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Social and Ethnic ‘Segregation’

Manifestations, Understanding, Impacts,

Responses

Sako Musterd

Urban Geography / Urban Studies

University of Amsterdam

The Netherlands Seminar on Mobility,

Segregation and

Neighbourhood Change

Tartu, 14-15 March 2013

2

Four issues

1. Segregation research: a changing focus: – from classic description and index construction of

segregation to analysis of inequality and concentrations;

– from a focus on residential segregation to analysis in non-residential domains (work, leisure, public space related).

2. How can we understand the variation of inequalities?

3. What can we say about the effects or impacts of urban inequality?

4. What are the typical policy responses to urban inequality in European cities?

0 20 40 60

Copenhagen 1st quintile

Amsterdam 1st quintile metro

Bern unemployed

Berlin hh income < € 900

Birmingham income support

Milan blue collar workers

Manchester income support

Manchester unemployed

Amsterdam 1st quintile

Berlin hh income > € 3500

Lille unemployed vs employed

Rotterdam 1st quintile

Amsterdam 5th quintile metro

Oslo social assistance

Birmingham unemployed

Leeds unemployed

Sheffield unemployed

Milan professionals

Copenhagen 10th decile

Amsterdam 5th quintile

Rotterdam 5th quintile

USA Portland OR MSA poor

Antwerp 'poor'

USA 100 largest cities poor

USA Rochester NY MSA poor

1a

Social

inequality in

selected EU

cities;

segregation

indexes as

classic tools

for describing

urban

inequality

These overviews provide much information

• Low levels and lower in EU than in the US

• State dependent: higher in Belgium, low in Denmark and the Netherlands

• City dependent: high in Leeds, lower in Manchester

• Group dependent: higher levels in higher social classes; lower class in EU still in one system with middle class

Social Segregation Patterns

(problems with indicator selection, but

still information rich)

Amsterdam as an example

Social Segregation Pattern in 1960 Social rank (pca on ‘classic’ indicators)

Social Segregation Pattern in 2007 University education

Social Segregation Pattern in 2007 m2 Price for Housing

Social

Segregation

Pattern in

2012 test scores for entry in

secondary education

9

Low

Medium

High

10

Micro-level Social Segregation Pattern 2011 concentrations high (red) and low (blue) real

estate values in housing

http://regiomonitor-uva.everimap.com/

Ethnic

inequality:

‘classic’

segregation

measures

(D) and

recent

change (difference between

years mentioned)

-40 -20 0 20 40 60 80 100

Cologne Italians 1990-2000

Cologne Yugoslavs 1990-2000

Rotterdam Surinamese 1994-2009

Cologne Turks 1990-2000

Barcelona Peruvians 1995-2003

Amsterdam Surinamese 1994-2009

Birmingham Indians 1990-2000

Amsterdam Moroccans 1994-2009

Amsterdam Turks 1994-2009

Rotterdam Moroccans 1994-2009

Rotterdam Turks 1994-2009

London Black Carribean 1990-2000

London Indians 1990-2000

Leeds Pakistani 1990-2000

Barcelona Moroccans 1995-2003

Birmingham Bangladeshi 1990-2000

London Bangladeshi 1990-2000

Leeds Bangladeshi 1990-2000

most recent year

difference

Sources: Arbaci (2007); Friedrichs (1998) ; Malheiros (2002a, b); Martori et al. (2005); Musterd (2005) (1996);

Peach (1996); Stillwell & Phillips (2006)

1b

Development

of index of

dissimmilarity

in several

European

cities

12

Again these overviews provide much

information

• Varied levels, usually lower in EU than in the US

• State dependent: higher in UK and Belgium, lower in Germany and the Netherlands

• City dependent: higher in Leeds, lower in Birmingham

• Group dependent: higher levels for Bangladeshi, lower for Indian origin.

Changing

Patterns of

Segregation

Moroccan

origin

1973

1981

1990

Moroccan 2011(similar classification relative to average)

15

Type of index

is relevant:

D dissimilarity

upper half

xPx* isolation

lower half

1994-2009 0,00

0,10

0,20

0,30

0,40

0,50

0,60

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Amsterdam Rotterdam

Surinamese

Antillean

Turkish

Moroccan

Surinamese

Antillean

Turkish

Moroccan

Amsterdam Rotterdam

Micro-level Ethnic Segregation Pattern 2011 concentrations of Moroccan (2-4sd; >4sd)

17

Here too, a move away from classic

measures of segregation to micro-

level data used for constructing

concentrations and for describing

and analysing them

18

19

Concentrations:

Surinamese in 2009

Total in the city: 68761 (9.09%)

N Surinamese per area: >= 50

Perc. Surinamese in

concentrations >= 17.83

110 concentrations with (total):

90087 inhabitants

30227 Surinamese (33.6%)

30227: 43.9% of all Surinamese

562.4 hectares

Amsterdam, Surinamese origin, 2009, n > 50, > 2sd

20

Concentrations:

Surinamese in 2009



Perc. Surinamese in

concentrations >=26.52


67539 inhabitants



419.4 hectares

Amsterdam, Surinamese origin, 2009, n > 50, > 4sd

21

Concentrations:

Surinamese in 2009



Perc. Surinamese in

concentrations >=50%


3245 inhabitants


1848: 2.7 % of all Surinamese

27.9 hectares

Amsterdam, Surinamese origin, 2009, n > 50, > 50%

22

Concentrations:

Surinamese in 2009



Perc. Surinamese in

concentrations >=60%


753 inhabitants



6.1 hectares

Amsterdam, Surinamese origin, 2009, n > 50, > 60%

Concentrations (4sd+) of ethnic categories in

Amsterdam 2009

1 2 3 4 5 6= (4/5)*100 7=(4/2)*100

Ethnic

category

Category’s

city

population

Percentage

of

category

in city

Category’s

concentration

population

Total

concentration

population

Percentage of

category in

concentrations

Category’s

concentration

population

relative to

category’s

city

population

Turkish 39654 5.2 16102 68532 23.5 40.6

Moroccan 68099 9.0 32446 91235 35.6 47.6

Surinamese 68761 9.1 23511 61710 38.1 34.2

Antillean 11559 1.5 2010 16895 11.9 17.4

Share of four population categories in the city

of Amsterdam, 2000-2011, based on country of

origin (1st and 2nd generation) (column 3)


Amsterdam 2009

1 2 3 4 5 6= (4/5)*100 7=(4/2)*100

Ethnic

category

Category’s

city

population

Percentage

of

category

in city

Category’s

concentration

population

Total

concentration

population

Percentage of

category in

concentrations

Category’s

concentration

population

relative to

category’s

city

population

Turkish 39654 5.2 16102 68532 23.5 40.6

Moroccan 68099 9.0 32446 91235 35.6 47.6

Surinamese 68761 9.1 23511 61710 38.1 34.2

Antillean 11559 1.5 2010 16895 11.9 17.4

Percentage of each of the population categories

relative to total population, in concentrations of

these population categories (column 6) 2000-11


Amsterdam 2009

1 2 3 4 5 6= (4/5)*100 7=(4/2)*100

Ethnic

category

Category’s

city

population

Percentage

of

category

in city

Category’s

concentration

population

Total

concentration

population

Percentage of

category in

concentrations

Category’s

concentration

population

relative to

category’s

city

population

Turkish 39654 5.2 16102 68532 23.5 40.6

Moroccan 68099 9.0 32446 91235 35.6 47.6

Surinamese 68761 9.1 23511 61710 38.1 34.2

Antillean 11559 1.5 2010 16895 11.9 17.4

Percentage of each of the population categories

that lives in concentrations of these population

categories (column 7) (2000-11)

30

How to understand urban inequalities?

• Globalisation

• Internationalisation

• Economic restructuring

• Path dependency (chain migration); urban structure ((un) fit for current urban economies; multi-layered or single-layered)

• Welfare regime type and change

• Behaviour, culture, tolerance, discrimination, political discourse, choice

produces

inequality

polarisation

mismatch

2

Structural

Pathways

Institutional

Other

31

Context:

levels of

social

inequality,

within and

between

states.

Gini-index 2008,

black: sharp rise

in past decade

0 5 10 15 20 25 30 35 40

Slovakia

Sweden

Denmark

Hungary

Czechia

Austria

Finland

Luxembourg

Netherlands

France

Belgium

Germany

Ireland

Spain

Italy

Estonia

Poland

Greece

United Kingdom

Bulgaria

Romania

Portugal

Latvia

Lithuania

32

Levels of social inequality, 2008

Polarisation or integrated social classes share of total income per income decile, The Netherlands, 2010

33

34

Welfare

states and

levels of

social

inequality in

European

cities

Segregation

index low

ses

residual

extensive

hybrid universal

Source: Domburg 2005

35

Segregation and concentration

receive much attention because of

expected negative effects on

participation

3

36

Urban inequalities, effects on

participation; theory

Mechanisms

• Socialisation, role models, peer groups

• Stigmatisation

• Social networks

• Opportunity for encountering ‘others’

In Europe, hypotheses

• Lower levels of segregation small effects

• Perhaps even positive effects

37

Effects of urban inequalities, methods

• Qualitative in-depth research

• Quantitative large datasets, longitudinal

• Both rich in terms of variables

• Detailed geo-coding available

• Quantitative research using techniques

that make efforts dealing with selection

effects

• Quantitative research enables detection of

non-linearities, thresholds, etc.

Examples of results of some own (co-researched) large-scale longitudinal, individual level studies in Sweden and The Netherlands on the impact of neighbourhood composition (various sizes and compositions (ethnic, social, tenure)) on social outcomes (mostly income) 38

39

Musterd, S. (1996) Ruimtelijke segregatie en sociale effecten. Inaugurele rede. Assen: Van Gorcum.

Ostendorf, W., S. Musterd & S. de Vos (2001) Social mix and the neighbourhood-effect: policy-ambition and

empirical support. Housing Studies, vol. 16, no. 3, pp. 371-380.

Musterd, S., W. Ostendorf & S. de Vos (2003) Environmental Effects and Social Mobility. Housing Studies. Vol.

18 6. pp. 877-892.

Andersson, R., Musterd, S., Galster, G. and Kauppinen, T. (2007) What Mix Matters? Exploring the

Relationships between Individual’s Incomes and Different Measures of their Neighbourhood Context.

Housing Studies, 22 (5), pp. 637-660.

Musterd, S., Andersson, R., Galster, G. and Kauppinen, T. (2008) Are Immigrants’Earnings Influenced by the

Characteristics of their Neighbours? Environment and Planning A. 40, pp. 785-805.

Galster, G., Kauppinen, T., Musterd, S. and Andersson, R. (2008). Does Neighborhood Income Mix Affect

Earnings of Adults? A New Approach using Evidence from Sweden. Journal of Urban Economics. 63, pp.

858-870

Musterd, S. (2008) Residents Views on Social Mix: Social Mix, Social Networks and Stigmatisation in Post-war

Housing Estates. Urban Studies, Volume 45, No. 4, pp. pp. 897-915.

Galster, G., R. Andersson & S. Musterd (2010) Who Is Affected by Neighbourhood Income Mix? Gender, Age,

Family, Employment and Income Differences. Urban Studies. 47(14), pp. 2915-2944.

Andersson R. & S. Musterd (2010) What Scale Matters? Exploring the Relationships between Individuals’ Social

Position, Neighbourhood Context and the Scale of Neighbourhood. Geografiska Annaler: Series B, Human

Geography 92 (1), pp. 23-43.

Sykes, B. & S. Musterd (2011) Examining Neighbourhood and School Effects Simultaneously: What Does the

Dutch Evidence Show? Urban Studies, 48(7), pp. 1307-1331.

Musterd, S., Vos, S. de, Das, M. & Latten, J.J. (2012). Neighbourhood Composition and Economic Prospects: A

Longitudinal Study in the Netherlands. Tijdschrift voor Economische en Sociale Geografie, 103(1), 85-100.

Musterd, S., G. Galster & R. Andersson (2012) Temporal dimensions and measurement of neighbourhood

effects. Environment and Planning A 44(3) 605 – 627.

Andersson, R., S. Musterd & G.Galster (2013) Neighbourhood Ethnic Composition Effects On Immigrant

Incomes. Accepted by Journal of Ethnic and Migration Studies.

A selection of (mostly recent) neighbourhood effect studies (co) authored

Sweden

1.Concentrations of low income households have negative effects on individual’s social mobility.

2.Effects are generally stronger in metropolitan than

in non-metropolitan areas and stronger for males than

for females.

3.Own group ethnic concentrations can initially pay

dividends for immigrants, but these benefits turn into

disadvantages over time, after approx. two years.

4.The impact of other immigrants turned out positive

only if unemployment levels are very low.

40

Sweden continued

5.For males who are not employed full time, or have a

low income, middle income neighbours have a positive

marginal impact (relative to either high- or low-income

neighbours).

6.Increases in middle-income neighbours will have a

negative effect on high-income males if they substitute

for high-income neighbours.

7.Smallest scale areas (10,000 m2) have strongest

effects.

8.Recent, and continued cumulative exposure yields

stronger associations than lagged, temporary ones.

9.There is distinct time decay (but some persistence)

in the potential effects after exposure ceases.

41

The Netherlands

10.Higher median neighbourhood income is positively related to individual income prospects.

11.Income mix in the neighbourhood likely has a small positive effect.

12.A high share of rented dwellings relates to higher income gain than a high share of owner-occupied dwellings (possibly because the rented sector functions as a springboard rather than a trap).

42

43

Typical policy responses to urban

inequalities in European cities

• Fear for lack of integration and assumed

relation with spatial inequalities

• Call for forced interventions to obtain

reduction of segregation

• Policies aimed at creating balanced

communities and social mix

• Instruments: urban restructuring and mixed

tenure, mixed qualities and mixed house

prices, gentrification

4

Theoretical considerations; Empirical findings

Macro and managerial; social mix policy …

1.prevents the development of uncontrollable

neighbourhoods and rising segregation

2.is a ‘conspiracy against the poor’: it produces

gentrification, favours the affluent and displaces the poor

44

L. Lees (2008)

“[i]t is ironic that a process that results in

segregation and polarization – gentrification – is

being promoted via social mix policies as the

‘positive’ solution to segregation…the rhetoric

of social mixing tends to conceal the inequalities

of fortune and economic circumstance that are

produced through the process of gentrification”

45


Macro and managerial; social mix policy …

1.prevents the development of uncontrollable

neighbourhoods and rising segregation

2.is a ‘conspiracy against the poor’: it produces

gentrification, favours the affluent and displaces the poor

3.helps to improve local conditions and service levels

4.creates negative spill-over effects (displacement)

5.reduces stigmatisation through social mix

6.increases stigmatisation through selection of areas

7.reduces the accumulation of neighbourhood problems

8.improves neighbourhood liveability

46


Micro and individual; social mix policy …

1.helps the poor to realize social mobility through

socialisation, role models, peers, and ‘better’ social

networks through weak ties

2.stimulates economic, social and cultural participation

and integration

3.destroys individual’s local social networks; spatial

proximity is no guarantee for social integration

4.frustrates individual’s behaviour – especially of those

who can afford – to sort into relatively homogeneous

neighbourhoods

5.neglects metropolitan and state level impacts on

social compositions 47

48

Comments on predominant policy

interventions

• Social mix may indeed help social prospects

• Social mix may be good for some, but harming others.

• Segregation and ‘social mix’ are often weakly defined, if at all, and mostly used as metaphores, which blurs discussions.

• Fear often drives policies, which is a bad thing.

• Social mix does not work when micro-level social distances and social inequality are too large.

• Social mix may create injustice effects (due to reduction of affordable housing).

49

Conclusions and discussion • Differences between cities relate to urban histories,

welfare regimes,and opportunities to adapt to structural economic transformation and globalisation.

• These differences produce different levels of social/ethnic (spatial) inequality.

• Which results in governmental intervention, strongest in universal welfare states

• Caution is required: – Interventions are good for some but bad for others

– Don’t pathologise the poor or social housing; Lupton and Tunstall (2008, p. 114):

“[i]t is a short step from there to the assumption that the solution is to reduce the proportion of poor people, rather than to address structural inequalities or inject additional resources to provide the services that people need”

50

Conclusions and discussion …Continued

• Caution is required: – Interventions are good for some but bad for others

– Don’t pathologise the poor or social housing

– Spatial sorting is a strong process, difficult to engineer

– Interventions may add to stigma

– Interventions may produce negative externalities (demolition, spillovers and fear)

• Moderate segregation associates with universal welfare states; however, almost all of these states appear to be heading towards more neo-liberal models

• Consider the potential of structural and institutional factors and interventions at various scales aimed at services delivery (schools) and enhanced individual labour market participation and social mobility

51

Conclusions and discussion …Continued

• Avoid cynical attitudes and neglect of potential impact of

concentrated poverty; this may produce more

segregation and marginalisation of the poor

• Recognise the complexity and reciprocal relations and

(social) ties between people, place, space and scale

• Address more comprehensive measures of individual

and neighbourhood well-being

• Avoid classifying poor neighbourhoods as a problem and

middle-class as a solution

52

Sako Musterd

Urban Geography /Urban Studies

University of Amsterdam

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