Picture of automobile manufacturing plant

Driving innovations in manufacturing: Open Access research from DMEM

Strathprints makes available Open Access scholarly outputs by Strathclyde's Department of Design, Manufacture & Engineering Management (DMEM).

Centred on the vision of 'Delivering Total Engineering', DMEM is a centre for excellence in the processes, systems and technologies needed to support and enable engineering from concept to remanufacture. From user-centred design to sustainable design, from manufacturing operations to remanufacturing, from advanced materials research to systems engineering.

Explore Open Access research by DMEM...

Equilibrium and economic growth: spatial econometric models and simulations

Fingleton, B. (2001) Equilibrium and economic growth: spatial econometric models and simulations. Journal of Regional Science, 41 (1). pp. 117-148. ISSN 0022-4146

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

Neoclassical theory assumes diminishing returns to capital and spatially constant exogenously-determined technological progress, although it is questionable whether these are realistic assumptions for modeling manufacturing productivity growth variations across European Union (E.U.) regions. In contrast, the model developed in this paper assumes increasing returns and spatially varying technical progress, and is linked to endogenous growth theory and particularly to 'new economic geography' theory. Simulations, involving 178 E.U.regions, show that productivity levels and growth rates are higher in all E.U. regions when the financially assisted (Objective 1) regions have faster output growth. This also reduces inequalities in levels of technology. Allowing the core regions to grow faster has a similar effect of raising productivity growth rates across the E.U., although inequality increases. Thus, the simulations are seen as an attempt to develop a type of 'computable geographical equilibrium' model which, as suggested by Fujita, Krugman, and Venables (1999), is the way theoretical economic geography needs to evolve in order to become a predictive discipline.