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Space-Time Analysis of GDP Disparities among European Regions: A Markov Chains Approach

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  • Julie Le Gallo

Abstract

The purpose of this article is to study the evolution of GDP disparities among 138 European regions over the period from 1980 to 1995. Regional per capitaGDPcross-sectional distribution is characterized by means of nonparametric estimations of density functions, and the growth process is modeled as a first-order stationary Markov chain. Spatial effects are then introduced within the Markov chain framework using regional conditioning and spatial Markov chains. The results of the analysis indicate the persistence of regional disparities, a progressive bias toward a poverty trap, and the importance of geography in the convergence process.

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  • Julie Le Gallo, 2004. "Space-Time Analysis of GDP Disparities among European Regions: A Markov Chains Approach," International Regional Science Review, , vol. 27(2), pages 138-163, April.
    • Handle: RePEc:sae:inrsre:v:27:y:2004:i:2:p:138-163
    DOI: 10.1177/0160017603262402
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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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