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Exploratory Spatial Data Analysis and Spatial Econometric Modeling for the study of Regional Productivity Differentials in European Union, from 1975 to 2000

Author

Listed:
  • Yiannis Kamarianakis

    () (Regional Analysis Division, Institute of Applied and Computational Mathematics, Foundation for Research and Technology-Hellas, Greece)

  • Julie Le Gallo

    () (legallo@u-bordeaux.fr, France)

Abstract

Economic processes are often characterized by spatial autocorrelation: the coincidence of value similarity to locational similarity. As a consequence of spatial autocorrelation, analysts observe spatial regional clusters. Recent advances in the areas of spatial statistics/econometrics offer tools for the investigation of the aforementioned issues. Following the exploratory spatial data analysis of Le Gallo and Ertur (2003) on European regional per capita GDP we use such tools to investigate the evolution of regional productivity disparities in the European Union and the extent to which the existing interregional inequalities in productivity can be attributed to differences in sectoral composition between regions and/or to uniform productivity gaps across sectors. At the exploratory stage we observe a core-periphery pattern similar to the one observed in the study of regional GDP. At the modeling stage the inclusion of spatial dependencies produces estimations significantly different from the ones presented at previous studies.

Suggested Citation

  • Yiannis Kamarianakis & Julie Le Gallo, "undated". "Exploratory Spatial Data Analysis and Spatial Econometric Modeling for the study of Regional Productivity Differentials in European Union, from 1975 to 2000," Working Papers 0401, University of Crete, Department of Economics.
  • Handle: RePEc:crt:wpaper:0401
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    Keywords

    spatial autocorrelation; exploratory spatial data analysis; European regions; productivity dispariti;

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