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Spatial Externalities and Growth in a Mankiw-Romer-Weil World: Theory and Evidence

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  • Fischer, Manfred M.

Abstract

This paper presents a theoretical growth model that accounts for technological interdependence among regions in a Mankiw-Romer-Weil world. The reasoning behind the theoretical work is that technological ideas cannot be fully appropriated by investors and these ideas may diffuse and increase the productivity of other firms. We link the diffusion of ideas to spatial proximity and allow for ideas to flow to nearby regional economies. Through the magic of solving for the reduced form of the theoretical model and the magic of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form theoretical model and an associated empirical model where changes in a single region can potentially impact all other regions. This implies that conventional regression interpretations of the parameter estimates would be wrong. The proper way to interpret the model has to rely on matrices of partial derivatives of the dependent variable with respect to changes in the Mankiw-Romer-Weil variables, using scalar summary measures for reporting the estimates of the marginal impacts from the model. The summary impact measure estimates indicate that technological interdependence among European regions works through physical rather than human capital externalities.

Suggested Citation

  • Fischer, Manfred M., 2015. "Spatial Externalities and Growth in a Mankiw-Romer-Weil World: Theory and Evidence," Working Papers in Regional Science 2015/04, WU Vienna University of Economics and Business.
  • Handle: RePEc:wiw:wus046:4760
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
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    Cited by:

    1. Carlos Mendez & Felipe Santos-Marquez, 2022. "Economic and Social Disparities across Subnational Regions of South America: A Spatial Convergence Approach," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 64(4), pages 582-605, December.
    2. Vicente German-Soto & Gregory Brock, 2022. "Overall US and Census Region β-Convergence 1963–2015 Controlling for Spatial Effects," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 64(1), pages 44-67, March.

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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