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Marshallian Externalities And The Emergence And Spatial Stability Of Technological Enclaves


  • Paul David
  • Dominique Foray
  • Jean-Michel Dalle


Technological dualism often is found to be associated with the geographical clustering of firms that use the same techniques. To shed further light on these localization phenomena, we analyze the long-run dynamic behavior of a system in which firms' choices among alternative production methods (each of which requires a technique-specific input) are influenced by both firm-specific random shocks and Marshallian 'industrial neighborhood' effects. The latter are local factor market externalities that tend to lower the relative marginal costs d those inputs that are used most extensively in the immediate locale. The model developed here focuses on labor market externalities affecting the supply conditions for workers with technology-specific skills, and their effect on the choices made by producers at various sites whose choice of technique is subject to periodic revisions. A special structure familiar in the applied theory of Markov random fields, the stochastic Ising model. provides a reduced-form representation of this dynamic spatial system. The general properties of models of this type and their application in economics are considered. Discrete time numerical simulations of the behavior of an ensemble of firms (located at the nodes of a finite lattice formed on a two-dimensional (orus) shows that positive neighborhood externalities effects do not necessarily result in the uniquitous diffusion of one of the two available technologies. Instead. this system exhibits a spatially localized form of 'technological dualism," in which at least two technological enclaves emerge and undergo path-dependent evolution. The temporal durations of these spatial patterns in technology adoption are affected by parameters of the Ising model that can be given a straightforward economic interpretation

Suggested Citation

  • Paul David & Dominique Foray & Jean-Michel Dalle, 1998. "Marshallian Externalities And The Emergence And Spatial Stability Of Technological Enclaves," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 6(2-3), pages 147-182.
  • Handle: RePEc:taf:ecinnt:v:6:y:1998:i:2-3:p:147-182 DOI: 10.1080/10438599800000018

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    References listed on IDEAS

    1. Klette, Tor Jakob & Griliches, Zvi, 1996. "The Inconsistency of Common Scale Estimators When Output Prices Are Unobserved and Endogenous," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 343-361, July-Aug..
    2. Jacques Mairesse & Mohamed Sassenou, 1991. "R&D Productivity: A Survey of Econometric Studies at the Firm Level," NBER Working Papers 3666, National Bureau of Economic Research, Inc.
    3. Zvi Griliches & Jacques Mairesse, 1981. "Productivity and R and D at the Firm Level," NBER Working Papers 0826, National Bureau of Economic Research, Inc.
    4. Hall, Bronwyn H. & Mairesse, Jacques, 1995. "Exploring the relationship between R&D and productivity in French manufacturing firms," Journal of Econometrics, Elsevier, vol. 65(1), pages 263-293, January.
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    Cited by:

    1. Dalle, Jean-Michel & Jullien, Nicolas, 2003. "'Libre' software: turning fads into institutions?," Research Policy, Elsevier, vol. 32(1), pages 1-11, January.
    2. Paul A. David & Francesco Rullani, 2006. "Micro-dynamics of Free and Open Source Software Development. Lurking, laboring and launching new projects on SourceForge," LEM Papers Series 2006/26, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Cowan, Robin & Jonard, Nicolas, 2004. "Network structure and the diffusion of knowledge," Journal of Economic Dynamics and Control, Elsevier, vol. 28(8), pages 1557-1575, June.

    More about this item


    economic geography; industrial locslizalion; Marshallian extcrnalities; technology diffusion; path-dependence; Markov random field; stochastic king rnodel J.E.L. Clessification: C6; D2; LO.R3;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D2 - Microeconomics - - Production and Organizations


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