Regional disparities in the European Union and the enlargement process: an exploratory spatial data analysis, 1995–2000

Ertur, Cem; Koch, Wilfried

doi:10.1007/s00168-006-0062-x

Regional disparities in the European Union and the enlargement process: an exploratory spatial data analysis, 1995–2000

Original Paper
Published: 07 April 2006

Volume 40, pages 723–765, (2006)
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Cem Ertur¹ &
Wilfried Koch¹

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Abstract

The aim of this paper is to study the space–time dynamics of European regional per capita gross domestic product (GDP) in the perspective of the enlargement of the European Union using exploratory spatial data analysis. We find strong evidence of global and local spatial autocorrelation as well as spatial heterogeneity in the distribution of regional per capita GDP in a sample of 258 European regions including regions from acceding and candidate European countries over the period 1995–2000. However, contrary to previous results obtained in the literature highlighting a North–South polarization scheme, the enlargement process leads to a new North–West–East polarization scheme. The economic dynamism of EU15 regions and acceding or candidate regions is also investigated by exploring the spatial pattern of regional growth. Implications for regional development and cohesion policies are finally suggested.

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Regional Dynamics in EU11

Regional Inequalities in Central and Eastern European Countries: The Role of Capital Regions and Metropolitan Areas

The Impact of Structural Funds on Regional Growth: A Panel Data Spatial Analysis

Article Open access 01 September 2020

Notes

French acronym for Nomenclature for Territorial Statistical Units used by Eurostat.
All computations have been realized by means of SpaceStat 1.90 (Anselin 1999) and GeoDa 1.93 (Anselin 2003). Maps and figures have been realized using Arcview 3.2 (ESRI).
Complete results for k=15, 20, 25 nearest neighbors are available from the authors upon request.
Note that statistics which include the value taken by the variable in region i have also been suggested by Getis and Ord (1992) and Ord and Getis (1995).
More about this problem can be found in Savin (1984).
The complete results are presented in Appendix B for the restricted sample of 203 regions and in Appendix D for the sample of 258 regions extended to candidate countries.
High (resp. low) means above (resp. below) the mean.
Following Anselin (1995, p.101), the G _i(d) statistic cannot be considered as a LISA “because its individual components are not related to a global statistic of spatial association”.
Note that only the quantity \({\sum\nolimits_j {w_{{ij}} {\left( {x_{i} - \mu } \right)}} }\) needs to be computed for each permutation because the term \({{( {x_{i} - } )}} {/ {{{{( {x_{i} - } )}} {m_{0} }}} . } {m_{0} }\) remains constant for a given location i.
Results using the Bonferroni 5% pseudo-significance level are presented in Appendix E. The complete results are presented in Appendix C for the restricted sample of 203 regions and in Appendix D for the sample of 258 regions extended to candidate countries.
We note that almost all of these statistics are significant using the Bonferroni pseudo-significance level.
We use the approximation of average annual growth rates throughout the period 1995–2000, i.e., for a region i of the sample, we have \(g_{i} = {{\left[ {{\text{ln }}y_{{i,2000}} - {\text{ln }}y_{{i,1995}} } \right]}} \mathord{\left/ {\vphantom {{{\left[ {{\text{ln }}y_{{i,2000}} - {\text{ln }}y_{{i,1995}} } \right]}} 5}} \right. \kern-\nulldelimiterspace} 5\) where y _i,2000 and y _i,1995 stand for per capita GDP of region i measured in PPS, respectively, in 2000 and 1995. Indeed, this variable is the dependant variable in empirical growth regressions.
The complete results are presented in Appendix B for the restricted sample of 203 regions and in Appendix D for the sample of 258 regions extended to new acceding and candidate countries.
The complete results are presented in Appendix C for the restricted sample of 203 regions and in Appendix D for the sample of 258 regions extended to new acceding and candidate countries.

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Acknowledgements

We would like to thank J. Le Gallo and B. Schmitt for their valuable comments. We would also like to thank A. Behrens from the regional statistics section (division E4) as well as J. Recktenwald and I. Dennis for the help they provided on the Eurostat-Regio database. The usual disclaimer applies.

Author information

Authors and Affiliations

LEG UMR 5118 CNRS, Université de Bourgogne, Pôle d’Economie et de Gestion, B.P. 26611, 21066, Dijon, Cedex, France
Cem Ertur & Wilfried Koch

Authors

Cem Ertur
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Wilfried Koch
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Corresponding author

Correspondence to Cem Ertur.

Additional information

A previous version of this paper was presented at the 3rd Spatial Econometrics Workshop in Strasbourg, June 9, 2004 and at the XLth Conference of the French Speaking Regional Science Association, Brussels, September 1–3, 2004

Appendices

Appendix A

1.1 Eurostat-Regio database

The data are extracted from the Eurostat-Regio database. Eurostat is the Statistical Office of the European Communities. Its task is to provide the EU with statistics at European level that enable comparisons between countries and regions. These statistics are used by the European Commission and other European institutions so that they can define, implement, and analyze community policies. The Regio database is the official source of harmonized annual data at the regional level throughout the 1980–1995 period for the EU, and per capita GDP is likely to be one of the most reliable series in this database.

We use the Eurostat 1995 nomenclature of statistical territorial units, which is referred to as NUTS. The aim is to provide a single uniform breakdown of territorial units for the production of regional statistics for the EU. In this nomenclature, NUTS1 means European Community Regions while NUTS2 means Basic Administrative Units. For practical reasons to do with data availability and the implementation of regional policies, this nomenclature is based primarily on the institutional divisions currently in force in the Member States following “normative criteria”. Eurostat defines these criteria as follows: “Normative regions are the expression of political will; their limits are fixed according to the tasks allocated to the territorial communities, according to the size of population necessary to carry out these tasks efficiently and economically, and according to historical and cultural factors.” (Regio database, user’s guide, Methods and Nomenclatures, Eurostat 1999, p. 7). It excludes territorial units specific to certain fields of activity or functional units in favor of regional units of a general nature. The regional breakdown adopted by Eurostat appears therefore as one of the major shortcomings of the Regio database, which can have some impact on our spatial weight matrix and estimation results (scale problems).

We use the series E2GDP95 for EU15 and XE_GDP for new acceding and candidate countries based on ESA95 measured in PPS per inhabitant over the 1995–2000 period. We use per capita GDP expressed in PPS because it takes into account price levels variations between countries not reflected by prevailing exchange rates and because it is widely used as a key indicator for assessing levels of economic development in regions and disparities between them in cross-region international comparisons. In addition, the eligibility condition under Objective 1 of Structural Funds is also expressed in PPS and not in Euro. Using PPS allows a better understanding of the consequences of the enlargement process on the eligibility criteria.

The first sample contains 203 NUTS2 regions for EU15 and the second contains 258 NUTS2 regions for EU27: Belgium (11), Denmark (1), Germany (40), Greece (13), Spain (16), France (22), Ireland (2), Italy (20), Luxembourg (1), Netherlands (12), Austria (9), Portugal (5), Finland (6), Sweden (8), United Kingdom (37) for EU15 and Czech Republic (8), Estonia (1), Hungary (7), Lithuania (1), Latvia (1), Poland (16), Slovenia (1), Slovakia (4), Malta (1), Cyprus (1), for the new acceding countries and Romania (8), and Bulgaria (6) for candidate countries for EU27.

We exclude some geographically isolated regions in both of our samples: the Canary Islands and Ceuta y Mellila for Spain, the Azores and Madeira for Portugal, and Guadeloupe, Martinique, French Guyana and Réunion for France.

The choice of the NUTS2 level as our spatial scale of analysis may appear to be quite arbitrary and may have some impact on our inference results. Regions in NUTS2 level may be too large in respect to the variable of interest and the unobserved heterogeneity may create an ecological fallacy, so that it might have been more relevant to use NUTS3 level. In contrast, they may be too small so that the spatial autocorrelation detected could be an artifact that comes out from slicing homogenous zones in respect to the variable considered, so that it might have been more relevant to use NUTS1 level. Even if, ideally, the choice of the spatial scale should be based on theoretical considerations, we are constrained in empirical studies by data availability. Moreover, our preference for the NUTS2 level rather than the NUTS1 level, when data are available, is based on European regional development policy considerations: Indeed, it is the level at which eligibility under Objective 1 of Structural Funds is determined since their reform in 1989. Our empirical results are indeed conditioned by this choice and could be affected by different levels of aggregation and even by missing regions. Therefore, they must be interpreted with caution.

Appendix B

1.1 Getis–Ord statistics for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27

Code	Regions	EU15	EU27	EU15	EU27	EU15	EU27
Code	Regions	2000		1995		Growth rates
	Belgium
be1	Région Bruxelles-capitale	+	+*	+	+	−	−
be21	Antwerpen	+*	+*	+*	+*	−	−
be22	Limburg (B)	+*	+*	+*	+*	−	−
be23	Oost-Vlaanderen	+	+*	+	+*	−	−
be24	Vlaams Brabant	+*	+*	+	+*	−	−
be25	West-Vlaanderen	+	+*	+	+*	−	−
be31	Brabant Wallon	+	+*	+	+*	−*	−
be32	Hainaut (Objective 1)	+	+*	+	+*	−*	−
be33	Liège	+	+*	+	+*	−	−
be34	Luxembourg (B)	+*	+*	+	+*	−	−
be35	Namur	+	+*	+	+*	−*	−
	Denmark
Dk	Denmark	+*	+*	+	+*	−*	−
	Germany
de11	Stuttgart	+*	+**	+*	+*	−*	−
de12	Karlsruhe	+*	+*	+*	+*	−*	−
de13	Freiburg	+*	+**	+*	+*	−*	−
de14	Tübingen	+**	+**	+**	+**	−	−
de21	Oberbayern	+*	+**	+*	+**	−	−
de22	Niederbayern	+*	+	+*	+	−	−
de23	Oberpfalz	+	+	+	+	−	−*
de24	Oberfranken	+	+	+	+	−	−
de25	Mittelfranken	+*	+*	+*	+*	−	−
de26	Unterfranken	+*	+*	+*	+*	−	−
de27	Schwaben	+**	+**	+**	+**	−	−
de3	Berlin (Objective 1, East Berlin)	−*	−	−**	−	−	−
de4	Brandenburg (Objective 1)	−*	−	−**	−	−*	−*
de5	Bremen	+*	+*	+	+*	−**	−*
de6	Hamburg	+	+	+	+	−**	−
de71	Darmstadt	+*	+*	+	+*	−*	−
de72	Gießen	+*	+**	+*	+*	−*	−
de73	Kassel	+	+*	+	+*	−	−
de8	Mecklenburg-Vorpommern (Objective 1)	−	+	−	+	−*	−
de91	Braunschweig	+	+	+	+	−*	−
de92	Hannover	+*	+*	+	+*	−**	−*
de93	Lüneburg	+	+*	+	+*	−*	−
de94	Weser-Ems	+*	+*	+	+*	−	−
dea1	Düsseldorf	+	+	+	+	−*	−
dea2	Köln	+	+*	+	+	−*	−
dea3	Münster	+	+*	+	+*	−	−
dea4	Detmold	+*	+*	+	+*	−**	−*
dea5	Arnsberg	+*	+*	+	+*	−**	−*
deb1	Koblenz	+*	+**	+*	+*	−*	−
deb2	Trier	+	+*	+	+*	−*	−
deb3	Rheinhessen-Pfalz	+*	+*	+	+*	−**	−*
dec	Saarland	+	+*	+	+	−**	−
ded1	Chemnitz (Objective 1)	−	−	−	−	−**	−*
ded2	Dresden (Objective 1)	−	−	−*	−	−*	−**
ded3	Leipzig (Objective 1)	−	−	−*	−	−*	−*
dee1	Dessau (Objective 1)	−*	−	−*	−	−*	−*
dee2	Halle (Objective 1)	−	+	−	−	−	−
dee3	Magdeburg (Objective 1)	−	+	−	+	−**	−
def	Schleswig-Holstein	+	+*	+	+*	−*	−
deg	Thüringen (Objective 1)	−	+	−	+	−	−
	Greece
gr11	Anatoliki Makedonia, Thraki (Objective 1)	−**	−**	−**	−**	+*	−**
gr12	Kentriki Makedonia (Objective 1)	−**	−**	−**	−**	+	−*
gr13	Dytiki Makedonia (Objective 1)	−**	−*	−**	−*	+	−
gr14	Thessalia (Objective 1)	−**	−	−**	−	+	−
gr21	Ipeiros (Objective 1)	−**	−	−**	−	+	+
gr22	Ionia Nisia (Objective 1)	−**	−	−**	−	+*	+
gr23	Dytiki Ellada (Objective 1)	−**	−	−**	−	+*	+
gr24	Sterea Ellada (Objective 1)	−**	−*	−**	−	+*	+
gr25	Peloponnisos (Objective 1)	−**	−	−**	−	+	+
gr3	Attiki (Objective 1)	−**	−	−**	−	+	+
gr41	Voreio Aigaio (Objective 1)	−**	−*	−**	−*	+	−
gr42	Notio Aigaio (Objective 1)	−**	−*	−**	−*	+	−
gr43	Kriti (Objective 1)	−**	−	−**	−	+	+
	Spain
es11	Galicia (Objective 1)	−**	−	−*	−	+*	+
es12	Principado de Asturias (Objective 1)	−*	−	−*	+	+*	+
es13	Cantabria (Objective 1)	−	+	−	+	+	+
es21	Pais Vasco	−	+	−	+	+	+
es22	Comunidad Foral de Navarra	−	+	−	+	+	+
es23	La Rioja	−	+	−	+	+*	+
es24	Aragón	−	+	−	+	+	+
es3	Comunidad de Madrid	−*	−	−*	+	+*	+
es41	Castilla y León (Objective 1)	−*	+	−	+	+*	+
es42	Castilla-la Mancha (Objective 1)	−*	+	−	+	+*	+
es43	Extremadura (Objective 1)	−**	−	−**	−	+	+
es51	Cataluña	−	+	−	+	+	+
es52	Comunidad Valenciana (Objective 1)	−	+	−	+	+*	+
es53	Illes Balears	−	+	−	+	+	+
es61	Andalucia (Objective 1)	−**	−	−**	−	+	+
es62	Murcia (Objective 1)	−*	+	−	+	+*	+
	France
fr1	Île de France	−	+	−	+	−*	−
fr21	Champagne-Ardenne	+	+*	+	+	−*	−
fr22	Picardie	+*	+*	+	+*	−*	−
fr23	Haute-Normandie	+	+*	+	+*	+	+
fr24	Centre	+	+	−	+	−	−
fr25	Basse-Normandie	+	+	+	+*	+	+
fr26	Bourgogne	+	+	−	+	−*	−
fr3	Nord-Pas-de-Calais	+*	+**	+*	+*	−*	−
fr41	Lorraine	+	+*	+	+	−*	−
fr42	Alsace	+	+*	+	+*	−**	−*
fr43	Franche-Comté	+*	+*	+*	+*	−	−
fr51	Pays de la Loire	+	+	+	+	−	−
fr52	Bretagne	−	+	−	+	+	+
fr53	Poitou-Charentes	+	+	+	+	−	−
fr61	Aquitaine	−	+	−	+	+	+
fr62	Midi-Pyrénées	−	+	−	+	−	−
fr63	Limousin	+	+	+	+	−	−
fr71	Rhône-Alpes	+	+	+	+	−*	−
fr72	Auvergne	+	+	+	+	−	−
fr81	Languedoc-Roussillon	+	+	−	+	−	−
fr82	Provence-Alpes-Côte d'Azur	+	+*	+	+	−	−
fr83	Corse (Objective 1)	+*	+*	+*	+*	−	−
	Ireland
ie01	Border, Midlands and Western (Objective 1)	−	+	−	+	+	+
ie02	Southern and Eastern (Objective 1)	−	+	−	+	+	+
	Italy
it11	Piemonte	+*	+*	+*	+*	−	−
it12	Valle d’Aosta	+*	+*	+	+*	−	−
it13	Liguria	+**	+**	+**	+**	+	+
it2	Lombardia	+**	+**	+**	+**	+	+
it31	Trentino-Alto Adige	+**	+**	+**	+**	+	+
it32	Veneto	+**	+**	+**	+**	+	+
it33	Friuli-Venezia Giulia	+**	+*	+**	+*	+	+
it4	Emilia-Romagna	+*	+*	+*	+*	+	+
it51	Toscana	+*	+*	+*	+*	+	+
it52	Umbria	+	+*	+	+*	+	+
it53	Marche	+	+*	+	+*	+	+
it6	Lazio	−	+	+	+	+	+
it71	Abruzzo (Objective 1)	+	+	+	+	+	+
it72	Molise (Objective 1)	−	+	−	+	+	+
it8	Campania (Objective 1)	−	+	−	+	+	+
it91	Puglia (Objective 1)	−*	−	−*	+	+	+
it92	Basilicata (Objective 1)	−*	+	−	+	+	+
it93	Calabria (Objective 1)	−**	−	−**	−	+	+
ita	Sicilia (Objective 1)	−	−	−	+	+	+
itb	Sardegna (Objective 1)	+	+*	+	+*	+	+
	Luxembourg
lu	Luxembourg	+	+	−	+	−**	−*
	Netherlands
nl11	Groningen	+	+*	+	+*	−	−
nl12	Friesland	+	+*	+	+*	+	+
nl13	Drenthe	+	+*	+	+*	−	−
nl21	Overijssel	+	+*	+	+	−	−
nl22	Gelderland	+	+*	+	+*	+	+
nl23	Flevoland (Objective 1)	+	+*	+*	+*	+	+
nl31	Utrecht	+	+*	+	+*	+	+
nl32	Noord-Holland	+	+*	+	+*	+	+
nl33	Zuid-Holland	+**	+**	+**	+**	−	−
nl34	Zeeland	+*	+*	+	+*	−	−
nl41	Noord-Brabant	+*	+*	+*	+*	+	+
nl42	Limburg (NL)	+	+*	+	+*	−	−
	Austria
at11	Burgenland (Objective 1)	+	−	+*	−	+	+
at12	Niederösterreich	+	−	+	−	−	−
at13	Vienna	+	−	+	−	+	+
at21	Kärnten	+*	+*	+**	+*	+	+
at22	Steiermark	+*	+	+*	+	+	+
at31	Oberösterreich	+*	+	+*	+	+	−
at32	Salzburg	+*	+	+*	+	+	+
at33	Tirol	+**	+**	+**	+**	−	−
at34	Vorarlberg	+**	+**	+**	+**	−	−
	Portugal
pt11	Norte (Objective 1)	−**	−	−**	−	+	+
pt12	Centro (PT) (Objective 1)	−**	−	−**	−	+	+
pt13	Lisboa e Vale do Tejo (Objective 1)	−**	−	−**	−	+	+
pt14	Alentejo (Objective 1)	−**	−	−**	−	+	+
pt15	Algarve (Objective 1)	−**	−	−**	−	+	+
	Finland
fi13	Itä-Suomi	+	−	+	−	+	+**
fi14	Väli-Suomi	+	−	+	+	+	+**
fi15	Pohjois-Suomi	+	+	+	+	+	+*
fi16	Uusimaa (suuralue)	+	−	+	−	+	+**
fi17	Etelä-Suomi	+	−	+	−	+	+**
fi2	Åland	+	+	+	+	−	+
	Sweden
se01	Stockholm	+	−	+	−	−	+
se02	Östra Mellansverige	+	−	+	+	−*	+
se04	Sydsverige	−	−	−	−	−*	−
se06	Norra Mellansverige	+	+	+	+	−	+
se07	Mellersta Norrland	+	+	+	+	−	+
se08	Övre Norrland	+	+*	+	+*	+	+
se09	Småland med öarna	+	−	+	−	−	+*
se0a	Västsverige	+	+	+	+	−**	−
	United Kingdom
ukc1	Tees Valley and Durham	−	+	−	+	+	+
ukc2	Northumberland, Tyne and Wear	−	+	−	+	−	−
ukd1	Cumbria	−	+	−	+	−	+
ukd2	Cheshire	−	+	−	+	+	+
ukd3	Greater Manchester	−	+	−	+	+	+
ukd4	Lancashire	−	+	−	+	+	+
ukd5	Merseyside (Objective 1)	−	+	−	+	+	+
uke1	East Riding and North Lincolnshire	−	+	−	+	+	+
uke2	North Yorkshire	−	+	−	+	+	+
uke3	South Yorkshire	−	+	−	+	+	+
uke4	West Yorkshire	−	+	−	+	+	+
ukf1	Derbyshire and Nottinghamshire	−	+	−	+	+	+
ukf2	Leicestershire, Rutland and Northants	+	+	+	+*	+*	+
ukf3	Lincolnshire	+	+	+	+	+**	+*
ukg1	Herefordshire, Worcestershire and Warks	+	+	+	+	+	+
ukg2	Shropshire and Staffordshire	−	+	−	+	+	+
ukg3	West Midlands	+	+	+	+	+*	+
ukh1	East Anglia	+	+*	+	+*	+**	+*
ukh2	Bedfordshire, Hertfordshire	+	+*	+*	+*	+**	+*
ukh3	Essex	+	+*	+*	+*	+**	+*
uki1	Inner London	+	+	+	+*	+**	+*
uki2	Outer London	+	+*	+*	+*	+**	+*
ukj1	Berkshire, Bucks and Oxfordshire	+	+*	+*	+*	+**	+*
ukj2	Surrey, East and West Sussex	+	+*	+*	+*	+**	+*
ukj3	Hampshire and Isle of Wight	+	+*	+*	+*	+**	+
ukj4	Kent	+	+*	+*	+*	+**	+*
ukk1	Gloucestershire, Wiltshire and North Somerset	+	+	+	+	+*	+
ukk2	Dorset and Somerset	−	+	−	+	+*	+
ukk3	Cornwall and Isles of Scilly	−	+	−	+	+	+
ukk4	Devon	−	+	−	+	+	+
ukl1	West Wales and The Valleys	−	+	−	+	+	+
ukl2	East Wales	−	+	−	+	+	+
ukm1	North Eastern Scotland	−	+	−	+	−	−
ukm2	Eastern Scotland	−	+	−	+	−	−
ukm3	South Western Scotland	−	+	−	+	−	−
ukm4	Highlands and Islands (Objective 1)	−	+	−	+	−	−
ukn	Northern Ireland (Objective 1)	−	+	−	+	+	+

*Significant at the 5% significance level based on normal approximation

**Significant at the 5% Sidàk pseudo-significance level

Objective 1 Eligible regions which have benefited from Objective 1 Structural Funds throughout the 1995–2000 period taking into account NUTS modifications

Appendix C

1.1 LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27

Code	Regions	EU15	EU27	EU15	EU27	EU15	EU27
Code	Regions	2000		1995		Growth rates
	Belgium
be1	Région Bruxelles-capitale	HH	HH*	HH	HH*	LL*	LL
be21	Antwerpen	HH*	HH**	HH*	HH**	LL	LL
be22	Limburg (B)	HH*	HH**	LH*	HH**	LL	LL
be23	Oost-Vlaanderen	HH*	HH**	HH	HH*	LL*	LL
be24	Vlaams Brabant	HH*	HH**	HH	HH*	HL*	HL
be25	West-Vlaanderen	HH*	HH**	HH	HH*	LL*	LL
be31	Brabant Wallon	HH*	HH**	HH	HH*	HL**	HL*
be32	Hainaut (Objective 1)	LH*	LH**	LH	LH*	LL*	LL*
be33	Liège	LH	HH*	LH	HH*	LL	LL
be34	Luxembourg (B)	LH*	HH**	LH*	HH**	LL	LL
be35	Namur	LH*	HH**	LH	LH*	LL*	LL
	Denmark
dk	Denmark	HH*	HH**	HH	HH*	HL**	HL*
	Germany
de11	Stuttgart	HH**	HH**	HH*	HH**	HL*	HL
de12	Karlsruhe	HH*	HH**	HH*	HH**	LL*	LL
de13	Freiburg	HH**	HH**	HH*	HH**	LL*	LL
de14	Tübingen	HH**	HH**	HH**	HH**	LL	LL
de21	Oberbayern	HH**	HH**	HH*	HH**	HL	HL
de22	Niederbayern	HH*	HH	HH*	HH	LL	LL
de23	Oberpfalz	HH	HH	HH	HH	HL	HL*
de24	Oberfranken	HH	HH*	HH	HH*	LL	LL
de25	Mittelfranken	HH*	HH**	HH*	HH**	LL	LL
de26	Unterfranken	HH*	HH**	HH*	HH**	LL*	LL
de27	Schwaben	HH**	HH**	HH**	HH**	LL	LL
de3	Berlin (Objective 1, East Berlin)	HL**	HL	HL**	HL	LL*	LL
de4	Brandenburg (Objective 1)	LL*	LL	LL**	LL	LL*	LL*
de5	Bremen	HH*	HH**	HH	HH*	LL**	LL*
de6	Hamburg	HH	HH*	HH	HH	LL**	LL*
de71	Darmstadt	HH*	HH**	HH*	HH*	LL*	LL
de72	Gießen	HH**	HH**	HH*	HH**	LL*	LL
de73	Kassel	HH*	HH*	HH	HH*	LL*	LL
de8	Mecklenburg-Vorpommern (Objective 1)	LL	LH	LL	LH	LL**	LL*
de91	Braunschweig	HH	HH*	HH	HH*	HL*	HL
de92	Hannover	HH*	HH**	HH*	HH*	LL**	LL*
de93	Lüneburg	LH*	HH*	LH	HH*	LL*	LL
de94	Weser-Ems	HH*	HH**	LH*	HH*	LL*	LL
dea1	Düsseldorf	HH	HH*	HH	HH	LL*	LL
dea2	Köln	HH	HH*	HH	HH*	LL*	LL
dea3	Münster	HH*	HH**	LH	HH*	LL*	LL
dea4	Detmold	HH*	HH**	HH	HH*	LL**	LL*
dea5	Arnsberg	HH*	HH**	HH*	HH**	LL**	LL*
deb1	Koblenz	HH**	HH**	LH*	HH**	LL*	LL
deb2	Trier	LH*	HH**	LH	HH*	LL*	LL
deb3	Rheinhessen-Pfalz	HH*	HH**	HH	HH*	LL**	LL*
dec	Saarland	HH	HH*	HH	HH*	LL**	LL*
ded1	Chemnitz (Objective 1)	LL	LL	LL*	LL	LL**	LL*
ded2	Dresden (Objective 1)	LL*	LL	LL*	LL	LL*	LL**
ded3	Leipzig (Objective 1)	LL*	HL	LL*	LL	LL*	LL*
dee1	Dessau (Objective 1)	LL*	LL	LL**	LL	LL**	LL*
dee2	Halle (Objective 1)	LL	LH	LL*	LL	LL	LL
dee3	Magdeburg (Objective 1)	LL	LH	LL	LH	HL**	HL*
def	Schleswig-Holstein	HH*	HH*	HH	HH*	LL*	LL
deg	Thüringen (Objective 1)	LL	LH	LL	LH	HL	HL
	Greece
gr11	Anatoliki Makedonia, Thraki (Objective 1)	LL**	LL**	LL**	LL**	LH*	LL**
gr12	Kentriki Makedonia (Objective 1)	LL**	LL**	LL**	LL**	HH*	HL*
gr13	Dytiki Makedonia (Objective 1)	LL**	LL*	LL**	LL*	HH	HL
gr14	Thessalia (Objective 1)	LL**	LL*	LL**	LL*	HH	HL
gr21	Ipeiros (Objective 1)	LL**	LL	LL**	LL	HH	HH
gr22	Ionia Nisia (Objective 1)	LL**	LL	LL**	LL	HH*	HH
gr23	Dytiki Ellada (Objective 1)	LL**	LL*	LL**	LL	LH*	LH
gr24	Sterea Ellada (Objective 1)	LL**	HL*	LL**	HL	LH*	LH*
gr25	Peloponnisos (Objective 1)	LL**	LL	LL**	LL	HH	HH
gr3	Attiki (Objective 1)	LL**	LL*	LL**	LL	LH*	LH
gr41	Voreio Aigaio (Objective 1)	LL**	LL*	LL**	LL*	HH	HL*
gr42	Notio Aigaio (Objective 1)	LL**	LL*	LL**	HL*	HH	HL
gr43	Kriti (Objective 1)	LL**	LL	LL**	LL	HH*	HH
	Spain
es11	Galicia (Objective 1)	LL**	LL	LL**	LL	HH*	HH
es12	Principado de Asturias (Objective 1)	LL**	LL	LL*	LH	HH*	HH
es13	Cantabria (Objective 1)	LL	LH	LL	HH	HH	HH
es21	Pais Vasco	HL	HH	HL	HH	HH	HH
es22	Comunidad Foral de Navarra	HL	HH	HL	HH	HH	HH
es23	La Rioja	LL	HH	LL	HH	HH*	HH
es24	Aragón	LL	HH	LL	HH	HH*	HH
es3	Comunidad de Madrid	HL**	HL	HL*	HH	HH*	HH
es41	Castilla y León (Objective 1)	LL*	LH	LL*	LH	HH*	HH*
es42	Castilla-la Mancha (Objective 1)	LL*	LH	LL*	LH	HH*	HH*
es43	Extremadura (Objective 1)	LL**	LL	LL**	LL	HH	HH
es51	Cataluña	HL	HH	HL	HH	HH	HH
es52	Comunidad Valenciana (Objective 1)	LL	LH	LL	HH	HH*	HH
es53	Illes Balears	HL	HH	HL	HH	HH	HH
es61	Andalucia (Objective 1)	LL**	LL	LL**	LL	HH*	HH
es62	Murcia (Objective 1)	LL*	LH	LL*	LH	HH*	HH
	France
fr1	Île de France	HL	HH	HL	HH	LL**	LL*
fr21	Champagne-Ardenne	HH	HH*	HH	HH*	LL*	LL
fr22	Picardie	LH*	HH**	LH	HH*	LL*	LL
fr23	Haute-Normandie	HH	HH*	HH	HH*	LH	LH
fr24	Centre	HH	HH	LL	HH	LL*	LL
fr25	Basse-Normandie	LH	HH*	LH	HH*	LH	LH
fr26	Bourgogne	HH	HH*	LL	HH	LL**	LL*
fr3	Nord-Pas-de-Calais	LH**	HH**	LH*	HH**	LL*	LL
fr41	Lorraine	LH	HH*	LH	HH*	LL**	LL*
fr42	Alsace	HH*	HH**	HH	HH*	LL**	LL*
fr43	Franche-Comté	LH*	HH**	LH*	HH**	LL	LL
fr51	Pays de la Loire	LH	HH*	LH	HH*	LL	LL
fr52	Bretagne	LL	HH	LL	HH	LH	LH
fr53	Poitou-Charentes	LH	HH*	LH	HH	LL*	LL
fr61	Aquitaine	HL	HH	LL	HH	LH	LH
fr62	Midi-Pyrénées	LL	HH	LL	HH	LL	LL
fr63	Limousin	LH	HH	LH	HH	LL	LL
fr71	Rhône-Alpes	HH	HH*	HH	HH	LL*	LL
fr72	Auvergne	LH	HH*	LH	HH	LL*	LL
fr81	Languedoc-Roussillon	LH	HH	LL	HH	LL	LL
fr82	Provence-Alpes-Côte d'Azur	HH	HH*	LH	HH*	LL	LL
fr83	Corse (Objective 1)	LH*	HH**	LH*	HH**	LL	LL
	Ireland
ie01	Border, Midlands and Western (Objective 1)	LL	LH	LL	HH	HH	HH
ie02	Southern and Eastern (Objective 1)	HL	HH	HL	HH	HH	HH
	Italy
it11	Piemonte	HH*	HH**	HH*	HH**	HL	HL
it12	Valle d’Aosta	HH*	HH**	HH*	HH**	LL	LL
it13	Liguria	HH**	HH**	HH**	HH**	HH	HH
it2	Lombardia	HH**	HH**	HH**	HH**	HH	HH
it31	Trentino-Alto Adige	HH**	HH**	HH**	HH**	HH	HH
it32	Veneto	HH**	HH**	HH**	HH**	HH	HH
it33	Friuli-Venezia Giulia	HH**	HH**	HH**	HH**	LH	LH
it4	Emilia-Romagna	HH*	HH**	HH*	HH**	HH	HH
it51	Toscana	HH*	HH**	HH*	HH**	HH	HH
it52	Umbria	HH	HH*	HH	HH*	HH	HH
it53	Marche	HH	HH*	HH*	HH*	HH	HH
it6	Lazio	HL	HH	HH	HH	HH	HH
it71	Abruzzo (Objective 1)	LH	HH	LH	HH*	LH	LH
it72	Molise (Objective 1)	LL	HH	LL	HH	HH	HH
it8	Campania (Objective 1)	LL	LH	LL	LH	HH	HH
it91	Puglia (Objective 1)	LL*	LL	LL*	LH	HH	HH
it92	Basilicata (Objective 1)	LL*	LH	LL*	LH	HH	HH
it93	Calabria (Objective 1)	LL**	LL	LL**	LL	HH*	HH
ita	Sicilia (Objective 1)	LL*	LL	LL	LH	HH	HH
itb	Sardegna (Objective 1)	LH	LH*	LH	HH*	HH	HH
	Luxembourg
lu	Luxembourg	HH	HH	HL	HH	HL**	HL*
	Netherlands
nl11	Groningen	HH	HH*	HH	HH*	LL	LL
nl12	Friesland	LH*	HH**	HH*	HH**	HH	HH
nl13	Drenthe	LH*	HH*	LH	HH*	LL	LL
nl21	Overijssel	HH	HH*	HH	HH*	HL	HL
nl22	Gelderland	HH	HH*	HH	HH*	HH	HH
nl23	Flevoland (Objective 1)	LH*	HH*	LH*	HH**	HH	HH
nl31	Utrecht	HH	HH*	HH	HH*	HH	HH
nl32	Noord-Holland	HH	HH*	HH	HH*	HH	HH
nl33	Zuid-Holland	HH**	HH**	HH**	HH**	HL	HL
nl34	Zeeland	HH*	HH**	HH*	HH**	LL	LL
nl41	Noord-Brabant	HH*	HH**	HH**	HH**	HH	HH
nl42	Limburg (NL)	HH*	HH**	HH	HH*	HL	HL
	Austria
at11	Burgenland (Objective 1)	LH*	LL	LH*	LL	HH	HH*
at12	Niederösterreich	LH	HL	HH	HL	HL	HL
at13	Vienna	HL	HL	HH	HL	LH	LH
at21	Kärnten	HH*	HH*	HH**	HH**	HH	HH
at22	Steiermark	LH*	HH	HH*	HH	HH	HH
at31	Oberösterreich	HH*	HH	HH*	HH	HH	HL
at32	Salzburg	HH*	HH*	HH*	HH*	HH	HH
at33	Tirol	HH**	HH**	HH**	HH**	HL	HL
at34	Vorarlberg	HH**	HH**	HH**	HH**	HL	HL
	Portugal
pt11	Norte (Objective 1)	LL**	LL	LL**	LL	HH*	HH
pt12	Centro (PT) (Objective 1)	LL**	LL	LL**	LL	LH*	LH
pt13	Lisboa e Vale do Tejo (Objective 1)	HL**	HL	HL**	HL	HH	HH
pt14	Alentejo (Objective 1)	LL**	LL	LL**	LL	LH*	LH
pt15	Algarve (Objective 1)	LL**	LL	LL**	LL	LH*	LH
	Finland
fi13	Itä-Suomi	LH	LL	LH	LL	LH	LH**
fi14	Väli-Suomi	LH	HL	LH	HH	HH	HH**
fi15	Pohjois-Suomi	LH	HH	LH	HH	HH	HH*
fi16	Uusimaa (suuralue)	HH	HL*	HH	HL	HH	HH**
fi17	Etelä-Suomi	LH	HL	HH	HL	HH	HH**
fi2	Åland	HH	HH	HH	HH	HL	HH
	Sweden
se01	Stockholm	HH	HL	HH	HL	HL	HH
se02	Östra Mellansverige	HH	HL	LH	HH	LL*	LH
se04	Sydsverige	HL	HL	HL*	HL	LL**	LL
se06	Norra Mellansverige	HH	HH	LH	HH	LL	LH
se07	Mellersta Norrland	HH	HH	HH	HH	LL	LH
se08	Övre Norrland	HH	HH*	LH	HH*	LH	LH
se09	Småland med öarna	HH	HL	HH	HL	LL*	LH*
se0a	Västsverige	HH	HH	HH	HH	LL**	LL
	United Kingdom
ukc1	Tees Valley and Durham	LL	HH	LL	LH	LH	LH
ukc2	Northumberland, Tyne and Wear	LL	HH	LL	HH	LL	LL
ukd1	Cumbria	HL	HH	LL	HH	LL	LH
ukd2	Cheshire	HL	HH	HL	HH	HH	HH
ukd3	Greater Manchester	LL	HH	LL	HH	HH	HH
ukd4	Lancashire	LL	HH	LL	HH	LH	LH
ukd5	Merseyside (Objective 1)	LL	LH	LL	LH	HH	HH
uke1	East Riding and North Lincolnshire	LL	HH	HL	HH	HH*	HH
uke2	North Yorkshire	LL	HH	HL	HH	HH	HH
uke3	South Yorkshire	LL	LH	LL	LH	HH	HH
uke4	West Yorkshire	LL	HH	LL	HH	HH	HH
ukf1	Derbyshire and Nottinghamshire	LL	HH	LL	HH	HH*	HH
ukf2	Leicestershire, Rutland and Northants	HH	HH*	HH	HH*	HH*	HH*
ukf3	Lincolnshire	LH	HH	LH	HH*	HH**	HH*
ukg1	Herefordshire, Worcestershire and Warks	HH	HH	HH	HH*	HH	HH
ukg2	Shropshire and Staffordshire	LL	HH	LL	HH	HH	HH
ukg3	West Midlands	HH	HH	HH	HH*	LH*	LH
ukh1	East Anglia	HH	HH*	HH*	HH**	HH**	HH*
ukh2	Bedfordshire, Hertfordshire	HH	HH*	HH*	HH**	HH**	HH*
ukh3	Essex	LH	HH*	HH*	HH**	HH**	HH*
uki1	Inner London	HH	HH*	HH	HH*	HH**	HH*
uki2	Outer London	LH	HH*	LH*	HH**	HH**	HH*
ukj1	Berkshire, Bucks and Oxfordshire	HH	HH*	HH*	HH**	HH**	HH*
ukj2	Surrey, East and West Sussex	HH	HH*	HH*	HH**	HH**	HH*
ukj3	Hampshire and Isle of Wight	HH	HH*	HH*	HH**	HH**	HH*
ukj4	Kent	LH	HH**	HH*	HH**	HH**	HH*
ukk1	Gloucestershire, Wiltshire and North Somerset	HH	HH	HH	HH*	HH*	HH
ukk2	Dorset and Somerset	LL	HH	LL	HH	HH*	HH
ukk3	Cornwall and Isles of Scilly	LL	LH	LL	LH	HH	HH
ukk4	Devon	LL	HH	LL	HH	LH*	LH
ukl1	West Wales and The Valleys	LL	LH	LL	LH	HH	HH
ukl2	East Wales	HL	HH	HL	HH	LH	LH
ukm1	North Eastern Scotland	HL	HH	HL	HH	LL	LL
ukm2	Eastern Scotland	HL	HH	HL	HH	LL	LL
ukm3	South Western Scotland	LL	HH	LL	HH	LL	LL
ukm4	Highlands and Islands (Objective 1)	LL	HH	LL	LH	LL	LL
ukn	Northern Ireland (Objective 1)	LL	HH	LL	HH	LH	LH

*Significant at the 5% significance level based on normal approximation
**Significant at the 5% Sidàk pseudo-significance level
Objective 1 Eligible Regions which have benefited from Objective 1 of Structural Funds throughout the 1995–2000 period taking into account NUTS modifications

Appendix D

1.1 Getis–Ord statistics and LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for new acceding and candidate countries

Code	Regions	2000		1995		Growth rates
Code	Regions	Gi	LISA	Gi	LISA	Gi	LISA
	Cyprus
cy	Cyprus	−**	HL**	−**	HL**	−*	LL**
	Czech Republic
cz01	Praha	−	HL*	−	HL	−*	HL*
cz02	Strední Cechy	−	LL	+	LH	−*	LL*
cz03	Jihozápad	+	LH	+	LH	−	LL
cz04	Severozápad	−	LL	−	LL	−	LL
cz05	Severovýchod	−	LL	−	LL	−	LL
cz06	Jihovýchod	−	LL	−	LL	−	LL
cz07	Strední Morava	−*	LL*	−*	LL*	−	LL
cz08	Moravskoslezko	−**	LL**	−**	LL**	+	LH
	Estonia
ee	Estonia	−	LL	−	LL*	+**	HH**
	Hungary
hu01	Közép-Magyarország	−**	HL**	−**	LL**	+	HH
hu02	Közép-Dunántúl	−	LL*	−*	LL*	+	HH
hu03	Nyugat-Dunántúl	−	LL	−	LL	+	HH
hu04	Dél-Dunántúl	−	LL	−	LL	+*	HH*
hu05	Észak-Magyarország	−**	LL**	−**	LL**	+*	HH**
hu06	Észak-Alföld	−**	LL**	−**	LL**	+	LH
hu07	Dél-Alföld	−**	LL**	−**	LL**	+	LH*
	Lithuania
lt	Lithuania	−**	LL**	−**	LL**	+**	HH**
	Latvia
lv	Latvia	−*	LL*	−**	LL**	+**	HH**
	Malta
mt	Malta	−	LL	−	LL	+	HH
	Poland
pl01	Dolnoslaskie	−**	LL**	−*	LL*	−	HL
pl02	Kujawsko-Pomorskie	−**	LL**	−**	LL**	+**	HH**
pl03	Lubelskie	−**	LL**	−**	LL**	+**	HH**
pl04	Lubuskie	−*	LL*	−	LL*	−	HL
pl05	Lódzkie	−**	LL**	−**	LL**	+*	HH*
pl06	Malopolskie	−**	LL**	−**	LL**	+	HH
pl07	Mazowieckie	−**	LL**	−**	LL**	+**	HH**
pl08	Opolskie	−**	LL**	−**	LL**	−	LL
pl09	Podkarpackie	−**	LL**	−**	LL**	+*	HH*
pl0a	Podlaskie	−**	LL**	−**	LL**	+**	HH**
pl0b	Pomorskie	−**	LL**	−**	LL**	+**	HH**
pl0c	Slaskie	−**	LL**	−**	LL**	+	HH
pl0d	Swietokrzyskie	−**	LL**	−**	LL**	+**	HH**
pl0e	Warminsko-Mazurskie	−**	LL**	−**	LL**	+**	HH**
pl0f	Wielkopolskie	−**	LL**	−**	LL**	+	HH
pl0g	Zachodniopomorskie	−*	LL*	−*	LL*	+	HH
	Slovenia
si	Slovenia	+	LH	+	LH	+	HH*
	Slovakia
sk01	Bratislavský	−	HL*	−	HL*	−	HL
sk02	Západné Slovensko	−	LL	−	LL	+	HH
sk03	Stredné Slovensko	−**	LL**	−**	LL**	+	HH
sk04	Východné Slovensko	−**	LL**	−**	LL**	+	HH
	Bulgaria
bg01	Severozapaden	−**	LL**	−**	LL**	−**	LL**
bg02	Severen Tsentralen	−**	LL**	−**	LL**	−**	LL**
bg03	Severoiztochen	−**	LL**	−**	LL**	−**	LL**
bg04	Yugozapaden	−**	LL**	−**	LL**	−**	LL**
bg05	Yuzhen Tsentralen	−**	LL**	−**	LL**	−**	LL**
bg06	Yugoiztochen	−**	LL**	−**	LL**	−**	LL**
	Roumania
ro01	Nord-Est	−**	LL**	−**	LL**	−**	LL**
ro02	Sud-Est	−**	LL**	−**	LL**	−**	LL**
ro03	Sud	−**	LL**	−**	LL**	−**	LL**
ro04	Sud-Vest	−**	LL**	−**	LL**	−**	LL**
ro05	Vest	−**	LL**	−**	LL**	−*	LL**
ro06	Nord-Vest	−**	LL**	−**	LL**	−*	LL*
ro07	Centru	−**	LL**	−**	LL**	−**	LL**
ro08	Bucuresti	−**	LL**	−**	LL**	−**	LL**

*Significant at the 5% significance level based on the normal approximation for Getis–Ord statistics and on 10,000 permutations for LISA
**Significant at the 5% Sidàk pseudo-significance level for Getis–Ord statistics and at the 5% Bonferroni pseudo-significance level for LISA

Appendix E

1.1 LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27, using Bonferroni pseudo-significance level

Significant LISA at the Bonferroni 5% pseudo-significance level for log per capita GDP (PPS) for 1995 and 2000, EU15

Years	Percentage of significant statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant HH statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant LL statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant LH statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant HL statistics at the 5% Bonferroni pseudo-significance level
2000	18.23%	5.91%	11.33%	0.00%	0.99%
1995	20.20%	7.39%	10.84%	0.49%	1.48%

Significant LISA at the Bonferroni 5% pseudo-significance level for log per capita GDP (PPS) for 1995 and 2000, EU27

Years	Percentage of significant statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant HH statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant LL statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant LH statistics at the 5% Bonferroni pseudo-significance level	Percentage of significant HL statistics at the 5% Bonferroni pseudo-significance level
2000	31.40%	16.28%	14.34%	0.00%	0.78%
1995	34.88%	19.38%	14.73%	0.39%	0.39%

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Ertur, C., Koch, W. Regional disparities in the European Union and the enlargement process: an exploratory spatial data analysis, 1995–2000. Ann Reg Sci 40, 723–765 (2006). https://doi.org/10.1007/s00168-006-0062-x

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Received: 01 September 2004
Accepted: 07 September 2005
Published: 07 April 2006
Issue Date: December 2006
DOI: https://doi.org/10.1007/s00168-006-0062-x

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Regional disparities in the European Union and the enlargement process: an exploratory spatial data analysis, 1995–2000

Abstract

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Regional Dynamics in EU11

Regional Inequalities in Central and Eastern European Countries: The Role of Capital Regions and Metropolitan Areas

The Impact of Structural Funds on Regional Growth: A Panel Data Spatial Analysis

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Appendices

Appendix A

1.1 Eurostat-Regio database

Appendix B

1.1 Getis–Ord statistics for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27

Appendix C

1.1 LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27

Appendix D

1.1 Getis–Ord statistics and LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for new acceding and candidate countries

Appendix E

1.1 LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27, using Bonferroni pseudo-significance level

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Regional disparities in the European Union and the enlargement process: an exploratory spatial data analysis, 1995–2000

Abstract

Access this article

Similar content being viewed by others

Regional Dynamics in EU11

Regional Inequalities in Central and Eastern European Countries: The Role of Capital Regions and Metropolitan Areas

The Impact of Structural Funds on Regional Growth: A Panel Data Spatial Analysis

Notes

References

Acknowledgements

Author information

Authors and Affiliations

Corresponding author

Additional information

Appendices

Appendix A

1.1 Eurostat-Regio database

Appendix B

1.1 Getis–Ord statistics for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27

Appendix C

1.1 LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27

Appendix D

1.1 Getis–Ord statistics and LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for new acceding and candidate countries

Appendix E

1.1 LISA for log per capita GDP measured in PPS and average annual growth rates, 1995 and 2000 for EU15 and EU27, using Bonferroni pseudo-significance level

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