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The economic growth literature suggests that knowledge spillovers are subject to distance decay effects. In this paper the main aim is to provide a theoretical framework and empirical evidence on the role played by other kinds of proximities, namely relational, social and technological proximity, in explaining productivity growth. Using a sample of 249 EU 27 NUTS 2 regions in the period 1990-2004, semiparametric spatial autoregressive models are estimated. Results provide evidence of a positive role of social and relational proximities as important channels of knowledge spillovers, and on the fact that, when simultaneously present, different kinds of proximities generate synergic effects on growth. Resumen La literatura sobre el crecimiento económico sugiere que los spillovers de conocimiento están sujetos a efectos de deterioro por distancia. El objetivo principal de este artículo es proporcionar un marco teórico y pruebas empíricas sobre el papel desempeñado por otros tipos de proximidades (relacional, social y tecnológica), a la hora de explicar el crecimiento de la productividad. Utilizando una muestra de 249 regiones NUTS 2 de la UE 27 para el período 1990-2004, se estiman modelos autorregresivos espaciales semiparamétricos. Los resultados aportan pruebas del papel positivo de las proximidades sociales y relacionales como canales importantes de spillovers de conocimientos, y del hecho de que, cuando se presentan simultáneamente, los diferentes tipos de proximidades generan efectos sinérgicos sobre el crecimiento. [ABSTRACT FROM AUTHOR]

In the coming years, the share of the working-age population in the total population will start to decline in all countries of the European Union. All other things remaining equal, this so-called demographic burden will have a downward effect on economic growth. This paper examines whether the Europe 2020 employment targets would be sufficient to compensate for the downward impact of demographic burden and whether the impact of demography on economic growth differs between EU countries and between urban and rural regions. The results show that raising employment rates to the Europe 2020 targets can restore positive opportunities for economic growth, but not in all countries and only to a limited extent. They also show that even though urban and rural regions differ in terms of population growth and growth of the working age population, the prospects for demographic burden are highly similar for both types of regions. [ABSTRACT FROM AUTHOR]

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. Resumen 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. [ABSTRACT FROM AUTHOR]