How can we explain the high Muslim levels of poverty?

Anthony HeathCentre for Social Investigation

Nuffield College, Oxford

Poverty rates among different religious groups

Poverty defined as equivalized household income less than 60% of the national median

14

50

18

0

10

20

30

40

50

60

Documenting the problem

• Our evidence from the UKLHS is unequivocal: poverty is a much more common experience among Muslims than among other religious groups

• Long known that ethnic groups with Pakistani or Bangladeshi origins have high rates of poverty, so is this an ethnic rather than a religious phenomenon?

Poverty by ethnicity and religious affiliation

Angl Cath O C Musl Hind Sikh Jew Budd Other None All White 14 18 14 30 12 11 20 18 16 B Caribbean 20 23 30 21 19 23 B African 36 37 33 56 40 21 37 Indian 24 16 38 20 26 18 23 Pakistani 57 60 57 Bangladeshi 49 22 46 Chinese 13 30 33 27 26 Other 19 16 22 50 30 31 18 14 22 27

N 12862 6521 8395 4452 1145 570 191 237 690 25862 60925

Possible explanations

• Transitory coincidental factors reflecting migration history and recent arrival in Britain. Might be expected to disappear in time

• Factors which might be intrinsic to particular religious traditions and might persist over time

• Factors which reflect prejudice towards Muslims on the part of British employers and co-workers

Transitory factors

• Recent arrival – lack of fluency in English a major barrier to employment

• LDC origins – lower levels of educational attainment restrict people to disadvantaged jobs

• Foreign qualifications mean lower returns to education

• Lack of knowledge about the UK labour market• History of migration to declining Northern

industrial areas

Possible intrinsic factors

• Family values – caring responsibilities might lead to lower female rates of economic activity, higher family size

• Religious involvement might lead to bonding rather than bridging social capital

• Mismatch between available work arrangements and religious preferences

• Mismatch between available childcare arrangements and religious preferences

Prejudice, discrimination and other barriers

• Discrimination by employers both in taking on Muslim workers and promoting them

• Cold reception from non-Muslim co-workers – the chill factor

• Pre-labour market discrimination, eg in elite higher education institutions

Practical difficulties in researching these potential explanations

Ideally one would use a range of research methods, eg • field experiments to detect discrimination, • in-depth interviews to explore the chill factor,• social network analysis on bridging and

bonding social capital, • Attitude or ethnographic research to explore

family values

A first approximation using statistical analysis of the UKLHS

Restricted to available measures in the UKLHS, which are largely proxies rather than direct measures of the explanatory concepts. We distinguish• Confounding factors such as age• Transitory factors such as generational status, fluency in

English, educational qualifications• Possible intrinsic/religion-related factors such as religiosity,

attendance at place of worship, number of children• Possible indicators of labour market barriersMeasures are undoubtedly sub-optimal

Transitory factors % with the characteristics Means 1st gen 2nd gen 3rd gen Primary

or less Degree Difficulty

with English

Anglican 2 5 92 37 16 0.01 Catholic 22 18 60 28 23 0.20 Other Christian 13 8 79 26 25 0.08 Muslim 58 35 7 27 28 1.05 Hindu 74 24 2 16 48 0.59 Sikh 45 51 4 22 28 0.62 Jew 9 28 63 20 44 0.02 Buddhist 58 10 32 21 45 1.02 Other 25 11 64 25 23 0.10 None 5 9 86 22 21 0.03 All 11 10 79 27 22 0.10

Religion-related factors Means % reporting Children HH

size Civic Female

employed Weekly

attendance Great

importance Anglican 0.32 2.48 0.97 42 10 17 Catholic 0.50 2.86 0.84 52 28 28 Other Christian 0.40 2.66 1.16 44 32 39 Muslim 0.98 4.62 0.45 28 41 59 Hindu 0.43 3.57 0.54 53 21 32 Sikh 0.61 4.24 0.55 53 33 39 Jew 0.49 2.95 1.14 42 17 25 Buddhist 0.46 2.68 0.81 60 14 46 Other 0.43 2.58 1.05 42 39 54 None 0.48 2.85 0.66 57 1 3 All 0.45 2.82 0.81 50 12 16

Labour market factors % reporting Means Unemployment Working

class Self-reported discrimination

Earnings (£)

Anglican 3 33 0.28 8,910 Catholic 6 36 0.96 11,334 Other Christian 4 30 1.51 10,162 Muslim 11 37 4.92 7,399 Hindu 6 30 6.96 12,800 Sikh 7 39 5.83 10,961 Jew 8 12 0.21 14,267 Buddhist 6 32 5.96 12,484 Other 6 34 1.17 8,108 None 8 35 0.64 12,257 All 6 33 0.98 10,934

In summary

• Muslims share many of the transitory disadvantages with Hindus and Sikhs, so these factors unlikely to explain their higher poverty rates

• Muslims do stand out with respect to religiosity, number of children and women’s economic activity – NB religiosity seems to persist across generations, the other variables less so

• Muslims do stand out with respect to unemployment rate and earnings, though surprisingly not with self-reported discrimination or occupational level

Statistical analysis of the risks of poverty

We use standard statistical techniques to attempt to see how far these sorts of factor account for excess Muslim rates of poverty1. We first take account of confounding factors and ethnicity2. Then the transitional factors – generation, education and

language difficulties3. Next number of children, household size and economic

activity4. Separate model for attendance, religiosity (NS) and civic

engagement5. Final model adds social class, earnings, discrimination (NS)

and unemployment

Results of the regression analysis: average marginal effects

Model 1:

Religion+ controls

Model 2: M1+English, edu and gen

Model 3: M2+HH & inactivity

Model 4: M3+social capital

Model 5: M4+labour market

Anglican (ref) Catholic 0.023*** 0.019** 0.014* 0.012 0.011 Other Christian -0.011 -0.002 -0.005 -0.002 0.006 Muslim 0.200*** 0.160*** 0.092*** 0.085*** 0.073*** Hindu 0.073*** 0.059** 0.058** 0.050** 0.033 Sikh 0.103*** 0.062* 0.038 0.032 0.019 Jew -0.003 0.028 -0.008 -0.009 -0.029 Buddhist -0.006 -0.025 -0.015 -0.016 -0.030 Other 0.036* 0.041* 0.031 0.031 0.019 None 0.020*** 0.014** 0.014** 0.009* 0.006 Pseudo R2 0.052 0.097 0.171 0.179 0.275 N 59,319 58,765 58,398 58,398 49,075

The key findings

• After taking account of confounding factors, the Muslim poverty rate is 20 percentage points higher than that of Anglicans

• Each block of factors (especially the second) explains part of this excess poverty rate

• In the case of the other religions, the predictors successfully explain their initial excess poverty rates, but for Muslims a 7 point gap remains

Do the mechanisms work differently for Muslims?

• In general processes operate similarly for all the religious groups

• Muslims are distinctive in the size of the effects of generational status

• But this largely re-states the problem

So how might we explain Muslim exceptionalism?

• Geographical segregation and concentration? But also applies to Sikhs so cannot explain the difference

• Replenishment of Muslim communities? Largely specific to replenishment from Pakistan, which the measure of ethnic origins will have taken into account

• Islamophobia and the ‘chill factor’? The most plausible speculation – supported by our current research on attitudes to Muslim migrants

Some grounds for optimism

• Transitional factors mean that we expect some convergence over time and generations in poverty rates

• Also generational change in family size and women’s economic activity – not actually all that intrinsic to Islam

• Considerable educational progress, with Muslim women in particular catching up rapidly

• Religiosity itself not a cause of poverty (either generally or among Muslims)

But important unanswered questions

• Not clear why Muslims have such low levels of civic engagement (also shown in other data sources)

• Not clear why Muslim earnings are so low (again shown in other data sources)

• Not clear how to test whether the chill factor really is a major part of the explanation

Policy responses?

• Tackling discrimination in universities and employment

• Tackling poor economic environment, especially in Northern England

• Tackling barriers to women’s employment (eg mismatch with respect to childcare or employment conditions)

• Countering Islamophobia in the media