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Convergence of European regions An approach by spatial econometrics

Catherine Baumont, Cem Ertur, Julie Le Gallo, 21 (France). Lab. d'Analyse et de Techniques Economiques (LATEC) Dijon Univ., 21 - Dijon (France). Lab. d'Analyse et de Techniques Economiques (LATEC) Centre National de la Recherche Scientifique (CNRS)

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Abstract

The aim of this paper is the analysis of spatial dependence in convergence processes applied to European regions. First, we apply the recently developed exploratory spatial data analysis (Anselin, 1996) in order to describe more precisely the geographical dynamics of European regional income growth patterns. New insights are brought to the usual cr-convergence measure, which hides geographical patterns that may fluctuate over time. Second, we test the presence of spatial autocorrelation in /^-convergence models by using spatial econometrics methods (Anselin, 1988 ; Anselin and Florax, 1995). We compare the results with and without spatial autocorrelation in order to assess the effect of geographic spillovers on regional growth.

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What this paper is about

The aim of this paper is the analysis of spatial dependence in convergence processes applied to European regions. First, we apply the recently developed exploratory spatial data analysis (Anselin, 1996) in order to describe more precisely the geographical dynamics of European regional income growth patterns. New insights are brought to the usual cr-convergence measure, which hides geographical patterns that may fluctuate over time. Second, we test the presence of spatial autocorrelation in /^-convergence models by using spatial econometrics methods (Anselin, 1988 ; Anselin and Florax, 1995). We compare the results with and without spatial autocorrelation in order to assess the effect of geographic spillovers on regional growth.

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Available abstract

The aim of this paper is the analysis of spatial dependence in convergence processes applied to European regions. First, we apply the recently developed exploratory spatial data analysis (Anselin, 1996) in order to describe more precisely the geographical dynamics of European regional income growth patterns. New insights are brought to the usual cr-convergence measure, which hides geographical patterns that may fluctuate over time. Second, we test the presence of spatial autocorrelation in /^-convergence models by using spatial econometrics methods (Anselin, 1988 ; Anselin and Florax, 1995). We compare the results with and without spatial autocorrelation in order to assess the effect of geographic spillovers on regional growth.

Key concepts: Convergence (economics), Spatial econometrics, Econometrics, Computer science, Mathematics, Economics, Macroeconomics

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