1. Swedish Agency for Economic and Regional Growth / RAPS Conference 2016
Stockholm, 28 November 2016
Swedish Agency for Economic and Regional Growth / RAPS Conference 2016
OECD Regions at a Glance 2016,
Highlights
Gonnard Eric
OECD Public Governance and Territorial Development Directorate

2. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

3. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

4. Regional development at the OECD
OECD composed of specialised Policy Committees
Regional Development Policy
Committee (TDPC)
Education Policy Committee
Committee on Fiscal Affairs
Employment, Labour and Social Affairs Committee
Committee on Statistics and Statistical Policy (CSSP)
...
…and Working parties
WP on Territorial Policy in Urban Areas
WP on Territorial Policy in Rural Areas
WP on Territorial Indicators (WPTI)
WP on Indicators of Educational Systems
WP on Tax Policy Analysis and Tax Statistics
WPs on Social Policy; Employment …
Secretariats (Directorates) often have responsibility for specific statistics, some statistical responsibilities are shared, but the Statistics Directorate and the Committee of Statistics (CSSP) play a co-ordinating role

5. Direction of territorial work is defined during working parties
From countries
Expression of policy questions
From OECD secretariat
Discussion on definitions, framework,
country experiences
Working Party on Territorial Indicators
Harmonised data collection
Annual questionnaire +
Public official sources
Policy awareness: instruments for communication
Outputs discussed, elaboration of policy strategy
Analysis of comparative performance
 Delegates
 Publications (Regions at Glance)
 Web tools (metroexplorer, oecdregionalwellbeing)
 Databases (oecd.stat)
 Regional structure, characteristics of different types of regions
 Spatial concentration
 Trends and persistence of inequalities
Working Party on Territorial Indicators

6. Example of themes discussed at the last WPTI (November 2016):
Final report on Well-being in Danish cities.
Interim results on housing prices, unit labour costs and GVC at regional level, Regional business demography and entrepreneurship.
Presentation of project “the role of local government in migrants integration”, including data needs, methodology for case studies and preliminary results on “The local impact of migration”.

7. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

8. The OECD Regional Database
Regions in each member country have been classified based on two administrative territorial levels (TLs):
Territorial Level 2 (TL2), consists of 362 OCDE large regions, while the lower level, Territorial Level 3 (TL3), is composed of small regions.
Classified by regional typology OECD definition: (Predominantly Urban, Intermediate, Predominantly Rural) and extended regional typology
Covers 6 wide topics
OECD Statistical portal:
Since 2015 : statistics on subnational government public finance, expenditure, revenues, investment, debt etc. by level of government.

9. To increase comparability among regions, they have been classified
New typology of regions (Predominantly Urban , Intermediate, Predominantly Rural) at TL3 level is defined through three steps:
1) Define urban clusters based on population grid density of 1km2, where clusters are contiguous cells with a density of at least 300 inhab./km2 and inhab. (600 inhab./km2 and inhab. in Japan and Korea)
2) Proportion of urban population in the region:
≥ 80%  Predominantly urban (PU)
< 50%  Predominantly rural (PR)
Between 50 and 80%  Intermediate (IN)
3) Reallocation of the typology, if more than 25% population of the region lives in urban cluster with at least:
inhab.: Rural  Intermediate
inhab.: Intermediate  Urban
Define urban clusters
% population living in (1)
Urban centres criteria

10. Extended rural typology: rural regions are classified according to the distance from an urban centre
Driving time of at least 50% of regional population to the closest locality with more than inhabitants. (<> 60 minutes)
Predominantly Urban (PU)
Intermediate (IN)
Predominantly Rural (PR)
Predominantly Urban (PU)
Intermediate (IN)
Predominantly Rural Close to a city (PRC)
Predominantly Rural Remote (PRR)

11. OECD-EU definition of Functional Urban Areas (cities)
Why an harmonised definition of cities?
Policies need to reflect the reality of where people live and work
The connections between cities and with surrounding areas can lead to important changes in how and where economic production takes place
Individual cities are interested in comparing their performance
The approach
It identifies urban areas beyond city boundaries, as integrated labour market areas
It identifies urban areas of different size ((small urban, medium-sized urban, metropolitan and large metropolitan)
It allows comparisons among the different forms that urbanisation takes

12. What is the method for FUA?
The method uses commuting data and population density calculated for grid spatial units of 1 km ²
The functional urban areas are defined as densely populated municipalities (city cores) and adjacent municipalities with high levels of commuting towards the densely populated urban cores (commuting zone).
A minimum threshold for the population size of the functional urban areas is set at 50^000 population
It is applied to 30 OECD countries and identifies urban areas
For more details on the methodology: “Redefining urban: a new way to measure metropolitan areas” , OECD Publishing, 2012

13. How does the new approach change our views of cities?
Many cities don’t match the city boundaries
Source: OECD calculations based on population density disaggregated with Corine Land Cover.

14. Cities in Sweden
Classification of 12 urban areas into four “types” according to population size
small urban areas, with a population below people;
medium-sized urban areas, with a population between and people;
metropolitan areas, with a population between and 1.5 million people;
large metropolitan areas, with a population of 1.5 million or more.
SE002 - Gothenburg
SE001 - Stockholm
SE003 – Malmö
In red: metropolitan areas (> pop.)
Stockholm
Malmö
Gothenburg
Uppsala 8

15. Metropolitan database (for those FUAs above 500 000 inhabitants)
- Population (level and growth)
- Population density
- Population by age
- Total Area
- Urbanised area (share & change)
- Polycentricity
- Concentration of population in core areas
- Sprawl index
- Local units
- Local units in core area
- Territorial fragmentation
- GDP (level and growth)
- GDP per capita (level and change)
- GDP per worker
- Disposable income
- Gini index of disposable income
- Patents application
- Employment (level and change)
- Employment rate
- Labour force (level and change)
- Unempl. (level and change)
- Unempl. rate
- Participation rate
- Air pollution
- CO2 emissions per capita
- Co2 emissions from transport and energy sector
Demographic
Urban form
Territorial organisation
Labour market/Social
Environmental
Economic and innovation

16. Where to find the metropolitan database?
OECD.Stat 
Metropolitan explorer 

17. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

18. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

19. Regions at a Glance 2016 Release of the publication:
15th of June 2016: DSG Kiviniemi Plenary Session of the Committee of the Regions in Brussels
A comprehensive picture of the level of progress in regions and metropolitan areas towards more inclusive and sustainable development
It looks at what local resources are mobilised to increase national prosperity
A wide range of measures and levels of geography to reflect where people experience the diverse conditions

20. Structure of Regions at a Glance 2016
Chapter 1. Well-being in regions
Chapter 2. Regions as drivers of national competitiveness
Chapter 3. Subnational government finance and investment for regional development
Chapter 4. Inclusion and sustainability in regions

21. Regional well-being framework
Place characteristics
People’s well-being
Individuals’
characteristics
Including citizenship, governance and institutions

22. Focus on expected results (outcomes indicators)

23. Measuring multi-dimension well-being http://www. oecdregionalwellbeing

24. Relative performance of Swedish regions by well-being dimensions

25. Over the last decade inter-regional gaps have grown in safety, income and environment and decreased in education and access to services
Regional gaps in all OECD countries in well-being outcomes
(Theil index)

26. In Turkey, Spain and Italy regional unemployment rates differs by 20 pp comparable to the difference between the national unemployment rate in Greece and Norway in 2014
Regional variation
in unemployment
rate, 2014

27. Beyond inter-regional disparities, income inequality is high within regions: in some states in Mexico and United States and in Chilean provinces Gini is much higher than the one in the country as a whole
Gini index in disposable income
(each point is the Gini index of disposable income of a region)

28. Regional difference in life expectancy at birth, 2013
Geography matters for longevity: Difference in life expectancy among countries is 9 years, between Canadian provinces 11 years, and 6 years between Australia or US states.
Regional difference in life expectancy at birth, 2013
Difference among OECD countries

29. Elderly dependency rate, 2014
In 2014, the elderly dependency rate across OECD regions was generally higher in rural regions than in urban ones, especially in Japan, Netherlands, Portugal, Spain, the United Kingdom, Australia and Korea
Elderly dependency rate, 2014
rural<urban
rural<urban
rural<urban

30. In 23 out of 33 OECD countries, the educational attainment of workforce in lagging regions has narrowed the gaps with advanced regions in the past 15 years
Regional difference between the highest and lowest regional share of the workforce with at least secondary education, 2000 and 2014

31. Economic affairs (mainly transport) and education are the priority sectors for SNG investment, accounting for 39% and 22% of SNG investment on average in the OECD
Breakdown of subnational government expenditure by economic function, 2013 (%)
Chap.3

32. In 13 out of 32 countries, the SNG investment has decreased between 2007 and 2014
Annual average change in subnational government investment,

33. Annual growth of regional productivity, 2000-13 (GDP per worker)
In 30% of regions, productivity growth has been below 0.5% per year in
Annual growth of regional productivity, (GDP per worker)

34. Metropolitan areas contributed to more than 60% national GDP growth and are usually more productive than the rest of the economy
% of national GDP growth
contributed by metro areas,
Ratio between productivity in metro areas
and rest of economy, 2013
Metropolitan areas are FUA with more than 500k people

35. Air pollution is often an issue in metropolitan areas
Air pollution is often an issue in metropolitan areas. In 2014, 53% of the urban population was exposed to levels of air pollution higher than 10 μg/m3
μg/m3 class:
In the Netherlands, Poland, Germany, Belgium, Slovenia, Austria, Czech Republic, Hungary, Korea and the Slovak Republic more than 90% of the urban population was exposed to high pollution concentration levels.
On the other hand, all urban population in countries such as Australia, Estonia, Ireland and Norway are exposed to pollution levels well within the recommended safe levels

36. Since the economic crisis of 2008, jobs have recovered in many metropolitan areas; however, 2014 employment rates in metropolitan areas are still below 2007 levels in 19 out of 28 OECD countries.

37. Since 2008 employment growth has slowed down also in the most dynamic regions

38. Employment growth is not specific to urban regions: in , for12 out of 24 countries, the employment growth was higher in predominantly rural regions than in predominantly urban regions
Employment average annual growth, by type of region,

39. In the period , for 22 out of 27 OECD countries, lagging regions have increased the share of tertiary educated labour force faster than advanced regions, in contrast to R&D personnel share for which the gap widened in 12 out of 19 countries
Change in the share of labour force with tertiary education
Change in the share of R&D personnel
Gap
change
Gap
change

40. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

41. Why look at inclusive growth in cities?
Slow productivity growth and rising inequalities
importance of inclusive growth, i.e. growth that is contributed by, and beneficial to, all
Cities are drivers of national growth
local governments play a major role in providing services and investment for more inclusive growth
The OECD report Making Cities Work for All offers:
new evidence on well-being and inclusiveness at city level
guidance in 5 key policy areas: jobs, education and skills, housing, transport, quality services and environment

42. urban & regional policy Inclusive growth policy
A policy shift towards inclusive growth in cities & regions: Only a goal or an ongoing reality?
Cohesion-oriented
urban & regional policy
Growth-oriented
Inclusive growth policy
in cities & regions
Objectives
Compensating temporarily for location disadvantages
of lagging areas
Tapping underutilised potential in all areas for enhancing urban & regional
competitiveness
Fostering both equity & growth in cities & regions
Unit of intervention
Administrative regions/cities & firms
Functional economic areas  
Functional urban areas (of all sizes) that reflect the reality of where people live and work 
Strategies
Sectoral approach
Integrated development projects for economic growth
Multi-dimensional well-being for all
Tools
Subsidies & state aids
Investment in infrastructure to exploit competitive advantages of different places
Integrated policy packages that address both physical/ environmental capital and human/social capital
Key actors
Mainly central governments
Different levels of government & business sector
Partnerships across levels of government, as well as between public and private spheres, and civil society

43. 1. Territorial statistics work at the OECD
Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- How do cities contribute to higher prosperity
and people’s well-being?
- How do inequalities play out within cities?
- Policy approaches for prosperous and inclusive cities

44. per equivalent household; 2014 or latest available year
On average, households incomes are on average 18% higher in cities than elsewhere
Metropolitan vs. non metropolitan household disposable income ratio by country
per equivalent household; 2014 or latest available year
Note: The graph plots the ratio between household disposable income per equivalent household in metropolitan areas over that in the rest of the national territory. Countries are ordered by increasing value of that ratio.

45. Cities concentrate high-skilled people: on average, the share of highly – educated workers 11ppt higher in cities
Share of working-age population with tertiary education, 2012
Source: OECD (2016), Making Cities Work for All, OECD Publishing, Paris.

46. Gini coefficient of household disposable income, 2014
But in many countries, cities are also more unequal than their respective national average
Gini coefficient of household disposable income, 2014
Source: Boulant, J., M. Brezzi and P. Veneri (2016), "Income Levels And Inequality in Metropolitan Areas:
A Comparative Approach in OECD Countries", OECD Regional Development Working Papers, No. 2016/06, OECD Publishing, Paris. DOI: 

47. Only 1/5 of OECD cities have grown inclusively
Change in GDP pc and in Gini coefficient of household disposable income,
Source: OECD (2016), Making Cities Work for All, OECD Publishing, Paris.

48. Well-being outcomes can be very different across cities in the same country
Income
33,500 USD household income between Washington D.C. and McAllen (around 30,000 USD among OECD countries)
Gini index of household income between Celaya and Mexico City 0.12 (around 0.24 among OECD countries)
Jobs
17pp in the unemployment rate of Las Palmas and Bilbao (23pp among OECD countries)
36pp in the employment rate between Firenze and Palermo (32pp among OECD countries)
Differences between highest and lowest values in metropolitan areas
Environment
23 mg/m3 in the level of air pollution (PM2.5) between Cuernavaca and Mérida (21 among OECD countries)
Education
21pp in the share of workforce with tertiary education between The Hague and Rotterdam (26pp among OECD countries)

49. Satisfaction with affordability of housing is lower in cities than in the rest of the country (13 pp lower on average)
% of people satisfied with the affordability of housing in their city

50. Inequalities also mean spatial segregation in cities
Source: OECD (2016), Making Cities Work for All, OECD Publishing, Paris.

51. Higher administrative fragmentation is associated with higher segregation of people in different municipalities
Hypothesis: Fragmented metropolitan governance can facilitate segregation at the level of local units.
Controlling for country fixed effects and other city characteristics (i.e. income , population, spatial structure), higher administrative fragmentation is associated to higher spatial segregation by income in different municipalities

52. Summing up: What are the policy implications?
Inequality goes beyond income City-level data on different well-being dimensions can help design integrated multi-dimensional policies.
Inequality in cities also means spatial segregation Appropriate governance systems of metropolitan areas can reduce the cost of administrative fragmentation, which is associated with higher segregation.
Five policy areas where cities can make headway comprehensive packages of structural policies targeting the specific local conditions need to be put in place jointly by national and local governments.

53. How can well-being metric be used for policy-making?
Regional well-being measurement cycle: A possible sequencing of steps
The starting point of this well‑being measurement cycle varies across regions, according to the specific objective of measuring well-being and who is leading the process.

54. Outline
1. Territorial statistics work at the OECD
2. Territorial tools, regional and metropolitan databases
3. How this evidence is used for policy making:
- Examples from Regions at Glance
- Making cities work for all: data and actions for inclusive growth
- Well-being in Danish cities

55. What are the city regions in Denmark?
58% of national population (2016)
61% of national employment (2014)

56. Since 2000, disposable household income has been growing in all Danish cities, most quickly in Copenhagen and Aarhus.
Equivalised household disposable income (US$ constant 2010 prices and PPP)
Aarhus also shows the fastest increase in tertiary educational attainment of its working-age inhabitants.

57. Income inequality has been rising driven by faster growth in the top 20% of the income distribution.

58. Labour participation higher than OECD average, but stagnating since the economic crisis, with Odense showing the fastest decline
Copenhagen
Esbjerg
Aalborg
Aarhus
Odense
OECD cities (282)

59. Unemployment is concentrated in the cores, with the highest gap between the core and the commuting zone observed in Esbjerg and Aarhus.
Ratio between the unemployment rate in the cores and in the commuting zones

60. Exposure to violent crimes is higher in the cores than in the commuting zones, despite the generally high safety levels of the cities.

61. Life expectancy is not homogeneous within cities Differences across municipalities within the same city-region can go up to more than 5 years (Copenhagen)

62. Life expectancy tends to be higher in municipalities with higher median income (and larger population), on average
Median income in 2010 and life expectancy at birth ( )

63. Spatial segregation by income is stronger among the poorest households, a pattern similar to that found for Dutch cities.

64. Making cities work for all
Regions at a Glance
Publication (English):
Databases:
Metropolitan Areas Database
Regional Database
Data Visualisation:
Metropolitan explorer
Regional well-being:
Making cities work for all
Full publication and country fact sheets(in English):
Policy Highlights (available in English, French and Spanish):
Well-being in Danish cities
Publication (English): en.htm

65. Thank you!