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HOW CAN PRODUCTIVITY GAINS
BE SHARED AND INCLUSIVE
ACROSS SPACE
Global Productivity Forum, Budapest
Rudiger Ahrend
Head of Urban Programme
Centre for Entrepreneurship, SMEs, Local
Development andTourism
• Productivity
– Productivity across regions and cities
– Productivity performance / catching up
– Drivers of catching-up
– Territorial aspects of, and strategies for
developing the tradable sector
• Inclusiveness
– Inclusiveness in regions and cities
– Productivity-inclusiveness nexus across space
• Conclusion: Trade / GVC integration
Productivity across regions and cities
Productivity differs widely within countries
5
Bigger cities are more productive
City productivity increases with city size
even after controlling for sorting
6
• Productivity
increases by 2-5%
for a doubling in
population size
Administrative fragmentation is correlated
with lower city productivity
7 7
Productivity Performance /
Catching up
OECD economies have converged -
Within countries, regions have diverged
The productivity gap between frontier
and lagging regions has increased
Notes: Average of top 10% and bottom 10% TL2 regions, selected for each year. Top and bottom regions are the aggregation of
regions with the highest and lowest GDP per worker and representing 10% of national employment. 19 countries with data included.
Averages
of top
10%
(frontier),
bottom
75%, and
bottom
10%
(lagging)
regional
GDP per
worker,
TL2
regions
50 000
60 000
70 000
80 000
90 000
100 000
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
USD PPP per employee
Frontier regions Lagging regions 75% of regions
1.6% per year
1.3% per year
1.3% per year
60% increase
Geography of
productivity
convergence
relative to
national
frontiers in
European
regions
ITA DEU DNK AUT BEL CAN GRC NLD NZL FIN FRA ESP PRT USA AUS GBR SWE IRL SVN HUN CZE KOR POL SVK
-2%
-1%
0%
1%
2%
3%
4%
5%
Catching up Diverging Keeping pace Frontier Country average productivity growth
Productivity growth of the region
National labour productivity growth depends
on the performance of regions
Annual average growth in real per worker GDP between 2000-2013 (or
closest year available).
 Regional catching-up can play an
important role for national
productivity growth
Contribution to national labour
productivity growth, 2000-12
13
Productivity and “catching up” in Hungary
Percentage contribution to
national GDP growth, 2000-2012
Note: Difference between national labour productivity
growth as calculated with and without the indicated
region.
Note: The contribution is the product of a
region’s GDP growth rate by its initial share of
GDP.
Note: See http://www.oecd.org/regional/oecd-regional-outlook-2016-9789264260245-en.htm for country pages.
Frontier Catching up Keeping pace Diverging
Contribution to national labour
productivity growth, 2000-13
14
Productivity and “catching up” in Austria
Percentage contribution to
national GDP growth, 2000-2013
Note: Difference between national labour productivity
growth as calculated with and without the indicated
region.
Note: The contribution is the product of a
region’s GDP growth rate by its initial share of
GDP.
Note: See http://www.oecd.org/regional/oecd-regional-outlook-2016-9789264260245-en.htm for country pages.
Frontier Catching up Keeping pace Diverging
The drivers of regional
productivity catching-up
Good or bad productivity performance can
be found for all types of regions
0
10
20
30
40
50
60
70
80
90
100
Frontier (41) Catching-up (65) Diverging (76) Keeping pace (107)
%
Mostly Urban (127) Intermediate (62) Mostly Rural (100)
In which: 70% of mostly urban frontier
regions contain very large cities
in which: 75% of diverging mostly urban
regions contain very large cities
# regions in ( )
Labour productivity of remote rural areas
has recently declined
88%
89%
90%
91%
92%
93%
94%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Total
RURAL
RURAL CLOSE TO
CITIES
RURAL REMOTE
Productivity levels of Predominantly
Urban regions = 100
Stronger intensity of tradable sectors is
associated with productivity catching-up
All tradable sectors, TL2 regions
Notes: Tradable sectors are defined by a selection of the 10 industries defined in the SNA 2008. They include: agriculture (A), industry
(BCDE), information and communication (J), financial and insurance activities (K), and other services (R to U). Non tradable sectors are
composed of construction, distributive trade, repairs, transport, accommodation, food services activities (GHI), real estate activities (L),
business services (MN), and public administration (OPQ).
20
25
30
35
40
45
50
Frontier Catching-up Diverging Frontier Catching-up Diverging
Tradable GVA share Tradable employment share
2013 2000
%
19
Productivity gains in tradables are
mainly within sectors
-1
0
1
2
3
4
5
ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA
%
Tradable sectors - contribution to productivity growth
Employment shifts to faster growing sectors Employment shifts to initially more productive sectors
Sectoral productivity growth Productivity growth in tradable sectors
20
Productivity gains in non tradables are
associated with sectoral shifts
Only in Eastern Europe does the non-tradable
sector contribute by improving productivity
significantly; in some countries non-tradable
productivity is even declining
-1
0
1
2
3
4
5
ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA
%
Non-tradable sectors - contribution to productivity growth
Employment shifts to faster growing sectors Employment shifts to initially more productive sectors
Sectoral productivity growth Productivity growth in non-tradable sectors
Territorial aspects of, and strategies
for developing the tradable sector
Share of total
employment in
clusters by type
of TL2 region
Mostly urban
regions are those
with at least 70% of
its population living
in Functional Urban
Areas or part of its
population living in a
large metro area
with at least 1.5
million inhabitants.
Mostly rural regions
have less than 50%
of their population
living in FUAs
Source: OECD
Regional Statistics
and Ketels and
Protsiv (2016)
0 10 20 30 40 50 60 70 80 90 100
Footwear
Forestry
Leather and Related Products
Fishing and Fishing Products
Apparel
Agricultural Inputs and Services
Nonmetal Mining
Appliances
Livestock Processing
Coal Mining
Furniture
Water Transportation
Jewelry and Precious Metals
Wood Products
Textile Manufacturing
Electric Power Generation and Transmission
Automotive
Lighting and Electrical Equipment
Food Processing and Manufacturing
Vulcanized and Fired Materials
Downstream Metal Products
Paper and Packaging
Metalworking Technology
Plastics
Metal Mining
Construction Products and Services
Production Technology and Heavy Machinery
Upstream Metal Manufacturing
Transportation and Logistics
Medical Devices
Upstream Chemical Products
Environmental Services
Hospitality and Tourism
Local clusters (non-traded)
TOTAL
Printing Services
Education and Knowledge Creation
Recreational and Small Electric Goods
Distribution and Electronic Commerce
Downstream Chemical Products
Oil and Gas Production and Transportation
Performing Arts
Information Technology and Analytical Instruments
Tobacco
Aerospace Vehicles and Defense
Business Services
Marketing, Design, and Publishing
Insurance Services
Financial Services
Biopharmaceuticals
Video Production and Distribution
Communications Equipment and Services
Music and Sound Recording
Share of FTE employment in the cluster, %
Mostly urban Mostly intermediate Mostly rural
23
Urban areas attract more knowledge-
intensive firms
Birth shares by sector (births by sector/total regional births)
TL3 regions (15 OECD countries) 2014
Strategies for developing the tradable sector
To remain competitive in Tradable sectors there are mainly three
main options:
1. Continued specialisation in Natural resources. This is typically
an option for remote rural regions
2. Be integrated in Global Value Chains. Integration between
manufacturing and service sectors is needed. Connectivity and
proximity may favour low-density areas close to cities. Without a
territorial strategy it may be difficult to benefit from GVCs for
regional development. Forward and backward linkages (re-
bundling) are critical to maximize value-added of FDI and
creation of a network of local suppliers.
3. Develop Territorially differentiated products & services
through mobilisation of local assets. Consumers may express
preferences for local or traceable products, without subsidies or
some form of protection.
Inclusiveness in regions and cities
26
Gini index of disposable income (after tax and transfers), 2013
Disparities of household income are large
within regions, mainly in capital cities
Source: OECD Income Distribution Database and OECD Regional Well-being database
Eastern
Slovenia
Capital
Oslo
and
Akershus
Åland
Prague
Brussels
Capital
Region
Bratislava
Region
Central
Hungary
Vienna
Stockholm
North
Holland
Hesse
Ile-de-France
Central
Region
Hokkaido
Ticino
Southern
and
Eastern
Ontario
Sicily
Western
Australia
Ceuta
AttikiNorth
Island
South
East
England
Estonia
Jerusalem
District
District
of
Columbia
Northeastern
Anatolia
West
Santiago
Metropolitan
Oaxaca
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
#REF!
Regional value National average
Larger cities are more unequal
27
Metropolitan population and income inequality, circa 2014
Metropolitan size and inequality, once controlled for income levels and country effect
Brussels
Antwerpen​
Liège
​
Red Deer
​
Calgary
​
​
Lethbridge
​
​
​
Thunder Bay
​
Québec
​
Trois Rivières
​
Montreal
​
Sherbrooke
​
​
Toronto
​
​
Brant
​
Windsor
​
Iquique
​
Antofagasta
​
​
Calera
​
​
San Antonio
​
Rancagua
​
​
Linares
​
​
Temuco
​
Osorno
​
Punta Arenas
Paris
​
Toulouse​
Saint-Etienne​
​
Rouen Roma
Milano
Napoli
​
​
​ Tijuana
​
Hermosillo
​
Reynosa
​
Torreón
​
​
León Guadalajara
​Pachuca de Soto ​
Mexico City
​ Toluca
​
​
​
​
Oslo
​
Malmö
​
Portland
​​
Buffalo
​
Albany
​
Boston
​
​
Cleveland
​
Omaha
New York
​
​
Philadelphia
​
Denver
​
​
Cincinnati
Washington
​
​ San Francisco
​
Fresno
Las Vegas
​
​
Albuquerque
Memphis
​
Los Angeles
​
Atlanta
​
Dallas
Houston
Miami
McAllen
0.05
0.1
0.15
0.2
0.25
10 11 12 13 14 15 16 17
Ginicoefficient(componentplusresiduals)
City population (natural logarithm)
What do we know about the nexus
between productivity and
inclusiveness across space
Towards a topology for regions and cities*
*This section is based on preliminary work that has been prepared by the Program for
Local Economic and Employment Development (LEED) and discussed by its Committee.
Variables Weight
Unemployment
Equal
weighting
was selected
after PCA
assigned
similar
weights to all
indicators
Long-term unemployment
Low-work intensity household
Deprivation rate
Poverty rate
NEET rate
Educational attainment: primary education
Designing the Inclusiveness Composite
Indicator (Work in Progress)
Designing the Inclusiveness Composite
Indicator
What it does
• Reduce the data from a
multidimensional frame to a
single dimension, simplifying its
interpretation
• Concentrate on the inclusion of
the most disadvantaged
individuals in society
• Provide a way to measure
regional differences within the
same country and across
countries
What it does not do
• Provide a measure of income
inequality
• Act as an indicator of overall
well-being
• Include data on access to basic
services (future development)
Praha
Severozápad
Hovedstaden
Syddanmark
Helsinki-Uusimaa
Etelä-Suomi
Southern and Eastern
Trento
Veneto
Lazio
Molise
Puglia
Sicilia
Bratislavský kraj
Západné Slovensko
País VascoMadrid
Cataluña
Andalucía
Ceuta
Stockholm
Sydsverige
-2-10123
Labourproductivity
-2 -1 0 1
Inclusiveness Composite Indicator
Czech Republic Denmark Finland Ireland
Italy Slovakia Spain Sweden
Comparing 70 regions across 8 OECD
countries
• Following the evidence presented by the other panellists,
integration of regions and cities into global value chains
improves various inclusiveness outcomes for them, thereby
improving inclusiveness within territories
• This is coherent with the evidence that by and large
productivity and inclusiveness seem to be correlated across
space
• However, it is typically cities and regions sufficiently close to
larger urban centers that get integrated into GVCs, given
the obvious importance of good transport links
• For remote (rural) regions such an integration is more
difficult, implying that the emergence of GVCs may have
contributed to widen spatial gaps between territories
Conclusion: Can integration into global trade
(and into GVCs) further spatial inclusiveness?
References
Ahrend, Farchy, Kaplanis and Lembcke (2017) “What Makes Cities More Productive? Agglomeration
Economies & the Role of Urban Governance: Evidence from 5 OECD Countries”, Journal of Regional Science,
Vol. 57(3).
Ahrend and Schumann (2014) “Does Regional Economic Growth Depend on Proximity to Urban Centres?”,
OECD Regional Development Working Papers, 2014/07.
Bachtler, Oliveira Martins, Wostner & Zuber (2017) “Towards Cohesion Policy 4.0: Structural Transformation
and Inclusive Growth”, Regional Studies Association Europe Paper for the 7th EU Cohesion Forum
Boulant, Brezzi and Veneri (2016) “Income levels and inequality in OECD metropolitan areas. A Comparative
Approach in OECD Countries”, OECD Regional Development Working Papers, 2016/06.
OECD (2015) The Metropolitan Century: Understanding Urbanisation and its Consequences,
OECD (2015) Governing the City
OECD (2016), Regions at a Glance.
OECD (2016), Making Cities Work for All: Data and Actions for Inclusive Growth.
OECD (2016), Regional Outlook: Productive Regions for Inclusive Societies.
OECD (2017) “Analysing the Local Dimension of Productivity and Inclusiveness: Untangling the Nexus”,
Background Document, Spring Meeting of the Local Economic and Employment Development (LEED)
Committee
Veneri and Ruiz (2016), “Rural-to-urban population growth linkages: evidence from OECD TL3 regions.
Journal of Regional Science, Vol. 56(1).
THANK YOU

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How can productivity be shared and inclusive across space?

  • 1. HOW CAN PRODUCTIVITY GAINS BE SHARED AND INCLUSIVE ACROSS SPACE Global Productivity Forum, Budapest Rudiger Ahrend Head of Urban Programme Centre for Entrepreneurship, SMEs, Local Development andTourism
  • 2. • Productivity – Productivity across regions and cities – Productivity performance / catching up – Drivers of catching-up – Territorial aspects of, and strategies for developing the tradable sector • Inclusiveness – Inclusiveness in regions and cities – Productivity-inclusiveness nexus across space • Conclusion: Trade / GVC integration
  • 4. Productivity differs widely within countries
  • 5. 5 Bigger cities are more productive
  • 6. City productivity increases with city size even after controlling for sorting 6 • Productivity increases by 2-5% for a doubling in population size
  • 7. Administrative fragmentation is correlated with lower city productivity 7 7
  • 9. OECD economies have converged - Within countries, regions have diverged
  • 10. The productivity gap between frontier and lagging regions has increased Notes: Average of top 10% and bottom 10% TL2 regions, selected for each year. Top and bottom regions are the aggregation of regions with the highest and lowest GDP per worker and representing 10% of national employment. 19 countries with data included. Averages of top 10% (frontier), bottom 75%, and bottom 10% (lagging) regional GDP per worker, TL2 regions 50 000 60 000 70 000 80 000 90 000 100 000 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 USD PPP per employee Frontier regions Lagging regions 75% of regions 1.6% per year 1.3% per year 1.3% per year 60% increase
  • 12. ITA DEU DNK AUT BEL CAN GRC NLD NZL FIN FRA ESP PRT USA AUS GBR SWE IRL SVN HUN CZE KOR POL SVK -2% -1% 0% 1% 2% 3% 4% 5% Catching up Diverging Keeping pace Frontier Country average productivity growth Productivity growth of the region National labour productivity growth depends on the performance of regions Annual average growth in real per worker GDP between 2000-2013 (or closest year available).  Regional catching-up can play an important role for national productivity growth
  • 13. Contribution to national labour productivity growth, 2000-12 13 Productivity and “catching up” in Hungary Percentage contribution to national GDP growth, 2000-2012 Note: Difference between national labour productivity growth as calculated with and without the indicated region. Note: The contribution is the product of a region’s GDP growth rate by its initial share of GDP. Note: See http://www.oecd.org/regional/oecd-regional-outlook-2016-9789264260245-en.htm for country pages. Frontier Catching up Keeping pace Diverging
  • 14. Contribution to national labour productivity growth, 2000-13 14 Productivity and “catching up” in Austria Percentage contribution to national GDP growth, 2000-2013 Note: Difference between national labour productivity growth as calculated with and without the indicated region. Note: The contribution is the product of a region’s GDP growth rate by its initial share of GDP. Note: See http://www.oecd.org/regional/oecd-regional-outlook-2016-9789264260245-en.htm for country pages. Frontier Catching up Keeping pace Diverging
  • 15. The drivers of regional productivity catching-up
  • 16. Good or bad productivity performance can be found for all types of regions 0 10 20 30 40 50 60 70 80 90 100 Frontier (41) Catching-up (65) Diverging (76) Keeping pace (107) % Mostly Urban (127) Intermediate (62) Mostly Rural (100) In which: 70% of mostly urban frontier regions contain very large cities in which: 75% of diverging mostly urban regions contain very large cities # regions in ( )
  • 17. Labour productivity of remote rural areas has recently declined 88% 89% 90% 91% 92% 93% 94% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Total RURAL RURAL CLOSE TO CITIES RURAL REMOTE Productivity levels of Predominantly Urban regions = 100
  • 18. Stronger intensity of tradable sectors is associated with productivity catching-up All tradable sectors, TL2 regions Notes: Tradable sectors are defined by a selection of the 10 industries defined in the SNA 2008. They include: agriculture (A), industry (BCDE), information and communication (J), financial and insurance activities (K), and other services (R to U). Non tradable sectors are composed of construction, distributive trade, repairs, transport, accommodation, food services activities (GHI), real estate activities (L), business services (MN), and public administration (OPQ). 20 25 30 35 40 45 50 Frontier Catching-up Diverging Frontier Catching-up Diverging Tradable GVA share Tradable employment share 2013 2000 %
  • 19. 19 Productivity gains in tradables are mainly within sectors -1 0 1 2 3 4 5 ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA % Tradable sectors - contribution to productivity growth Employment shifts to faster growing sectors Employment shifts to initially more productive sectors Sectoral productivity growth Productivity growth in tradable sectors
  • 20. 20 Productivity gains in non tradables are associated with sectoral shifts Only in Eastern Europe does the non-tradable sector contribute by improving productivity significantly; in some countries non-tradable productivity is even declining -1 0 1 2 3 4 5 ROU SVK EST KOR CZE HUN SVN SWE GBR AUS PRT ESP IRL NLD BEL USA AUT GRC DNK CAN NZL FIN ITA % Non-tradable sectors - contribution to productivity growth Employment shifts to faster growing sectors Employment shifts to initially more productive sectors Sectoral productivity growth Productivity growth in non-tradable sectors
  • 21. Territorial aspects of, and strategies for developing the tradable sector
  • 22. Share of total employment in clusters by type of TL2 region Mostly urban regions are those with at least 70% of its population living in Functional Urban Areas or part of its population living in a large metro area with at least 1.5 million inhabitants. Mostly rural regions have less than 50% of their population living in FUAs Source: OECD Regional Statistics and Ketels and Protsiv (2016) 0 10 20 30 40 50 60 70 80 90 100 Footwear Forestry Leather and Related Products Fishing and Fishing Products Apparel Agricultural Inputs and Services Nonmetal Mining Appliances Livestock Processing Coal Mining Furniture Water Transportation Jewelry and Precious Metals Wood Products Textile Manufacturing Electric Power Generation and Transmission Automotive Lighting and Electrical Equipment Food Processing and Manufacturing Vulcanized and Fired Materials Downstream Metal Products Paper and Packaging Metalworking Technology Plastics Metal Mining Construction Products and Services Production Technology and Heavy Machinery Upstream Metal Manufacturing Transportation and Logistics Medical Devices Upstream Chemical Products Environmental Services Hospitality and Tourism Local clusters (non-traded) TOTAL Printing Services Education and Knowledge Creation Recreational and Small Electric Goods Distribution and Electronic Commerce Downstream Chemical Products Oil and Gas Production and Transportation Performing Arts Information Technology and Analytical Instruments Tobacco Aerospace Vehicles and Defense Business Services Marketing, Design, and Publishing Insurance Services Financial Services Biopharmaceuticals Video Production and Distribution Communications Equipment and Services Music and Sound Recording Share of FTE employment in the cluster, % Mostly urban Mostly intermediate Mostly rural
  • 23. 23 Urban areas attract more knowledge- intensive firms Birth shares by sector (births by sector/total regional births) TL3 regions (15 OECD countries) 2014
  • 24. Strategies for developing the tradable sector To remain competitive in Tradable sectors there are mainly three main options: 1. Continued specialisation in Natural resources. This is typically an option for remote rural regions 2. Be integrated in Global Value Chains. Integration between manufacturing and service sectors is needed. Connectivity and proximity may favour low-density areas close to cities. Without a territorial strategy it may be difficult to benefit from GVCs for regional development. Forward and backward linkages (re- bundling) are critical to maximize value-added of FDI and creation of a network of local suppliers. 3. Develop Territorially differentiated products & services through mobilisation of local assets. Consumers may express preferences for local or traceable products, without subsidies or some form of protection.
  • 26. 26 Gini index of disposable income (after tax and transfers), 2013 Disparities of household income are large within regions, mainly in capital cities Source: OECD Income Distribution Database and OECD Regional Well-being database Eastern Slovenia Capital Oslo and Akershus Åland Prague Brussels Capital Region Bratislava Region Central Hungary Vienna Stockholm North Holland Hesse Ile-de-France Central Region Hokkaido Ticino Southern and Eastern Ontario Sicily Western Australia Ceuta AttikiNorth Island South East England Estonia Jerusalem District District of Columbia Northeastern Anatolia West Santiago Metropolitan Oaxaca 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 #REF! Regional value National average
  • 27. Larger cities are more unequal 27 Metropolitan population and income inequality, circa 2014 Metropolitan size and inequality, once controlled for income levels and country effect Brussels Antwerpen​ Liège ​ Red Deer ​ Calgary ​ ​ Lethbridge ​ ​ ​ Thunder Bay ​ Québec ​ Trois Rivières ​ Montreal ​ Sherbrooke ​ ​ Toronto ​ ​ Brant ​ Windsor ​ Iquique ​ Antofagasta ​ ​ Calera ​ ​ San Antonio ​ Rancagua ​ ​ Linares ​ ​ Temuco ​ Osorno ​ Punta Arenas Paris ​ Toulouse​ Saint-Etienne​ ​ Rouen Roma Milano Napoli ​ ​ ​ Tijuana ​ Hermosillo ​ Reynosa ​ Torreón ​ ​ León Guadalajara ​Pachuca de Soto ​ Mexico City ​ Toluca ​ ​ ​ ​ Oslo ​ Malmö ​ Portland ​​ Buffalo ​ Albany ​ Boston ​ ​ Cleveland ​ Omaha New York ​ ​ Philadelphia ​ Denver ​ ​ Cincinnati Washington ​ ​ San Francisco ​ Fresno Las Vegas ​ ​ Albuquerque Memphis ​ Los Angeles ​ Atlanta ​ Dallas Houston Miami McAllen 0.05 0.1 0.15 0.2 0.25 10 11 12 13 14 15 16 17 Ginicoefficient(componentplusresiduals) City population (natural logarithm)
  • 28. What do we know about the nexus between productivity and inclusiveness across space
  • 29. Towards a topology for regions and cities* *This section is based on preliminary work that has been prepared by the Program for Local Economic and Employment Development (LEED) and discussed by its Committee.
  • 30. Variables Weight Unemployment Equal weighting was selected after PCA assigned similar weights to all indicators Long-term unemployment Low-work intensity household Deprivation rate Poverty rate NEET rate Educational attainment: primary education Designing the Inclusiveness Composite Indicator (Work in Progress)
  • 31. Designing the Inclusiveness Composite Indicator What it does • Reduce the data from a multidimensional frame to a single dimension, simplifying its interpretation • Concentrate on the inclusion of the most disadvantaged individuals in society • Provide a way to measure regional differences within the same country and across countries What it does not do • Provide a measure of income inequality • Act as an indicator of overall well-being • Include data on access to basic services (future development)
  • 32. Praha Severozápad Hovedstaden Syddanmark Helsinki-Uusimaa Etelä-Suomi Southern and Eastern Trento Veneto Lazio Molise Puglia Sicilia Bratislavský kraj Západné Slovensko País VascoMadrid Cataluña Andalucía Ceuta Stockholm Sydsverige -2-10123 Labourproductivity -2 -1 0 1 Inclusiveness Composite Indicator Czech Republic Denmark Finland Ireland Italy Slovakia Spain Sweden Comparing 70 regions across 8 OECD countries
  • 33. • Following the evidence presented by the other panellists, integration of regions and cities into global value chains improves various inclusiveness outcomes for them, thereby improving inclusiveness within territories • This is coherent with the evidence that by and large productivity and inclusiveness seem to be correlated across space • However, it is typically cities and regions sufficiently close to larger urban centers that get integrated into GVCs, given the obvious importance of good transport links • For remote (rural) regions such an integration is more difficult, implying that the emergence of GVCs may have contributed to widen spatial gaps between territories Conclusion: Can integration into global trade (and into GVCs) further spatial inclusiveness?
  • 34. References Ahrend, Farchy, Kaplanis and Lembcke (2017) “What Makes Cities More Productive? Agglomeration Economies & the Role of Urban Governance: Evidence from 5 OECD Countries”, Journal of Regional Science, Vol. 57(3). Ahrend and Schumann (2014) “Does Regional Economic Growth Depend on Proximity to Urban Centres?”, OECD Regional Development Working Papers, 2014/07. Bachtler, Oliveira Martins, Wostner & Zuber (2017) “Towards Cohesion Policy 4.0: Structural Transformation and Inclusive Growth”, Regional Studies Association Europe Paper for the 7th EU Cohesion Forum Boulant, Brezzi and Veneri (2016) “Income levels and inequality in OECD metropolitan areas. A Comparative Approach in OECD Countries”, OECD Regional Development Working Papers, 2016/06. OECD (2015) The Metropolitan Century: Understanding Urbanisation and its Consequences, OECD (2015) Governing the City OECD (2016), Regions at a Glance. OECD (2016), Making Cities Work for All: Data and Actions for Inclusive Growth. OECD (2016), Regional Outlook: Productive Regions for Inclusive Societies. OECD (2017) “Analysing the Local Dimension of Productivity and Inclusiveness: Untangling the Nexus”, Background Document, Spring Meeting of the Local Economic and Employment Development (LEED) Committee Veneri and Ruiz (2016), “Rural-to-urban population growth linkages: evidence from OECD TL3 regions. Journal of Regional Science, Vol. 56(1).