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Agglomeration, Innovation and Regional Development: Theoretical Perspectives and Meta-Analysis

Listed author(s):
  • Henri L.F. de Groot

    ()

    (Vrije Universiteit Amsterdam)

  • Jacques Poot

    ()

    (University of Waikato, Hamilton, NZ)

  • Martijn J. Smit

    ()

    (Vrije Universiteit Amsterdam)

Innovation and technological change are central to the quest for regional development. In the globally-connected knowledge-driven economy, the relevance of agglomeration forces that rely on proximity continues to increase, paradoxically despite declining real costs of information, communication and transportation. Globally, the proportion of the population living in cities continues to grow and sprawling cities remain the engines of regional economic transformation. The growth of cities results from a complex chain that starts with scale, density and geography, which then combines with industrial structure characterised by its extent of specialisation, competition and diversity, to yield innovation and productivity growth that encourages employment expansion, and further urban growth through inward migration. This paper revisits the central part of this virtuous circle, namely the Marshall-Arrow-Romer externalities (specialisation), Jacobs externalities (diversity) and Porter externalities (competition) that have provided alternative explanations for innovation and urban growth. The paper evaluates the statistical robustness of evidence for such externalities presented in 31 scientific articles, all building on the seminal work of Glaeser et al. (1992). These articles yield 393 estimates of those externalities, which are characterized by their sign and statistical significance. We aim to explain variation in estimation results using study characteristics by means of ordered probit analysis. The evidence in the literature on the role of the specific externalities is rather mixed, although for each type of externality we can identify how various aspects of primary study design, such as the adopted proxy for growth, the data used, and the choice of covariates influence the outcomes.

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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 07-079/3.

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Date of creation: 10 Oct 2007
Handle: RePEc:tin:wpaper:20070079
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