Presenation by Rudiger Ahrend, Head of Economic Analysis, Statistics and Multi-level Governance, CFE, OECD.

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

42. https://www.oecd.org/governance/oecd-regions-
and-cities-at-a-glance-26173212.htm
http://www.oecd.org/publications/productivity-
and-jobs-in-a-globalised-world-9789264293137-
en.htm
https://www.oecd-ilibrary.org/employment/job-
creation-and-local-economic-development-
2018_9789264305342-en
Underlying Publications: