Income inequality in OECD countries is at its highest level for the past half century. Check out the Mayors Innovation Studio presentation from CityLab Washington DC, 27 October 2019

1. Aziza
Akhmouch
HEA D O F CITIES, U RBA N PO LICIES, A N D
SU STA IN A BLE DEVELO PMEN T DIVISIO N O ECD

2. Aziza Akhmouch
Understanding the
challenge around
the world
HEA D O F CITIES, U RBA N PO LICIES, A N D
SU STA IN A BLE DEVELO PMEN T DIVISIO N O ECD

3. INEQUALITY
Analytical Framework
ECONOMIC
MOBILITY
Income
Beyond
income
Earnings
mobility
Educationalmobility
Occupationalmobility
Health
Education
Job access
Housing
Absolute
mobility
Relative mobility

4. Income inequality in
OECD countries is at its
highest level for the past
half century.

5. Average income of the
richest 10% is about
10 times
that of the
poorest 10%
40%
an increase of
in a single generation

6. But inequalities are even
more acute in cities.

7. Maximum Metropolitan Area
Huge gaps in disposable income between metropolitan areas
Source: OECD (2018), OECD Regions and cities at a glance 2018
SanFrancisco
GreaterPerth
Stockholm
Calgary
Linz
London
Gent
Munich
Paris
Utrecht
Helsinki
Bologna
Tokyo
Lisbon
Santiago
Hermosillo
Hidalgo
GreaterAdelaide
Malmö
Sherbrooke
Vienna
Cardiff
Leipzig
Saint-Etienne
Groningen
Palermo
Naha
Porto
Concepción
Orizaba
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
USA (93) AUS (6) SWE (3) CAN (34) AUT (3) GBR (21) BEL (4) DEU (26) FRA (15) NLD (6) FIN (1) ITA (13) JPN (76) PRT (2) CHL (3) MEX (38)
USD
Minimum Metropolitan Area Country average
Liège

8. Income levels differ between city core & commuting zone
Source: OECD (2018), OECD Regions and cities at a glance 2018
Maximum Metropolitan Area Minimum Metropolitan Area Average of Metropolitan Areas
SanLuisPotosi
Santiago
Roma
GreaterBrisbane
Lisbon
Stockholm
Nantes
Wake
Dresden
Cardiff
Amsterdam
Graz
Brussels
BenitoJuarez
Valparaíso
Catania
GoldCoast
Porto
Malmö
Saint-Etienne
NewHaven
Augsburg
KingstonuponHull
sGravenhage
Wien
Antwerp
-60
-40
-20
0
20
40
60
80
100
120
140
MEX (38) CHL (3) ITA (13) AUS (6) PRT (2) SWE (3) FIN (1) FRA (15) USA (93) DEU (26) GBR (21) NLD (6) AUT (3) BEL (4)
%DIFFERENCEOFINCOMEINTHECOREWITH
RESPECTTOTHATINTHECOMMUTINGZONE

9. People living in larger cities
have a higher level of
disposable income
but larger cities also have
higher levels of income inequality

10. Huge disparity in access to green space across metropolitan areas
Source: OECD (2018), Regions and cities at a glance
Maximum Minimum Average of metropolitan areas
Lisboa
Graz
Lublin
Basel
Liège
Catania
Brno
Dresden
Rennes
Leeds
Gothenburg
LasPalmas
Amsterdam
Luxembourg
Ljubljana
Oslo
Budapest
Tallinn
Dublin
Bratislava
Athens
Helsinki
Copenhagen
Porto
Vienna
Lódz
Genève
Antwerp
Milan
Prague
Ruhrgebiet
Paris
Liverpool
Malmö
Madrid
TheHague
5060708090100
LUX(1)
SVN(1)
NOR(1)
PRT(2)
AUT(3)
POL(8)
CHE(3)
BEL(4)
ITA(11)
CZE(3)
HUN(1)
DEU(21)
FRA(15)
EST(1)
IRL(1)
SVK(1)
GBR(14)
GRC(1)
FIN(1)
SWE(3)
ESP(8)
NLD(5)
DNK(1)
%

11. Inequality vs. mobility
Unequal societies
stifle upward economic
mobility, making it harder
for individuals to close
the gap.

12. What would it take to
close the gap?

13. BEL GBR DEU CHE FRA SVK CAN HUN IRL
Upward Mobility
80
70
60
50
40
30
20
10
0
KOR USA SVN NLD FIN CZE NOR ISL POL ESP ITA PRT AUS
%
ISR OECD DNK EST SWE
(26)
Downward Mobility
Source: OECD calculations based on the ESS all seven waves for European countries (2002-2014), PSID for the United States
(1999-2013), CNEF for Australia and Korea (2000-14) and the GSS cycle 15 for Canada.
Absolute upward occupational mobility is more
common than downward mobility

14. 21
18
10
7
18
13
0
10
20
30
40
50
60
70
AUS
ISL
ITA
CAN
CZE
GBR
ESP
EST
NOR
DEU
KOR
DNK
IRL
PRT
SVK
FIN
CHE
POL
ISR
BEL
NLD
SWE
FRA
SVN
HUN
USA
OECD26
%
OECD Manager(↗) Manual Worker
Source: OECD calculations based on the ESS all seven
waves for European countries (2002-2014), PSID for the
United States (1999- 2013), CNEF for Australia and Korea
(2000-14) and the GSS cycle 15 for Canada.
chance of growing up
to become a manager
(OECD average)
If your parents are managers, you have…
48%

15. 0
10
20
30
40
50
60
ISL
CAN
NLD
CHE
ISR
NOR
GBR
DEU
SWE
DNK
FRA
SVN
IRL
BEL
FIN
ITA
KOR
POL
EST
ESP
SVK
USA
CZE
HUN
AUS
PRT
OECD(26)
%
70
OECD Manual Worker(↗) Manager
Source: OECD calculations based on the ESS all seven waves for
European countries (2002-2014), PSID for the United States
(1999-2013), CNEF for Australia and Korea (2000-14) and the
GSS cycle 15 for Canada.
If your parents are manual workers, you have…
37%
24%
chance of growing
up to become a
manual worker
(OECD average)
of chance of
growing up to
become a manager
(OECD average)

16. 60% 80% 100%
At least one parent
has attained tertiary
At least one parent
has attained secondary
Neither parent has attained
upper secondary
0% 20% 40%
Lower secondary or less
Upper secondary & post-secondary, non-tertiary
Tertiary - Bachelor, Master, Professional, and Research degree
Source: OECD calculation using
Programme for the International
Assessment of Adult Competencies
(PIAAC) 2012 and 2015
OECD average
Likelihood of educational attainment by parental background
Only 12/100
persons with
low-educated
parents obtain a
tertiary degree
or higher

17. 40
35
30
25
20
15
10
5
0
45%
Bottom Quartile (↗) Top Quartile
Source: OECD calculations based on the GSOEP for Germany, the PSID for the United States, the ECHP and EU-SILC 2011 module for Austria, Belgium,
Denmark, France, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain and the United Kingdom, the MHP and the EU-SILC 2011 module for
Hungary, CASEN 2009 for Chile.
“Sticky floor” for sons of bottom earnings fathers

18. %
60
50
40
30
20
10
0
Bottom Quartile Top Quartile (↗)
Source: OECD calculations based on the GSOEP for Germany, the PSID for the United States, the ECHP and EU-SILC 2011 module for Austria, Belgium,
Denmark, France, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain and the United Kingdom, the MHP and the EU-SILC 2011 module for
Hungary, CASEN 2009 for Chile.
“Sticky ceiling” for sons of top earnings fathers

19. Why does economic mobility matter?
Lack of upward mobility prospects affects…
Economic growth Economic cohesion,
participation & trust
Life satisfaction &
well-being

20. Public resources +
well-targeted policy
measures
Why does economic
mobility matter for Mayors?
meaningful impact
on residents’
upward mobility

21. Data shows that local
policies impact
economic mobility
EDUCATION
LABOUR &
SKILLS
URBAN
ENVIRONMENTS

22. Data shows that local
policies impact
economic mobility
URBAN
ENVIRONMENTS
Affordable quality housing in
high opportunity areas
Accessible and reliable transport
for the underserved population
Safe environment and healthy
conditions for residents
Expanded access to public
spaces

23. Data shows that local
policies impact
economic mobility
EDUCATION
Make quality early childhood
education and care
accessible & affordable
Strengthen the link between
school and home
Reduce social and spatial
segregation in education
Prevent early drop-outs
Invest in physical space
Focus on quality teachers

24. Data shows that local
policies impact
economic mobility
LABOR &
SKILLS
Grant disadvantaged
youth a right start in
the labour market
Address in-work poverty
Opportunities for skill
development for jobs of
the future

25. Where does your
city stand?

26. Average income inequality is around 30%
higher than the OECD average
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
VilniusFreetownHalifax
Saskatoon
Plymouth,UK
Trenggalek
Anchorage,AK
SiouxFalls,SD
Tacoma,W
A
Topeka,KSGary,IN
FortCollins,CO
GrandRapids,MIPrague
Albany,NY
St.Paul,MN
Syracuse,NY
SanJose,CA
Oakland,CA
Seattle,W
A
CostaMesa,CAAkron,OH
Albuquerque,NM
Columbia,SC
Paterson,NJ
Quito
Durham
,NC
Louisville,KYTulsa,OK
Providence,RI
PompanoBeach,FL
SantaFe,NM
Lexington,KY
Little
Rock,AR
Birmingham,AL
BatonRouge,LAHelsinki
Philadelphia,PA
W
ashington,DC
Atlanta,GAFortaleza
SanJuan,PuertoRicoReykjavik
City value OECD average (2016)
Gini index for income, 0 denotes the lowest inequality and 1 the highest inequality
Giniindex
*Iceland
*National average only

27. • Looking at the data of the
GINI inequality in your city,
and the cities in the room,
what surprises you?
• You identified one
opportunity area earlier
today. What other policy
areas might you need to
target to be in a better
position in 2030?

28. Thank you