Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial

Most of the empirical works in regional convergence are based on either crosssectional or “a-spatial” panel data models. In this paper, we propose the use of panel data econometrics models that incorporate an explicit consideration of spatial dependence effects (Anselin, 1988; Elhorst, 2001; 2003)....

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Main Authors: Gianfranco Piras, Giuseppe Arbia
Format: Article
Language:English
Published: University of Bologna 2013-05-01
Series:Statistica
Online Access:http://rivista-statistica.unibo.it/article/view/3513
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author Gianfranco Piras
Giuseppe Arbia
author_facet Gianfranco Piras
Giuseppe Arbia
author_sort Gianfranco Piras
collection DOAJ
description Most of the empirical works in regional convergence are based on either crosssectional or “a-spatial” panel data models. In this paper, we propose the use of panel data econometrics models that incorporate an explicit consideration of spatial dependence effects (Anselin, 1988; Elhorst, 2001; 2003). This allows us to extend the traditional convergence models to include a rigorous treatment of regional spillovers and to obtain more reliable estimates of the parameters.We consider two models respectively based on the introduction of a spatial lag among the explanatory variables (the “spatial lag model”) and imposing a spatial autoregressive structure to the stochastic component (the “spatial error model”). We apply such a modelling framework to the long-run convergence of per-capita GDP of 125 EU-NUTS2 regions observed yearly in the period 1977-2002. A comparison of the results obtained using the two spatial panel data specifications with the main evidence available in the literature is also provided.
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spelling doaj.art-f3e3a4b4fe8b44979a71618215d8c4392022-12-22T01:14:06ZengUniversity of BolognaStatistica0390-590X1973-22012013-05-0167215717210.6092/issn.1973-2201/35133260Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatialGianfranco Piras0Giuseppe Arbia1REAL, UIUC E DASTA - Università di ChietiDASTA, Università di ChietiMost of the empirical works in regional convergence are based on either crosssectional or “a-spatial” panel data models. In this paper, we propose the use of panel data econometrics models that incorporate an explicit consideration of spatial dependence effects (Anselin, 1988; Elhorst, 2001; 2003). This allows us to extend the traditional convergence models to include a rigorous treatment of regional spillovers and to obtain more reliable estimates of the parameters.We consider two models respectively based on the introduction of a spatial lag among the explanatory variables (the “spatial lag model”) and imposing a spatial autoregressive structure to the stochastic component (the “spatial error model”). We apply such a modelling framework to the long-run convergence of per-capita GDP of 125 EU-NUTS2 regions observed yearly in the period 1977-2002. A comparison of the results obtained using the two spatial panel data specifications with the main evidence available in the literature is also provided.http://rivista-statistica.unibo.it/article/view/3513
spellingShingle Gianfranco Piras
Giuseppe Arbia
Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial
Statistica
title Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial
title_full Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial
title_fullStr Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial
title_full_unstemmed Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial
title_short Convergence in per-capita GDP across EU-NUTS2 regions using panel data models extended to spatial
title_sort convergence in per capita gdp across eu nuts2 regions using panel data models extended to spatial
url http://rivista-statistica.unibo.it/article/view/3513
work_keys_str_mv AT gianfrancopiras convergenceinpercapitagdpacrosseunuts2regionsusingpaneldatamodelsextendedtospatial
AT giuseppearbia convergenceinpercapitagdpacrosseunuts2regionsusingpaneldatamodelsextendedtospatial