Regions, technological interdependence and growth in Europe (original) (raw)
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Journal of Macroeconomics, 2015
This study examines the role of proximity in regional growth using a multi-dimensional framework, for seven EU countries during 1990-2005. We incorporate geographical as well as economic and technological effects in two seminal growth models in order to test for the existence and magnitude of interregional externalities. Our findings show that spillovers are important for European regional growth, regardless of the measure of proximity; thus regions surrounded by dynamic entities are likely to growth faster than otherwise. Moreover, our results underline the need for coordinated EU policies aiming at higher physical and human capital accumulation, taking into account regional synergies.
Spatial knowledge spillovers and regional productivity growth in Europe
Revue d’Économie Régionale & Urbaine, 2007
The aim of this paper, which is strictly empirical in nature, is to analyze the effects that local, national, and international technological knowledge spillovers can play on labor productivity dynamics in the manufacturing sectors located in European regions between 1980 and 1992. In particular, by adopting a modified version of a 'catching-up' equation and by using an enlarged version of Eurostat's REGIO database, we will empirically verify whether the three dimensions discussed above are possible explanatory factors for the labor productivity growth of firms located in different European regions. We will thus examine eventual trade-offs between local (regarding the transfer of 'tacit' knowledge) and global (regarding the diffusion of fully 'codified' knowledge) pressures as possible determinants of the growth in manufacturing productivity at the regional level in Europe between 1980 and 1992.
Regional economic growth in Europe: A semiparametric spatial dependence approach
Papers in Regional Science, 2008
AbstractIn this article a semiparametric spatial Durbin model is employed to analyse the growth behaviour of 155 European regions in the period 1988–2000. This specification combines the semiparametric approach with the usual parametric spatial econometric technique to accommodate both spatial dependence and nonlinearities as suggested by recent neoclassical growth models with spatial technological interdependence. The results provide evidence of nonlinearities in the effect of initial per capita incomes and human capital investments. Moreover, the specification used allows identifying the effect of the interaction between the characteristics (initial conditions and structural variables) of each region and those of its neighbours. Finally, it shows some indication of global spillovers across-country and local spatial spillovers from domestic neighbours.In this article a semiparametric spatial Durbin model is employed to analyse the growth behaviour of 155 European regions in the period 1988–2000. This specification combines the semiparametric approach with the usual parametric spatial econometric technique to accommodate both spatial dependence and nonlinearities as suggested by recent neoclassical growth models with spatial technological interdependence. The results provide evidence of nonlinearities in the effect of initial per capita incomes and human capital investments. Moreover, the specification used allows identifying the effect of the interaction between the characteristics (initial conditions and structural variables) of each region and those of its neighbours. Finally, it shows some indication of global spillovers across-country and local spatial spillovers from domestic neighbours.ResumenEn este artículo se emplea un modelo semiparamétrico espacial de Durbin para analizar el comportamiento del crecimiento de 155 regiones europeas durante el periodo 1988–2000. Esta especificación combina el enfoque semiparamétrico con técnicas econométricas espaciales paramétricas habituales para reconciliar la dependencia espacial y las no linealidades, tal y como sugieren los modelos de crecimiento neoclásicos recientes con interdependencia tecnológica espacial. Los resultados ofrecen pruebas de no linealidades en el efecto de ingresos per capita iniciales e inversiones en capital humano. Además, la especificación utilizada permite utilizar el efecto de la interacción entre las características (condiciones iniciales y variables estructurales) de cada región y las de sus vecinos. Finalmente, da una idea de spillovers (efectos de derrame) globales entre países y spillovers espaciales locales de regiones vecinas dentro del país.En este artículo se emplea un modelo semiparamétrico espacial de Durbin para analizar el comportamiento del crecimiento de 155 regiones europeas durante el periodo 1988–2000. Esta especificación combina el enfoque semiparamétrico con técnicas econométricas espaciales paramétricas habituales para reconciliar la dependencia espacial y las no linealidades, tal y como sugieren los modelos de crecimiento neoclásicos recientes con interdependencia tecnológica espacial. Los resultados ofrecen pruebas de no linealidades en el efecto de ingresos per capita iniciales e inversiones en capital humano. Además, la especificación utilizada permite utilizar el efecto de la interacción entre las características (condiciones iniciales y variables estructurales) de cada región y las de sus vecinos. Finalmente, da una idea de spillovers (efectos de derrame) globales entre países y spillovers espaciales locales de regiones vecinas dentro del país.
Regional Externalities And Growth: Evidence From European Regions*
Journal of Regional Science, 2004
This paper models externalities of production across regional economies. Under the assumption that knowledge diffuses without political or administrative barriers, we derive externalities that affect the steady state and the process of growth of each economy. The empirical counterpart of the reduced form equation summarizing the process of growth allows us to test for the presence of regional spillovers and to measure their magnitude. Our results for a sample of European regions show that spillovers are far from negligible, are robust to the consideration of variables within each region, and may cause nondecreasing returns at the spatial aggregate level. The paper also relates previous empirical evidence on spatial dependence in growth studies to the externalities modeled here. 43 *Raymond Florax and Bernard Fingleton provided useful comments on earlier drafts. Three anonymous referees also provided comments that greatly improved the paper. We also want to thank the current and previous editors for comments and encouragement. Authors acknowledge financial support from
Regional Studies, 2008
Research on the impact of innovation on regional economic performance in Europe has fundamentally followed three approaches: a) the analysis of the link between investment in R&D, patents, and economic growth; b) the study of the existence and efficiency of regional innovation systems; and c) the examination of geographical diffusion of regional knowledge spillovers. These complementary approaches have, however, rarely been combined. Important operational and methodological barriers have thwarted any potential cross-fertilization. In this paper, we try to fill this gap in the literature by combining in one model R&D, spillovers, and innovation systems approaches. A multiple regression analysis is conducted for all regions of the EU-25, including measures of R&D investment, proxies for regional innovation systems, and knowledge and socio-economic spillovers. This approach allows us to discriminate between the influence of internal factors and external knowledge and institutional flows on regional economic growth. The empirical results highlight how the interaction between local and external research with local and external socio-economic and institutional conditions determines the potential of every region in order to maximise its innovation capacity. They also indicate the importance of proximity for the transmission of economically productive knowledge, as spillovers show strong distance decay effects. In the EU-25 context, only the innovative efforts pursued within a 180 minute travel radius have a positive and significant impact on regional growth performance.
Regional productivity growth in Europe: a Schumpeterian perspective
Using data for the European regions at NUTS-2 level, we test the predictions of a microfounded Schumpeterian growth model with technological interdependence recently developed by Ertur and Koch (2011, EK11). Spatial interdependence is identified by means of a semiparametric geoadditive spatial autoregressive model which permits us to disentangle the effect of nonlinearities, spatial heterogeneity and spatial dependence. A control function approach is applied to estimate this particular SAR-type model using the spatial lag of the quality of regional governance and the spatial lags of various social capital measures as instrumental variables for the endogenous term Wy. The results corroborates the predictions of EK11's model: R&D investments and R&D spillovers are important divers of regional growth in Europe. However, spillover effects are much lower after controlling for spatial unobserved heterogeneity. Moreover, important nonlinearities in the effect of physical capital investments emerge, putting into question the strong homogeneity assumption and suggesting a threshold effect in growth behavior.
Geographic spillover and growth: a spatial econometric analysis for European regions
2000
The aim of this paper is to integrate the geographical dimension of data in the estimation of the convergence of European regions and emphasize the importance of spatial effects in regional economic growth phenomena. In a sample of 122 European regions over the 1980-1995 period, we find strong evidence of spatial autocorrelation in the unconditional β-convergence model using spatial econometric methods with different weight matrices: a simple contiguity matrix and 4 distance-based matrices. Therefore, this standard β-convergence model exhibit misspecification, its estimation by OLS leads to inefficient estimators and invalid statistical inference. We suggest then a "minimal" specification of β-convergence, which integrates and treats adequately the spatial autocorrelation detected.. Moreover, this model is interpreted as a conditional β-convergence model revealing a spatial spillover effect between European regions. Therefore the European regions are interdependent and we show by a simulation experiment that a random shock affecting a given region propagates to all the regions of the sample.