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MULTILEVEL MODELS: AN APPLICATION TO THE BETA-CONVERGENCE MODEL

Authors: Coro CHASCO; Ana Mª LÓPEZ;

MULTILEVEL MODELS: AN APPLICATION TO THE BETA-CONVERGENCE MODEL

Abstract

Many kinds of data in the social sciences have a hierarchical, multilevel or clustered structure. For example, municipalities are grouped into regions; regions are formed within countries; and quite often, countries belong to supra-national organizations. Once groupings are established, they will tend to become differentiated, and this differentiation implies that the group and its members both influence and are influenced by group membership. To ignore this relationship is to risk overlooking the importance of group effects and it may also render invalid many of the traditional statistical analysis techniques used for studying data relationships. In this paper, we specify a basic two-level model for a conditional beta-convergence model of a sample of European NUTS-2 regions. Specifically, we test for the role of regional decentralization (country-level variable) on regional income growth, since it has been suggested that countries with a governmental form of regional decentralization foster innovation and economic growth.

Keywords

MULTILEVEL MODELS, HIERARCHICAL MODELS, CONVERGENCE, EUROPEAN REGIONS, DECENTRALIZATION, SPATIAL EFFECTS, jel: jel:C23, jel: jel:C21, jel: jel:O18, jel: jel:R15

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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