The beta-convergence model has been widely used to predict the convergence rates of European regions to their steady states. However, this model has two major limitations. First, it does not take into account the spatial interactions of the economies and, second, it does not include their structural differences. Many authors have overcome the first problem by sing spatial econometric techniques such as spatial lag or spatial error, but the latter problem has remained unresolved. In our model we use the spatial filtering technique to manage both spatial dependence and structural differences of the economies. Our results show that European regions have a wide range of convergence rates and in some cases regions with similar structural conditions are clustered. The spatial filtering technique is also able to highlight the scale (local, regional or global) of the phenomena that influence growth. This information is very useful for policy makers.
Pecci, F., Pontarollo, N. (2010). The Application of Spatial Filtering Technique to the Economic Convergence of the European Regions between 1995 and 2007. In D. Hutchison, T. Kanade, J. Kittler, J.M. Kleinberg, F. Mattern, J.C. Mitchell, et al. (a cura di), Computational science and its applications - ICCSA 2010, Pt 1, Proceedings (pp. 46-61). Springer Verlag [10.1007/978-3-642-12156-2-4].
The Application of Spatial Filtering Technique to the Economic Convergence of the European Regions between 1995 and 2007
Pontarollo, Nicola
2010
Abstract
The beta-convergence model has been widely used to predict the convergence rates of European regions to their steady states. However, this model has two major limitations. First, it does not take into account the spatial interactions of the economies and, second, it does not include their structural differences. Many authors have overcome the first problem by sing spatial econometric techniques such as spatial lag or spatial error, but the latter problem has remained unresolved. In our model we use the spatial filtering technique to manage both spatial dependence and structural differences of the economies. Our results show that European regions have a wide range of convergence rates and in some cases regions with similar structural conditions are clustered. The spatial filtering technique is also able to highlight the scale (local, regional or global) of the phenomena that influence growth. This information is very useful for policy makers.
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