in this area, and economic geography provides the most fertile ground for the future of this research.