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Regional Convergence in the European Union, 1985- 1999: A Spatial Dynamic Panel Analysis

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  • Harald Badinger
  • Werner Muller
  • Gabriele Tondl

Abstract

Badinger H., Muller W. G. and Tondl G. (2004) Regional convergence in the European Union, 1985- 1999: a spatial dynamic panel analysis, Reg. Studies38, 241-253. We estimate the speed of income convergence for a sample of 196 European NUTS 2 regions over the period 1985-1999. So far there is no direct estimator available for dynamic panels with spatial dependencies. We propose a two-step procedure, which involves first spatial filtering of the variables to isolate the spatial dependence, and application of standard GMM estimators for dynamic panels in a second step. Our results show that ignorance of the spatial correlation leads to potentially misleading results. Applying a system GMM estimator on the filtered variables, we obtain a speed of convergence of 7%. Badinger H., Muller W. G. et Tondl G. (2004) Convergence regionale dans l'Union europeenne, 1985-1999: une analyse en panel spatial dynamique, Reg. Studies38, 241-253. Nous estimons le taux de convergence des revenus regionaux dans un echantillon de 196 regions europeennes au niveau NUTS 2 sur la periode 1985-1999. Un estimateur pour les panels dynamiques avec autocorrelation spatiale n'a pas encore ete developpe. Nous proposons donc une approche en deux etapes. Cette procedure consiste a d'abord filtrer spatialement les variables afin d'isoler l'autocorrelation spatiale, et d'appliquer ensuite un estimateur GMM standard pour panels dynamiques. Nos resultats indiquent qu'ignorer l'autocorrelation spatiale implique des conclusions potentiellement erronees. En appliquant notre methode en deux etapes, nous aboutissons a un taux de convergence estime de 7%. Badinger H., Muller W. G. und Tondl G. (2004) Regionale Konvergenz in der Europaischen Union, 1985-1999: eine raumliche Panelanalyse, Reg. Studies38, 241-253. Diese Studie schatzt die Geschwindigkeit der Einkommenskonvergenz fur eine Stichprobe von 196 NUTS 2 Regionen. Bis jetzt steht kein direkter Schatzer fur dynamische Panels mit raumlicher Abhangigkeit zur Verfugung. Wir schlagen ein zweistufiges Verfahren vor: in einem ersten Schritt werden die Variablen raumlich gefiltert um die raumliche Abhangigkeit zu isolieren; in einem zweiten Schritt werden Standard- GMM Schatzer fur dynamische Panels verwendet. Die Ergebnisse zeigen, dass das Ignorieren der raumlichen Korrelation zu irrefuhrenden Ergebnissen fuhren kann. Die Verwendung eines System-GMM Schatzers mit den gefilterten Variablen liefert eine Konvergenzgeschwindigkeit von 7 Prozent. Badinger H., Muller W. G. y Tondl G. (2004) Convergencia regional en la Union Europea 1985-1999: un analisis espacial de paneles dinamicos, Reg. Studies38, 241-253. Calculamos la velocidad de convergencia en los ingresos de 196 regiones europeas NUTS 2 durante el periodo comprendido entre 1985 y 1999. Hasta el momento no existe ningun estimador directo que este disponible para paneles dinamicos con dependencias espaciales. Proponemos un procedimiento que consta de dos pasos, el cual comprende, en primer lugar, una filtracion espacial de las variables para aislar la dependencia espacial, y un segundo paso consistente en la aplicacion de estimadores estandares GMM (Metodo de Momentos Generalizado) a paneles dinamicos. Nuestros resultados muestran que no tener en cuenta la correlacion espacial lleva a resultados que son potencialmente enganosos. Aplicando un estimador GMM de sistema a las variables filtradas obtenemos una velocidad de convergencia del siete por ciento.

Suggested Citation

  • Harald Badinger & Werner Muller & Gabriele Tondl, 2004. "Regional Convergence in the European Union, 1985- 1999: A Spatial Dynamic Panel Analysis," Regional Studies, Taylor & Francis Journals, vol. 38(3), pages 241-253.
    • Handle: RePEc:taf:regstd:v:38:y:2004:i:3:p:241-253
    DOI: 10.1080/003434042000211105
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    More about this item

    Keywords

    Growth; Convergence; Spatial Dependence; Spatial Filtering; Dynamic Panels Gmm;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • O00 - Economic Development, Innovation, Technological Change, and Growth - - General - - - General

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