Exploratory Spatial Data Analysis and Spatial Econometric Modeling for the study of Regional Productivity Differentials in European Union, from 1975 to 2000
Yiannis Kamarianakis () and
Julie Le Gallo ()
No 401, Working Papers from University of Crete, Department of Economics
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.
Keywords: spatial autocorrelation; exploratory spatial data analysis; European regions; productivity dispariti (search for similar items in EconPapers)
Pages: 18 pages
New Economics Papers: this item is included in nep-eff, nep-geo and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:crt:wpaper:0401
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