Southern Europe: A regional view
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The document provides an analysis of regional economic performance in Southern Europe, focusing on the contribution of metropolitan areas to national GDP and their growth trends from 2000 to 2016. It identifies varying productivity growth rates among urban and rural regions, highlighting the challenges and opportunities posed by different economic models across countries. Additionally, it notes regional disparities in employment, education, and access to public services, emphasizing the need for effective governance and strategies to improve regional economic outcomes.
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Southern Europe: A regional view
- 1. Southern Europe – A Regional View Head of Economic Analysis, Statistics and Multi-level Governance Centre for Entrepreneurship, SMEs, Regions and Cities Rudiger Ahrend Brussels, 16 October 2018
- 2. The contribution of capital city regions to national GDP, TL2 regions 0 5 10 15 20 25 30 35 40 45 50 USA AUS DEU ITA NZL MEX BEL ESP NLD POL GBR CZE AUT NOR SVK FRA SWE JPN PRT FIN CAN DNK CHL HUN GRC KOR 2016 2000 %
- 3. Importance of metropolitan areas 39% 33% 61% 60% 0 10 20 30 40 50 60 70 80 % of national GDP % of national population Italy OECD averageItaly OECD averageItaly OECD average% 56% 43% 61% 60% 0 10 20 30 40 50 60 70 80 % of national GDP % of national population Greece OECD average 48% 37% 41% 61% 60% 54% 0 10 20 30 40 50 60 70 80 % of national GDP % of national employment % of national population Portugal OECD average % 49% 46% 42% 61% 60% 54% 0 10 20 30 40 50 60 70 80 % of national GDP % of national employment % of national population Spain OECD average %
- 4. Firm creation rates by country and type of region, 2015 3 5 7 9 11 13 15 17 19 21 23 AUT CZE DNK ESP EST FIN FRA GBR HUN ITA LVA NOR PRT SVK OECD14 Predominantlyrural Intermediate Predominantlyurban %
- 5. Annual GDP growth in metropolitan areas, 2000-16 Ordered by the highest to lowest difference between the metropolitan areas and the rest of the country -1 0 1 2 3 4 5%
- 6. GDP growth in metropolitan areas, 2000-16 0.31% per year -0.54% per year -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 % Greek metropolitan areas Rest of the country -0.18% per year -0.29% per year -0.5 -0.4 -0.3 -0.2 -0.1 0.0% Italian metropolitan areas Rest of the country 1.5% per year 1.22% per year 0.0 0.5 1.0 1.5 2.0 % Spanish metropolitan areas Rest of the country 0.02% per year 0.39% per year 0.0 0.1 0.2 0.3 0.4 0.5 0.6 % Portuguese metropolitan areas Rest of the country
- 7. 7 Space matters: proximity to cities benefits surrounding rural & intermediate regions Source: Ahrend and Schumann (2014) “Does regional economic growth
- 8. Where do productivity gain occur? Proximity to cities and exposure to international competition matter In 2/3 of countries, the productivity gap between top and bottom 10% has narrowed since 2010. Rural regions close to cities have narrowed the gap with urban regions by 3 percentage points since 2010. Regions with a higher specialization in the tradable sector – implying higher exposure to international competition showed a higher growth in productivity Rural close to cities Rural remote Rural total 75 76 77 78 79 80 81 82 83 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Productivity level of Predominantly Urban regions=100 % Productivity growth in rural regions, 2000-15 (TL3)
- 9. Drivers of Regional Productivity
- 10. Convergence in per capita GDP and labour productivity in the OECD/EU between 2000 and 2014 Frontier regions • most productive regions accounting for 10% of total employment Catching up/Diverging • Productivity growth is 5% higher/lower than in the frontier over a 13 year period 10 Source:OECD(2018)ProductivityandJobsinaGlobalisedWorld:(How)CanAllRegionsBenefit? Challenge? Productivity gaps have narrowed in the EU and the OECD
- 11. 11 But: Gaps within some countries are widening Source:OECD(2018)ProductivityandJobsinaGlobalisedWorld:(How)CanAllRegionsBenefit? Countries follow two growth models Distributed growth model: Catching up supports productivity growth • AUT, CZE, DEU, ESP, ITA, POL, PRT, ROU Concentrated growth model: The “frontier” dominates growth • BGR, DNK, FIN, FRA, GBR, GRC, HUN, NLD, SVK, SWE
- 12. Annual productivity growth 2010-16, TL2 regions SouthandEast C.Anatolia-W.S. OsloRegion Šiauliaicounty GreaterPoland N.Territory East CentralBohemia Aguascalientes Gangwon Manitoba East Canterbury Stockholm Catalonia Flevoland NorthEstonia Zealand Brittany Thuringia Wales Zurich Centro FlemishRegion C.Transdanubia NorthDakota Vorarlberg South Bolzano-Bozen Thessaly - 5 - 3 - 1 1 3 5 7 9 Minimum Country average Maximum % -12
- 13. Spatial productivity differences within the same region, 2000-15 0 10 20 30 40 50 60 70 80 90 2015 2000% Country (number ofTL2 regions)
- 14. Annual average GVA growth, 2000-13 Percentage of total GVA (right axis), 2013 -20 -10 0 10 20 30 40 50 60 70 80 -1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 Tradable services Industry Agriculture Non-tradable services %% -20 -10 0 10 20 30 40 50 60 70 80 -1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 Tradable services Industry Agriculture Non-tradable services %% -20 -10 0 10 20 30 40 50 60 70 80 -1 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 Tradable services Industry Agriculture Non-tradable services %% Goods ? 14 The nature of tradable sectors is changing … but not in all parts of Europe EU low-growth regions EU low-income regions Other European regions Tradable services Low-income: <50% of EU-average per capita GDP; low-growth: <90% per capita GDP and below average growth Source : OECD (2018) Productivity and Jobs in a Globalised World: (How) Can All Regions Benefit?
- 15. Regions with strong pre-crisis increases in non-tradable sectors lost more jobs 15 Calculations based on 208 OECD TL2 regions. Those regions with the largest shifts towards non-tradable sectors suffered higher employment losses, on average, following the 2007-08 crisis. -3.5 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 Less than 2.5 percentage points increase 2.5 to 5 percentage points 5 to 7.5 percentage points More than 7.5 percentage points increase Change in the share of non-tradable employment, 2000-07 Employment growth (%), 2008-14 Source:OECD(2018)ProductivityandJobsinaGlobalisedWorld: (How)CanAllRegionsBenefit?
- 16. Annual productivity growth in tradable and non-tradable sectors, 2010-15 Productivity growth in TL2 regions that are more or less concentrated on tradable sectors than the national average -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 IRL POL USA GBR ESP PRT ITA CZE AUT NLD AUS BEL FIN SWE CAN SVK Regionsconcentrated on non-tradables Regions concentrated on tradables%
- 17. 17 GVC integration and vertical specialisation
- 18. Selected features of Southern European OECD Countries
- 19. Expenditure on R&D in regions (TL2), 2015 Seoul EastMiddle Styria Copenhagen Baden-Württemberg Helsinki-Uusimaa NewMexico FlemishRegion West N.Brabant Trøndelag Prague CanberraRegionACT E.ofEngland Quebec Central Piedmont LisbonMetropolitan BasqueCountry Border,Midland,W. Bratislava Mazovia Crete SouthWest Bucharest-Ilfov LosRíos 0 1 2 3 4 5 6 7 Minimum Country average Maximum%
- 20. Patents per million inhabitants in European regions (TL2)
- 21. Regional differences in the % of women in R&D employment, 2015 (TL2) NorthWest West Centro Central Extremadura South-East Podkarpacia W.Transdanubia CentralJutland FlemishRegion N.Ireland East Piedmont Moravia-Silesia Vorarlberg Drenthe N.East N.West Algarve Bratislava BalearicI. North Lodzkie N.GreatPlain Copenhaguen Wallonia GreaterLondon West Lazio Prague Vienna Groningen 10 15 20 25 30 35 40 45 50 55 60 LVA LTU BGR EST ROU PRT SVK ESP NOR POL HUN DNK BEL GBR SVN ITA CZE AUT NLD LUX Minimum Country average Maximum Gender equilibriumlevel (50%)%
- 22. Regional variation in the % of the labour force with at least secondary education, 2017 Labour force 15 years old or older, large regions (TL2) JewishOblast NorthEast North-West NorthEast E.Cape Caquetá East PrinceEdwardI. SmålandwithI. Border,Midland,W. LakeGeneva East Warmian-Masuria North BrusselsRegion Vorarlberg North Northwest Zealand Drenthe Åland Normandy North California N.GreatPlain Rhineland-Palatinate OtherRegions Gangwon Taurage Tasmania Apulia Maule Southland Azores E.Macedonia,Thrace Extremadura E.AnatoliaE. Moscow SouthWest GreaterNorth-East Bucharest-Ilfov Gauteng BogotáCapital West BritishColumbia UpperNorrland SouthandEast Zurich Bratislava Silesia OsloRegion FlemishRegion Carinthia Central Prague CopenhagenRegion Utrecht West Brittany GreaterLondon Maine Central Thuringia ReykjavikRegion SeoulRegion Vilnius CanberraACT Trento Antofagasta Wellington LisbonMetropolitan Attica BasqueCountry Ankara 0 20 40 60 80 100 120 Minimum Country average Maximum %
- 23. Regional disparities in the presence of native-born with tertiary education Large regions (TL2), 2014-15 (two-year average) East Åland Wallonia HedmarkandO Azores Sicily Border, Midland,W. Saskatchewan Styria N.GreatPlain N.Middle N.Jutland Zeeland East Saarland CanaryIslands Tasmania Picardy N.E.England Northwest WestVirginia Oaxaca West Helsinki-U. BrusselsReg. OsloRegion Lisbon Metropolitan Lazio SouthandEast Ontario Vienna Central Stockholm CopenhagenR. Utrecht Zurich Berlin BasqueC. Canberra RegionACT Île-de-France GreaterLondon Prague D.ofColumbia MexicoCity -20 0 20 40 60 80 100%
- 24. Regional variation in the % of households with a broadband connection, 2017 Large regions (TL2) Middle-West Ingushetia Gangwon OtherRegions Wallonia Zealand Overijssel East Burgenland South Border,Midland,W. Trøndelag Ticino West Northeast Quebec Northwest Galicia Latgale N.Middle N.E.England Tasmania Utena Brandenburg North Calabria Swietokrzyskie Alentejo Northland Corsica Mississippi Hokkaido Jerusalem Maule E.AnatoliaE. Chiapas GreaterNorth-East SaintPetersburg SeoulRegion ReykjavikRegion FlemishRegion CopenhagenRegion Flevoland West Styria Helsinki-Uusimaa SouthandEast OsloRegion Zurich Bratislava North Alberta Prague Madrid Riga CentralNorrland GreaterLondon CanberraRegionACT Kaunas Hamburg Central Lombardy Podkarpacia LisbonMetropolitan Auckland Île-de-France NewHampshire S.-Kanto Central Antofagasta Istanbul BajaCaliforniaS. 0 20 40 60 80 100 120 140 Minimum Country average Maximum %
- 25. Regional variation in the % of population using Internet for public services, 2017 Large regions (TL2) C.Transdanubia S.W.England LisbonMetropolitan Madrid Île-de-France CentralBohemia Berlin Groningen Trento OsloRegion BrusselsRegion Vienna Helsinki-Uusimaa UpperNorrland EspaceMittelland SouthandEast Bratislava CopenhagenRegion West 0 10 20 30 40 50 60 70 80 90 100 % Maximumregion (name) Minimum region
- 26. Regional differences of unemployment rate, 2017 Large regions (TL2) S.W.Oltenia Quindio NorthWestSouth-East FreeState Ingushetia East South Border,Midland,W. Kyushu,Okinawa SeoulRegion EastandNorth N.E.England AgderandRogaland Jerusalem South Moravia-Silesia South Madeira NewMexico Groningen Berlin Hauts-de-France LakeGeneva N.GreatPlain Atacama Tabasco Podkarpacia Northland Vienna East NewfoundlandLabrador BrusselsRegion W.Macedonia Extremadura Calabria SEAnatoliaE. 0 5 10 15 20 25 30 35 Minimum Country average Maximum %
- 27. Gender gaps in employment rate and share in tertiary education Difference between male and female, TL2 Highest regional gender gap in employment rate Central Prague Limburg Salzburg Central North East Central South Algarve Midi-Pyrénées Ceuta South-East S. Aegean E. Anatolia E. Stockholm Silesia Ticino Saxony-Anhalt Friesland Vienna Scotland East N. Great Plain Zealand Centro Corsica Campania Wallonia North W. Macedonia Ankara C. Norrland -15 -5 5 15 25 CHE DEU LUX CZE NLD AUT GBR SVK ROU HUN DNK PRT FRA ITA ESP BEL NOR GRC FIN IRL TUR SWE POL SVN LTU EST LVA Minimum Country average Maximum %-points Swietokrzyskie South and East Border, Midland East and North Greater London Bolzano-Bozen Brussels Region Helsinki-Uusimaa Castile and León Bucharest - Ilfov Central Moravia Baden-Württemberg Åland Trøndelag C. Norrland Iceland South East PACA North Saarland Alberta Brussels Region Greater London Victoria Ticino South and East Zeeland East Opole region Gyeongnam North S.-Kanto Utah West Maule Sardinia Chiapas 0 10 20 30 40 50 FIN NOR SWE ISL DNK SVN FRA PRT DEU CAN AUT BEL GBR AUS CHE IRL NLD SVK NZL HUN CZE POL KOR ESP ISR JPN USA GRC CHL ITA TUR MEX Percentage points Maximum in 2017 (region name) Maximum in 2000 Vorarlberg C. Anatolia - W.S. Tasman-Nelson-Marl. Central Bohemia W. Transdanubia Castile-La Mancha Gender gap in tertiary education, 2017
- 28. Urban differences in average exposure to air pollution, 2015 Bergen Turku Galway Toowoomba Tallinn Aalborg Umeå PontaDelgada St.John's Namur Leeuwarden Quimper Aberdeen Ljubljana Bend Flensburg Naha Innsbruck Kavala Szeged St.Gallen BenitoJuárez BanskáBystrica PuntaArenas Lugo KarlovyVary Slupsk Cosenza Jeju Luxembourg Stavanger Kuopio Dublin GreaterDarwin Tartu Odense Malmö PóvoadeVarzim Windsor Oostende Middelburg Hénin-Carvin Margate Maribor Merced Görlitz Kitakyushu Vienna Irakleio Budapest Lugano Mexicocity Trencín Santiago Melilla Karviná Rybnik Padova Pyeongtaek - 5 0 5 10 15 20 25 30 35 Minimum city Country average Maximumcity μg/m3
- 29. Public expenditure per capita by level of government (USD PPP, 2016) 0 5 000 10 000 15 000 20 000 25 000 30 000 35 000 40 000 45 000 MEX CHL TUR LVA POL KOR EST HUN SVK GRC CZE PRT NZL ISR SVN ESP OECD26 JPN OECD35 AUS GBR OECD9 EU28 CAN ITA IRL DEU USA CHE NLD ISL FRA FIN SWE BEL AUT DNK NOR LUX USD PPP Local government State government State and local government Central government and social security
- 30. The future of work: A regional dimension
- 31. Percentage of jobs at significant and high risk of automation by country (%), 2013
- 32. Some countries have wide disparities in terms of high risk of automation across regions
- 33. Regions highly affected by automation display higher unemployment and lower productivity Labour productivity and unemployment rate in TL2 regions, 2015
- 34. The Regional dimension of job creation: Italy
- 35. The Regional dimension of job creation: Italy A. Creating jobs, predominantly in less risky occupations B. Creating jobs, predominantly in riskier occupations C. Losing jobs, predominantly in riskier occupations D. Losing jobs, predominantly in less risky occupations Lombardy Campania Piedmont Liguria Molise Autonomous Province of Bolzano Valle d’Aosta Abruzzo Basilicata Tuscany Sicily Apulia Autonomous Province of Trento Sardinia Calabria Emilia-Romagna Veneto Friuli-Venezia Giulia Lazio Marche Umbria
- 36. Job creation by risk of automation, selected regions, 2011-16, Italy
- 37. The Regional dimension of job creation: Greece
- 38. The Regional dimension of job creation: Greece A. Creating jobs, predominantly in less risky occupations B. Creating jobs, predominantly in riskier occupations C. Losing jobs, predominantly in riskier occupations D. Losing jobs, predominantly in less risky occupations North Aegean Attica Ionian Islands South Aegean Crete East Macedonia, Thrace Central Macedonia West Macedonia Epirus Thessaly Western Greece Continental Greece Peloponnese
- 39. The Regional dimension of job creation: Portugal
- 40. The Regional dimension of job creation: Spain
- 41. The Regional dimension of job creation: Spain A. Creating jobs, predominantly in less risky occupations B. Creating jobs, predominantly in riskier occupations C. Losing jobs, predominantly in riskier occupations D. Losing jobs, predominantly in less risky occupations Valencia Aragon Galicia Castile and Leon Balearic Islands Andalusia Asturias Castile-La Mancha Canary Islands Murcia Cantabria Basque Country Navarre Rioja Madrid Extremadura Catalonia