Econometric Analysis of Income Convergence in Selected EU Countries and Their Nuts 3 Level Regions

Paas, Tiiu; Kuusk, Andres; Schlitte, Friso; Võrk, Andres

doi:10.2139/ssrn.1078863

Cited by 42 publications

(41 citation statements)

References 13 publications

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“…Previous literature testing for correlation between neighbouring regions in the EU generally finds evidence of high spatial autocorrelation of per capita income levels and dynamics (see, among the others, López-Bazo et al 1999;Stirböck 2004 that finds a positive spatial correlation between production sectors as well). Early studies considering the enlarged EU confirm the presence of spatial correlation (see Fischer & Stirböck 2005;Paas et al 2007;Chapman et al 2010).…”

Section: Spatial Correlation -mentioning

confidence: 95%

“…So far several empirical papers have investigated convergence in the EU‐25 (or 27) following different methodologies. Fischer and Stirböck (2004), Debarsy and Ertur (2006), Frenken and Hoekman (2006), Paas et al . (2007) test for convergence across the enlarged EU in the context of regression analysis; Ertur and Koch (2006) use exploratory spatial data analysis; Ezcurra and Rapun (2007) adopt a non‐parametric approach; Chapman et al .…”

Section: Introductionmentioning

confidence: 94%

“…So far several empirical papers have investigated convergence in the EU-25 (or 27) following different methodologies. Fischer and Stirböck (2004), Debarsy and Ertur (2006), Frenken and Hoekman (2006), Paas et al (2007) test for convergence across the enlarged EU in the context of regression analysis; Ertur and Koch (2006) use exploratory spatial data analysis; adopt a non-parametric approach; Chapman et al (2010) use both non-parametric and spatial regimes analyses. Overall they find some evi-dence of convergence (Fischer & Stirböck 2004;Frenken & Hoekman 2006;, but also of a new North-West/ East polarisation pattern which replaces the previous North-South one for the EU-15 (Ertur & Koch 2006;Chapman et al 2010).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Income Disparities in the Enlarged Eu: Socio‐economic, Specialisation and Geographical Clusters

Chapman

Meliciani

2011

Tijd voor Econ & Soc Geog

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The paper contains a non‐parametric analysis of regional convergence in the enlarged EU over the period 1998–2005. It finds overall convergence but growing within country disparities, especially due to the behaviour of newcomer regions. It also finds strong (but falling) spatial correlation of per‐capita income. Starting from this evidence, the paper considers the role of socio‐economic features, specialisation patterns and geographical factors in explaining within countries disparities. Overall we find that partly specialisation but more evidently socio‐economic clusters have a good explanatory power while simple geographical factors do not explain within countries divergence. This does not mean that spatial factors are not important: rather it means that agglomeration alone cannot explain a complex and variegated pattern of growth where structural and socio‐economic factors appear to be playing an important and increasing role.

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Section: Spatial Correlation -mentioning

confidence: 95%

Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

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Income Disparities in the Enlarged Eu: Socio‐economic, Specialisation and Geographical Clusters

Chapman

Meliciani

2011

Tijd voor Econ & Soc Geog

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“…Egger and Pfaffermayr (2005) or Paas and Schlitte (2007). If the same held for income dynamics, any analysis of real convergence would be under the imperative to use regional instead of national data.…”

Section: Introductionmentioning

confidence: 99%

Regional Dynamics of Unemployment in Poland A Convergence Approach

Tyrowicz

Wójcik²

2010

The Labour Market Impact of the EU Enlargement

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In this paper we approach the regional unemployment dynamics in Poland. Using policy relevant NUTS4 level data from 1999 to 2006, we employ tools typically applied to income convergence analyses to inquire the patterns of unemployment distribution. We apply diverse analytical techniques to seek traces of convergence, including β and σ convergence as well as pass-through analysis.We demonstrate that the unemployment rate distribution is highly stable over time, while only weak 'convergence of clubs' is supported by the data and only for the high unemployment regions. Results suggest no support in favour of β-type convergence, i.e. convergence of levels. Even controlling for nation-wide labour market outlooks (conditional convergence) does not provide any support to this hypothesis. Further, regions with both very high and very low unemployment show signs of high persistence and low mobility in the national distribution, while those in the middle tend to demonstrate higher mobility and essentially no persistence of regional unemployment differentials. This diagnosis is confirmed by σ-convergence analysis which indicates no general divergence or convergence patterns. Transitions seem to be slightly more frequent, but at the same time less sustainable for middle range districts, while movements up and down the ladder occur predominantly for the same districts.This methodology allows to define the patterns of local labour market dynamics, pointing to differentiated divergence paths. Importantly, these tendencies prevail despite cohesion financing schemes, which allocate relatively more resources to deprived regions.

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“…Moreover, Hungary is a good example of how the lack of institutional and implementing abilities, together with weak EC control of community funds, could vanish the value added of the EU policy, especially in the most peripheral and rural areas, fi nally increasing the internal development gap. Previous analyses investigated income-level convergence in the enlarged EU following different methodologies: Matkowski and Próchniak (2004) and Paas et al (2007) use parametric methodologies; Ertur and Koch (2006) use exploratory spatial analysis; Ezcurra et al (2007) adopt a non-parametric approach, highlighting the role played by neighbouring regions for explaining the dispersion in the distribution of GDP per worker; Chapman and Meliciani (2012) use non-parametric and spatial regimes analyses. They mainly fi nd evidence of catch-up during the integration process, but also a new north-west/east polarisation pattern which replaces the previous north-south one for the EU-15.…”

mentioning

confidence: 99%

Non parametric methods to assess the role of the CAP in regional convergence in Hungary

Monasterolo¹,

Benni²

2013

stagec

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Econometric Analysis of Income Convergence in Selected EU Countries and Their Nuts 3 Level Regions

Cited by 42 publications

References 13 publications

Income Disparities in the Enlarged Eu: Socio‐economic, Specialisation and Geographical Clusters

Income Disparities in the Enlarged Eu: Socio‐economic, Specialisation and Geographical Clusters

Regional Dynamics of Unemployment in Poland A Convergence Approach

Non parametric methods to assess the role of the CAP in regional convergence in Hungary

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