OECD Regions and Cities at a Glance 2018 - Overview
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Presentation by Rudiger Ahrend, Head of Economic Analysis, Statistics and Multi-level Governance at the OECD Centre for Entrepreneurship, SMEs, Regions and Cities at the second meeting of the Spatial productivity Lab of the OECD Trento Centre held on 4 December 2018. More info http://oe.cd/SPL
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OECD Regions and Cities at a Glance 2018 - Overview
- 1. Trento Spatial Productivity Lab OECD Regions and Cities at a Glance 2018 Head of Economic Analysis, Statistics and Multi-level Governance Centre for Entrepreneurship, SMEs, Regions and Cities Rudiger Ahrend Trento, 4 December 2018
- 2. Regions and Cities at a Glance 2018 New features of this edition Recent trends on entrepreneurship in regions, with new indicators on creation and destruction of firms and associated jobs. An assessment of migrant integration in OECD regions. Indicators of socio-economic conditions, inequalities and poverty in metropolitan areas and their neighbourhoods.
- 3. Structure of the presentation 1. Regions as drivers of national productivity 2. Selected determinants of productivity 3. (Well-being in regions) 4. (Cities and national economies)
- 4. Structure of the presentation 1. Regions as drivers of national productivity
- 5. Regional economic disparities have started narrowing, but remain high
- 6. 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 % % of GDP in the capital region (TL2) over total country GDP, 2016 Capital regions have been gaining economic importance within countries The median share of GDP in capital regions increased by 12% (2.8 percentage points) since 2000. Largest increase in Norway (+21%), lowest in Mexico (-8%). Enterprise creation and employment creation rates by new firms are 60% higher in capital regions.
- 7. Labour productivity in 2016, TL2 regions
- 8. Labour productivity 2016, large regions (TL2) Hawaii (USA) CHILE 400 km 350 km 250 km This map is for illustrative purposes and is without prejudice to the status of or sover- eignty over any territory covered by this map. Source of administrative boundaries: National Statistical Offices and FAO Global Administrative Unit Layers (GAUL). Higher than 92000 Between 72000 and 92000 Between 53 000 and 72000 Between 34500 and 72000 Lower than 34500 Data not available Acores (PRT) Canarias (ESP) 200 km 300 kmHigher than 92000 Between 72000 and 92000 Between 53000 and 72000 Between 34500 and 53000 Lower than 34500 Data not available 200 km Madeira (PRT) This map is for illustrative purposes and is without prejudice to the status of or sover- eignty over any territory covered by this map. Source of administrative boundaries: National Statistical Offices, Eurostat (European Commission) © EuroGeographics and FAO Global Administrative Unit Layers (GAUL). 500 km
- 9. 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 9 Source:OECD(2018)ProductivityandJobsinaGlobalisedWorld:(How)CanAllRegionsBenefit? Challenge? Productivity gaps have narrowed in the EU and the OECD
- 10. Annual productivity growth 2010-16 TL2 regions
- 11. Productivity convergence, 2010-16 (TL2) Difference in average annual productivity growth between top and bottom 10% regions
- 12. Composition of spatial disparities in productivity, 2015 Theil index of inequality, between and within large (TL2) regions
- 13. Spatial productivity differences within the same region, 2000-15
- 14. Where do productivity gains 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)
- 15. Patterns of productivity growth by type of region Distribution of type of regions into frontier, catching up, diverging and keeping pace, 2000-15, TL3.
- 16. 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 ? 16 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?
- 17. Annual productivity growth in tradable and non-tradable sectors, 2010-15 (TL2) Productivity growth in regions that are more or less concentrated on tradable sectors than the national average
- 18. Structure of the presentation 1. Regions as drivers of national productivity 2. Selected determinants of productivity
- 19. Expenditure on R&D in regions (TL2) R&D expenditures as % of GDP, 2015
- 20. Regional variation in the % of the labour force with at least secondary education, 2017
- 21. Regional disparities in the presence of native-born with tertiary education 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% Large regions (TL2), 2014-15 (two-year average)
- 22. Regional variation in the % of households with a broadband connection, 2017 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 % Large regions (TL2)
- 23. Regional variation in the % of population using Internet for public services, 2017
- 24. Importance of metropolitan areas
- 25. Population in cities continues to grow, with strongest growth in largest metropolitan areas • Metropolitan areas with more than 1.5 million inhabitants grew by 13% since 2000 0 10 20 30 40 50 60 70 80 90 100 Large metropolitan area (>1.5 Million) Metropolitan area (500k - 1.5 Million) Medium-sized urban area (250k -500k) Small urban area (50k -250k) % Country (number of urban areas) Share of people living in urban agglomerations (at least 50 thousands) Population in functional urban areas over total national population 69%
- 26. Metropolitan areas represent an important share of national economies Metropolitan areas (> 500 thousands people) represent 55% of total population, but account for 59% of employment and 60% of GDP. Capitals, typically the richest metropolitan areas, recorded a per capita GDP 37% higher than national per capita GDP Bogotá Santiago Vienna Oslo Toyohashi Copenhagen Basel Greater Perth Amsterdam Lisboa Helsinki Edmonton Brussels Madrid Athens Dublin Riga Ljubljana Tallinn Stockholm London Milan Budapest Prague Munich Paris Monterrey Nam Santa Cruz Warsaw Bratislava 0 20 000 40 000 60 000 80 000 100 000 120 000 COL CHL AUT NOR JPN DNK CHE AUS NLD PRT FIN CAN BEL ESP GRC IRL LVA SVN EST SWE GBR ITA HUN CZE DEU FRA MEX KOR USA POL SVK Country average Maximum USD per head, PPP, prices of 2010 Differences in GDP per capita between richest Metropolitan area and country average, 2016
- 27. Last 3 years, positive net inter-regional population flows, mainly towards urban regions Annual regional mobility, average 2014-16, TL3 regions, net flows - On average, 2% of total population changed region of residence in 2014-16 - Urban regions accounted for 80% of in-country youth migration over the last three years - Among rural regions, remote ones show higher net outflows
- 28. Annual GDP growth in metropolitan areas, 2000-16 -1 0 1 2 3 4 5% Ordered by the highest to lowest difference between the metropolitan areas and the rest of the country
- 29. 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 %
- 30. Structure of the presentation 1. Regions as drivers of national productivity 2. Selected determinants of productivity 3. Well-being in regions
- 31. Finding a job remains considerably more difficult in certain regions, especially for youths • Unemployment rates are on average close to pre-crisis level, but differences across regions remain high, up to 20pp • Differences are particularly stark for the youths, as more than 50% of young people is unemployed in certain regions in Italy and Greece. • Regional unemployment gap (2012- 16) increased mainly due to faster job growth in regions with low unemployment
- 32. Gender gaps in employment rate remain high (12.3 pp), but improved since 2000 Chap.3 Maximum regional gender gap in employment rate (male - female), 2000-16 0 5 10 15 20 25 30 35 40 45 50 Maximum region in 2016 Maximum region in 2000 Percentage points difference -2 -3
- 33. 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
- 34. Households spend on average 20% of income on housing, with large variation across places Housing expenditure exceeds 35% of household disposable income in the capital regions of Oslo (Norway) and Jerusalem (Israel) Families living in Greater London, and Vienna spend 50% more for housing than those in Northern Ireland and Burgenland, respectively.
- 35. Structure of the presentation 1. Regions as drivers of national productivity 2. Selected determinants of productivity 3. Well-being in regions 4. Cities and national economies
- 36. Metropolitan areas can also be highly unequal and show segregation of different income groups The Gini index of inequalities is 3.3% higher in metropolitan areas than elsewhere. Income inequalities can translate into rich and poor people living separated in different neighbourhoods (i.e. segregation). In 9 out of 11 countries considered, higher income groups show the highest segregation. Concepción Lancaster(PA) Québec Porto Gent Catania Nantes Göteborg Linz Santiago Miami Calgary Lisbon Brussels Bari Paris Malmö Vienna Copenhagen Oslo 0.1 0.2 0.3 0.4 0.5 0.6 CHL (3) USA (93) CAN (34) PRT (2) BEL (4) ITA (13) FRA (15) SWE (3) AUT (3) DNK (1) NOR (1) Minimum Metropolitan Area Country average Maximum Metropolitan Area Gini index Inequality in disposable income within metropolitan areas (2016 or latest available year)
- 37. Following improvements in the last decade, air pollution in cities has started to increase again 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 Urban average exposure to air pollution, 2015
- 38. Thank you! Contacts: RegionStat@oecd.org Rudiger.Ahrend@oecd.org Visit the updated web-sites: www.oecdregionalwellbeing.org https://measuringurban.oecd.org/# Look at the country pages: https://oe.cd/pub/2n9
- 39. Regions with strong pre-crisis increases in non-tradable sectors lost more jobs 39 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?
- 40. 40 GVC integration and vertical specialisation
- 41. 41 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
- 42. GDP growth in metropolitan areas, 2000-16
- 43. Elderly dependency ratios in 2017 10 15 20 25 30 35 40 45 50 55 TUN ROU BGR ISR LUX MEX TUR CHL SVK ISL IRL POL USA OECD BEL NZL KOR HUN SVN AUT CZE NOR CAN AUS LTU LVA CHE EST DEU DNK ITA FIN FRA GBR SWE GRC PRT NLD ESP JPN Rural Intermediate Urban % Dependency ratios in 2017
- 44. The future of work: A regional dimension
- 45. Percentage of jobs at significant and high risk of automation by country (%), 2013
- 46. Some countries have wide disparities in terms of high risk of automation across regions
- 47. Regions highly affected by automation display higher unemployment and lower productivity Labour productivity and unemployment rate in TL2 regions, 2015
- 48. The Regional dimension of job creation: Italy
- 49. 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
- 50. Job creation by risk of automation, selected regions, 2011-16, Italy
Editor's Notes
- Release of the publication: 18th of October 2018 during the Plenary Session of the Committee of the Regions in Brussels Published every two years with a special focus. The previous editions had a special chapters on Metropolitan areas and their contribution to national competiveness, in 2016 it was on well-being, for 2018 the focus is made on business demography and migration.
- This report aims at providing a comprehensive picture of measures that reflects the progress of people’s life and the level of progress in regions and metropolitan areas. Regional economies are analyzed along these dimensions, with their concentration of resources, their contribution to national growth, the persistence of disparities and the links between the characteristics of regions and their performance. The special chapters are about business demography and migration and built on the experience drawn from the reports on “Geography of Firm Dynamics (2017)” and “The integration of migrants in OECD regions” which have been presented thoroughly during the sessions of the Working Party
- This report aims at providing a comprehensive picture of measures that reflects the progress of people’s life and the level of progress in regions and metropolitan areas. Regional economies are analyzed along these dimensions, with their concentration of resources, their contribution to national growth, the persistence of disparities and the links between the characteristics of regions and their performance. The special chapters are about business demography and migration and built on the experience drawn from the reports on “Geography of Firm Dynamics (2017)” and “The integration of migrants in OECD regions” which have been presented thoroughly during the sessions of the Working Party
- Total OECD-wide regional disparities relatively stable but changing composition Recently, disparities across countries have become relatively more important again Similar trend in last years if we use the Theil decomposition Within countries, we see an increased concentration of economic activity in capitals. On average, they account for more than 26% of national GDP Importance is rising (relevance of service sector?) Since 2000, economic gaps between regions have been stable or decreasing in half of the OECD countries, but have been further increasing in the other half. For example, Chile, Mexico and New Zealand significantly narrowed regional economic disparities. In contrast, disparities for countries that were hit the hardest by the global financial crisis (e.g. countries in Southern Europe or Ireland) increased, albeit with some signs of a reversal in recent years.
- Within countries, we see an increased concentration of economic activity in capitals. On average, they account for more than 26% of national GDP Importance is rising (relevance of service sector?) - Enterprise rates: per capita
- Among economically lagging regions that successfully caught up with more productive regions, a number of characteristics stand out: proximity to cities and exposure to international trade. Rural regions close to a city have narrowed the gap with urban regions by 3 pp since 2010 and now their labour productivity levels are equivalent to 82% of urban regions’ productivity. On average, productivity gains in the tradable sector were generated by firms becoming more productive while gains in the non-tradable sector occurred through a reallocation of employment from less to more productive activities. Remote regions are overrepresented in the group of diverging, lagging regions. Remote lagging regions only make up 14% of ‘catching up’ regions (i.e. those regions that successfully managed to narrow the productivity gap versus the most productive regions in their country)
- This report aims at providing a comprehensive picture of measures that reflects the progress of people’s life and the level of progress in regions and metropolitan areas. Regional economies are analyzed along these dimensions, with their concentration of resources, their contribution to national growth, the persistence of disparities and the links between the characteristics of regions and their performance. The special chapters are about business demography and migration and built on the experience drawn from the reports on “Geography of Firm Dynamics (2017)” and “The integration of migrants in OECD regions” which have been presented thoroughly during the sessions of the Working Party
- The report documents that the importance of cities is rising across the OECD: Growing population Increasing economic significance More innovative and higher firm creation rates
- The documented regional differences in economic factors and living standard are likely to be affected by demographic megatrends such as migration and ageing: - They provide opportunities as well as challenges - R@AG documents these trends, with a special focus on migration: In the 31 observed OECD countries, 21.5 million people changed their region of residence each year, during the period 2014-16. This movement corresponded to 2% of the total population in the OECD area, more than four times the value of the international migration rate to OECD countries. 7 people per every 10 000 inhabitants of a urban area are migrants from a rural region. Net migration rate is -2 and -11 for intermediate and rural regions, respectively. Distance to labour markets and services seems to explain inter-regional migration within OECD countries: remote rural regions which are far in driving distance from urban agglomerations show higher net negative flows than predominantly rural regions. The mobility of youth, which represents 6% of the total internal mobility is a migration from rural to urban regions where higher education facilities and more diverse job opportunities can be found.
- This report aims at providing a comprehensive picture of measures that reflects the progress of people’s life and the level of progress in regions and metropolitan areas. Regional economies are analyzed along these dimensions, with their concentration of resources, their contribution to national growth, the persistence of disparities and the links between the characteristics of regions and their performance. The special chapters are about business demography and migration and built on the experience drawn from the reports on “Geography of Firm Dynamics (2017)” and “The integration of migrants in OECD regions” which have been presented thoroughly during the sessions of the Working Party
- Regional differences in these economic factors are highly relevant because they have a direct impact on people’s living standards. The report examines various well-being dimensions in regions: employment, education, housing etc. In several well-being dimensions, in particular education and health, regional disparities have fallen but they are often still significant. ** At least 10pp of differences between regions in unemployment rate are found in Turkey, Italy, Spain, Greece and Belgium. In 30% of regions, less than a half of working age women were employed in 2017
- - Female employment rates have increased in OECD countries over the past decades, the overall rate exceeding 61% in 2016. Important differences in the access to labour markets for women still persist in OECD area with a difference of 12.3 percentage points in employment rate compared to male in 2016, a gap slightly lower than in 2000 (12.8) The highest regional gender gap was above 20 percentage points in fifteen countries in 2000, and only in six countries in 2016 However, in 28% of OECD regions, less than half of women were employed in 2016. Regional discrepancies in female employment were the largest in Mexico, Turkey, Chile, Italy, Greece and Spain In Mexico, the highest region in 2000 was Campeche -51pp decreased to -39pp of difference, replaced by Chiapas as the highest gap (49pp in 2016) The biggest decrease in gender gap occurred : in the Azores in Portugal (-69% of the gap) – the reduction was of the same level in the Metropolitan area of Lisbon (-58%) In Ireland (-53% in Border, Midland and Western
- Housing remains a pressing issue for many residents in OECD regions as high and rising costs put a strain on household finances.
- This report aims at providing a comprehensive picture of measures that reflects the progress of people’s life and the level of progress in regions and metropolitan areas. Regional economies are analyzed along these dimensions, with their concentration of resources, their contribution to national growth, the persistence of disparities and the links between the characteristics of regions and their performance. The special chapters are about business demography and migration and built on the experience drawn from the reports on “Geography of Firm Dynamics (2017)” and “The integration of migrants in OECD regions” which have been presented thoroughly during the sessions of the Working Party
- While cities are richer and there residents enjoy higher income levels, they are also more unequal and often segregated.
- In 14 countries out of the 24 countries available, the capital-city region gathers the highest share of foreign-born. Two thirds of the foreign-born population live in mostly metropolitan regions, 6 percentage points more than the average of the native-born population (58%)