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Sandy Dallerba - One of the best experts on this subject based on the ideXlab platform.
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evaluating the temporal and spatial heterogeneity of the european Convergence Process 1980 1999
Journal of Regional Science, 2006Co-Authors: Julie Le Gallo, Sandy DallerbaAbstract:In this paper, we suggest a framework that allows testing simultaneously for temporal heterogeneity, spatial heterogeneity, and spatial autocorrelation in b-Convergence models. Based on a sample of 145 European regions over the 1980-1999 period, we estimate a Seemingly Unrelated Regression Model with spatial regimes and spatial autocorrelation for two sub-periods: 1980-1989 and 1989-1999. The assumption of temporal independence between the two periods is rejected, and the estimation results point to the presence of spatial error autocorrelation in both sub-periods and spatial instability in the second sub-period, indicating the formation of a Convergence club between the peripheral regions of the European Union. Copyright Blackwell Publishers, 2006
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evaluating the temporal and spatial heterogeneity of the european Convergence Process 1980 1999
Cahiers du GRES (2002-2009), 2006Co-Authors: Julie Le Gallo, Sandy DallerbaAbstract:In this paper, we suggest a general framework that allows testing simultaneously for temporal heterogeneity, spatial heterogeneity and spatial autocorrelation in beta-Convergence models. Based on a sample of 145 European regions over the 1980-1999 period, we estimate a Seemingly Unrelated Regression model with spatial regimes and spatial autocorrelation for two sub-periods: 1980-1989 and 1989-1999. The assumption of temporal independence between the two periods is rejected and the estimation results highlight the presence of spatial error autocorrelation in both sub-periods and spatial instability in the second sub-period, indicating the formation of a Convergence club between the peripheral regions of the European Union. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed (This abstract was borrowed from another version of this item.)
Julie Le Gallo - One of the best experts on this subject based on the ideXlab platform.
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evaluating the temporal and spatial heterogeneity of the european Convergence Process 1980 1999
Journal of Regional Science, 2006Co-Authors: Julie Le Gallo, Sandy DallerbaAbstract:In this paper, we suggest a framework that allows testing simultaneously for temporal heterogeneity, spatial heterogeneity, and spatial autocorrelation in b-Convergence models. Based on a sample of 145 European regions over the 1980-1999 period, we estimate a Seemingly Unrelated Regression Model with spatial regimes and spatial autocorrelation for two sub-periods: 1980-1989 and 1989-1999. The assumption of temporal independence between the two periods is rejected, and the estimation results point to the presence of spatial error autocorrelation in both sub-periods and spatial instability in the second sub-period, indicating the formation of a Convergence club between the peripheral regions of the European Union. Copyright Blackwell Publishers, 2006
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evaluating the temporal and spatial heterogeneity of the european Convergence Process 1980 1999
Cahiers du GRES (2002-2009), 2006Co-Authors: Julie Le Gallo, Sandy DallerbaAbstract:In this paper, we suggest a general framework that allows testing simultaneously for temporal heterogeneity, spatial heterogeneity and spatial autocorrelation in beta-Convergence models. Based on a sample of 145 European regions over the 1980-1999 period, we estimate a Seemingly Unrelated Regression model with spatial regimes and spatial autocorrelation for two sub-periods: 1980-1989 and 1989-1999. The assumption of temporal independence between the two periods is rejected and the estimation results highlight the presence of spatial error autocorrelation in both sub-periods and spatial instability in the second sub-period, indicating the formation of a Convergence club between the peripheral regions of the European Union. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed (This abstract was borrowed from another version of this item.)
Stephen Broadberry - One of the best experts on this subject based on the ideXlab platform.
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Vive la différence: Disaggregation of the productivity Convergence Process
Revista De Historia Economica, 1997Co-Authors: Stephen BroadberryAbstract:This paper examines the Convergence Process at a disaggregated level in a historical context. A three-way disaggregation of the national accounts by output, income and expenditure reveals a wealth of diversity, bom over time and across countries, i.e. history and geography matter. Countries can specialise according to comparative advantage, and Convergence at the aggregate level can occur through changes in structure as well as through Convergence at the micro level. Similarly, changes in factor proportions may lead to Convergence of aggregate incomes without requiring Convergence of all factor prices at the micro level. Also, differences in preferences may persist, so that individual components of expenditure do not need to converge in line with aggregate expenditure. Convergence at the aggregate level, dren, does not necessarily lead to uniformity. Vive la diffA©rence!
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Vive la différence: Disaggregation of the productivity Convergence Process
Revista de Historia Económica Journal of Iberian and Latin American Economic History, 1997Co-Authors: Stephen BroadberryAbstract:RESUMENEste trabajo examina el proceso de convergencia en perspectiva histórica a nivel desagregado. Tomando en consideración la producción, la renta y el gasto este trabajo muestra una gran diversidad geográfica y temporal. Cada país se especializó según su ventaja comparativa y la convergencia se produjo tanto a través de cambios en su estructura productiva, como a niveles microeconómicos. Asimismo, variaciones en la proporción de las facturas condujo a una mejor convergencia de la renta sin necesidad de una mayor aproximación de los precios de los factores. El trabajo demuestra también que persistieron importantes diferencias en las preferencias de los consumidores. Así pues, el proceso de convergencia a nivel agregado no condujo necesariamente a la uniformidad de las economías. ¡Vive la differénce!
Julie Le Gallo - One of the best experts on this subject based on the ideXlab platform.
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The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?
International Regional Science Review, 2006Co-Authors: Cem Ertur, Julie Le Gallo, Catherine BaumontAbstract:The authors show that spatial dependence and spatial heterogeneity matter in the estimation of the I²-Convergence Process among 138 European regions over the 1980 to 1995 period. Using spatial econometrics tools, the authors detect both spatial dependence and spatial heterogeneity in the form of structural instability across spatial Convergence clubs. The estimation of the appropriate spatial regimes spatial error model shows that the Convergence Process is different across regimes. The authors also estimate a strongly significant spatial spillover effect: the average growth rate of per capita GDP of a given region is positively affected by the average growth rate of neighboring regions.
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Geographic Spillover Effects of Regional Funds and their Impact on the European Convergence Process over 1989-1999
2003Co-Authors: Sandy Dall'erba, Julie Le GalloAbstract:The aim of this paper is to highlight the role of geographic spillover effects due to the regional funds on the Convergence Process of 145 European regions over 1989-1999. With the aim of enhancing cohesion, these funds are primarily allocated to the least developed regions. First the most important part of these funds is devoted to transportation infrastructures, which induce strong spillover effects. However they do not necessarily contribute to a more even regional development. Their impact has therefore to be seen in the light of growth rate variations of the targeted region and of the whole sample. Second, since the wealthiest regions have more ability to accompany regional funds, the role of additional funds in the regional development Process is investigated as well. Using the formal tools of spatial econometrics, we first detect strong evidence of spatial autocorrelation, both on per capita GDP and regional funds. Moreover, two clusters, representative of the core-periphery framework, are persistent over the period and highlight spatial heterogeneity. These spatial effects are then included in the estimation of an appropriate conditional -Convergence model, which allows us to control for spatial spillover effects among regions. Finally, with this model, we assess the impact of European regional funds on the regional Convergence Process using simulation experiments.
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The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?
Econometrics, 2002Co-Authors: Catherine Baumont, Cem Ertur, Julie Le GalloAbstract:We show in this paper that spatial dependence and spatial heterogeneity matter in the estimation of the b-Convergence Process among 138 European regions over the 1980-1995 period. Using spatial econometrics tools, we detect both spatial dependence and spatial heterogeneity in the form of structural instability across spatial Convergence clubs. The estimation of the appropriate spatial regimes spatial error model shows that the Convergence Process is different across regimes. We also estimate a strongly significant spatial spillover effect: the average growth rate of per capita GDP of a given region is positively affected by the average growth rate of neighboring regions.
Boriss Siliverstovs - One of the best experts on this subject based on the ideXlab platform.
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The Russian regional Convergence Process
Eastern European Economics, 2012Co-Authors: Konstantin A. Kholodilin, Aleksey Oshchepkov, Boriss SiliverstovsAbstract:This paper investigates income Convergence among Russian regions between 1998 and 2006. It makes two major contributions to the literature on regional Convergence in Russia. First, it identifies spatial regimes using the exploratory spatial data analysis. Second, it examines the impact of spatial effects on the Convergence Process. Our results show that the overall speed of regional Convergence in Russia, being slow by international standards, becomes even slower after controlling for spatial effects. However, when accounting for spatial regimes, we find a strong regional Convergence among high-income regions located near other high-income regions. Our results indicate that estimating the speed of Convergence using aggregate data may result in misleading conclusions regarding the nature of the Convergence Process among Russia's regions.
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The Russian regional Convergence Process: Where does it go? {
SSRN Electronic Journal, 2009Co-Authors: Konstantin A. Kholodilin, Aleksey Oshchepkov, Boriss SiliverstovsAbstract:This paper investigates the income Convergence among Russian regions in the period 1998-2006. It makes two major contributions to rather extensive literature on the regional Convergence in Russia. First, it identifies spatial regimes using the exploratory spatial data analysis. Second, it examines the impact of spatial effects on the Convergence Process. Our results show that the overall speed of regional Convergence in Russia, being low by international standards, becomes even lower after controlling for spatial effects. However, when accounting for the spatial regimes, we find a strong regional Convergence among high-income regions located near other high-income regions. Our results indicate that estimation of speed of Convergence using aggregate data may result in misleading conclusions regarding the nature of Convergence Process among Russia's regions.
