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18-19 March 2008 UPTAP Workshop

Neighbourhoods and the creation, stability and success of

mixed ethnic unions

Zhiqiang FengPaul Boyle, Maarten van Ham, Gillian Raab

linking lives through time www.lscs.ac.uk


Why study mixed-ethnic unions?

• Geographical Segregation– Numerous studies have ignored mixing within

households/families

• Government actively promotes integration of ethnic minorities

• Mixed-ethnic unions – Demonstrate break-down of ethnic barriers and are

suggestive of degree of ethnic integration in a society– Numbers are small but increasing– Create new minority groups-mixed ethnic groups


Proportions of mixed-unions by ethnic group

England and Wales, Data Source: 1991 and 2001 HHSARs

0

10

20

30

40

50

60

70

80

90

white

black

car

ibbean

black

afri

can

black

oth

er

india

n

pakis

tani

bang

ladesh

i

chine

se

othe

r-asia

n

othe

r-oth

er

male 1991

male 2001

female 1991

female 2001


Theories

• Assimilation– Most assimilated groups more likely to cross ethnic

lines to out-partner• Demography

– Sex ratio– Relative size

• Social exchange– Lower status majority members partner higher status

minority members• Segregation

– Reduce opportunity to meet potential partners


Existing Studies in Britain

• Data sources– Labour Force Surveys (Jones 1984, Coleman

1985, 2004)– The Fourth National Survey of Ethnic

Minorities (1994) (Muttarak 2003)– Census

• Household SARs (Berrington 1996, Model & Fisher 2002)

• ONS LS (Muttarak 2005)


Studies in Britain

• Most are descriptive

• They tend to use cross-sectional analyses


Some results from previous studies

• Positive effects:

– Age– Second generation– Males– Educational attainment– Higher social class


Some results from previous studies

• Negative

– Size of ethnic group– Residential segregation– Cultural distance


Issues with cross-sectional analysis

• We don’t know when or where marriage / cohabitation occurred– Prevalence vs incidence

• Pre-marriage / cohabitation conditions unknown– Socio-economic situations may change after

marriage / cohabitation– Not suitable for causal inference


Longitudinal analysis

• Identify people who were already in Britain before partnering occurred

• Have data on pre-marriage / cohabiting situations

• First British study to use the ONS LS and SLS to identify geographical influences on mixed-ethnic unions


Why study neighbourhood effects?

• Neighbourhoods may be important locations for social contacts

• Places reflect social relations and constitute and reinforce social relations (Delaney 2002)

• Places can be racialised – predominantly ethnic neighbourhoods may create “local cultures” which discourage mixed-ethnic unions


Why study neighbourhood effects?

• Previous studies find mixed-ethnic couples are more likely to live in mixed-ethnic neighbourhoods

• However, it is not clear whether this is because mixed-ethnic couples form there or move there after marriage / cohabitation

• Most studies use cross-sectional data so it is difficult to study event sequences


Objectives

1. Measure the growth of mixed-ethnic couples and their changing geographical distribution between 1991 and 2001

2. Test whether living in a mixed-ethnic neighbourhood makes it more likely that people will end up in mixed-ethnic couples

3. Test whether people in mixed-ethnic couples are more likely to move into mixed-ethnic neighbourhoods

4. Test whether mixed-ethnic couples are more likely to dissolve than single-ethnic couples


Objectives

5. Test whether mixed-ethnic couples are less likely to dissolve if they live in mixed-ethnic neighbourhoods

6. Test whether living in a less deprived neighbourhood makes it more likely that people will end up in mixed-ethnic couples

7. Test whether people in mixed-ethnic couples are more likely to move into less deprived neighbourhoods


Data source

• ONS LS– Longitudinal 1971-2001– 1% sample of England and Wales (500,000)

• SLS– Longitudinal 1991-2001– 5.3% sample of Scottish population (265,000)


Definition of ethnic groupsPresentation groupin the study 1991 (ETHNIC9) 2001(ETHGRP0)

White (W) White BritishIrishOther white

Black (B) Black-Caribbean Black-Caribbean Black-African Black-African Black other Other Black Black & White White & Black Caribbean

White & Black African*Asian (A) Indian Indian

Pakistani PakistaniBangladeshi Bangladeshi

Other Asian (OA) Chinese ChineseOther Asian Other Asian

Others (O) Other ethnic group: White & Asiannon-mixed origin Other mixedOther ethnic group: Other ethnic groupmixed origin


White Black Asian Other Asian

White WW WB WA WOA

Black BB BA BOA

Asian AA AOA

Other Asian

OAOA

Classifications of mixed-ethnic unions


Number of mixed-ethnic unions England & Wales

Mixed-ethnic unions 1991 2001

White / Black (WB) 1231 1737White / Asian (WA) 641 902White / Other Asians (WOA) 643 730White / Others (WO) 998 1770Total 3513 5139


Mixed ethnic neighbourhoods

Relative size

minority population / white population

Exposure index

Diversity

Shannons entropy

N

iiii pwMmI

1

)]/(*)/[(


Mixed ethnic neighbourhoods

• Continuous?

or

• Dichotomous?

• Use different forms in different models?


Methodology

• Objective 1 (growth of mixed-ethnic unions, 1991 vs 2001)

– ONS LS + SLS – Descriptive – Logistic / log-linear models


Methodology

• Objective 2 & 6 – whether mixed-ethnic neighbourhoods or less deprived neighbourhoods have positive effects on formation of mixed-ethnic unions

– ONS LS data, 1981 vs 1991, 1991 vs 2001– Whether people aged 6+ & single in 1981, ended up

being married to, or cohabiting with, people from another ethnic group in 1991

– Repeat for 1991-2001– Logistic & Heckman selection model controlling for

probability of partnering


Methodology

• Objectives 3,4,5,7 – whether mixed-ethnic couples

– More likely to move to mixed ethnic neighbourhood– More likely to dissolve than single ethnic couples– Less likely to dissolve if living in mixed-ethnic neighbourhoods

– More likely to move into less deprived neighbourhoods • ONS LS 1991-2001• Sample: People who were married or cohabiting in 1991• Logistic model of the probability of these events in 2001


Individual variables

Gender

Age

Urban/Rural

Social class

Highest level of education

Economic position

Number of dept. children

Marital status

Religion (2001)

Geographic region

Housing tenure

Country of birth

Ethnicity


Work so far

• Literature review

• Research design

• SLS proposal approved

• Data request sent to ONS LS