LFS/APS user meeting 2 Dec 2008 1 Is ethnicity or religion more important in explaining inequalities...

LFS/APS user meeting 2 Dec 2008 1

Is ethnicity or religion more important in explaining

inequalities in the labour market?

Jean MartinAnthony Heath

University of OxfordKarin Bosveld

Office for National Statistics


Previous research

• Lots of studies have looked at disadvantage by ethnic group

• ‘Ethnic penalty’ – differences which persist after controlling for differences between ethnic groups in age, qualifications etc.

• Few studies have looked at religion as well

• Not based on recent data/restricted to certain ethnic groups


Why might religion be important?

• An indication of cultural differences within an ethnic group

• Direct impact through religious beliefs &/or practices

• Lack of social networks linking to wide range of employment

• Chill factor

• Basis for discrimination by employers


Research questions

• Are there differences between religious groups that are consistent across ethnic groups?

• Are effects less marked among those born in UK than among first generation immigrants?

• Are there differences between men and women?


Identification problem

• Can’t always distinguish ethnicity and religion

• Eg All Pakistanis and Bangladeshis are Muslim

• Won’t know whether differences are due to culture or religion narrowly defined


Why use the APS?

• Interest in minority ethnic groups and religious differences within them means need very large sample

• Census/LS data now quite old – not enough of new immigrant groups like Black Africans

• APS has year of arrival in UK• But doesn’t have a measure of English language

proficiency and doesn’t code foreign qualifications


APS under special licence

• Need for fullest detail of ethnic and religious groups

• Plans for including detailed geographical area information (but not done yet)

• Disclosure risks


Data for analysis

• Combined 2005 & 2006 APS

• Working age population

• Excluding FT students

• Excluding 2005 boost sample which wasn’t asked about qualifications

• 172814 men and 171147 women


Men WomenEthnic group N % N %White British 152019 88.0 148870 87.0Other White 8652 5.0 8695 5.1White & Black Caribbean 287 0.2 334 0.2White & Black African 108 0.1 136 0.1White & Asian 201 0.1 243 0.1Other mixed 217 0.1 284 0.2Indian 3151 1.8 3114 1.8Pakistani 1966 1.1 2095 1.2Bangladeshi 675 0.4 789 0.5Other Asian 1175 0.7 1500 0.9Black Caribbean 1149 0.7 1507 0.9Black African 1234 0.7 1476 0.9Chinese 475 0.3 662 0.4Other ethnic group 1505 0.9 1442 0.8

172814 100.0 171147 100.0


Men WomenReligion N % N %Christian 128986 74.6 133272 77.9Buddhist 461 0.3 575 0.3Hindu 1711 1.0 1618 0.9Jew ish 592 0.3 533 0.3Muslim 4584 2.7 4713 2.8Sikh 939 0.5 916 0.5Other religion 1357 0.8 1397 0.8No religion 34184 19.8 28123 16.4

172814 100.0 171147 100.0


Religion

Ethnic group Christian Buddhist Hindu Jewish Muslim SikhOther

religion No religionWhite British 121481 162 11 412 151 16 1034 25603Other White 6863 22 1 75 214 2 125 1393White & Black Caribbean 226 1 2 4 101White & Black African 95 12 2 27White & Asian 114 4 2 39 4 6 74Other mixed 176 10 2 1 15 11 69Indian 325 9 1329 6 462 850 56 77Pakistani 27 5 3 2020 1 29 10Bangladeshi 5 5 772 1 6Other Asian 606 254 211 1 232 34 31 131Black Caribbean 1313 5 4 1 7 26 151Black African 1153 1 7 1 258 1 17 38Chinese 203 104 1 4 23 327Other ethnic group 685 3 40 33 525 8 32 116

Women


Religion



Women


Women Religion



Identification problem


Outcome variables

• Proportion economically inactive

• Proportion unemployed of the economically active

• Not employment rates because affected by ratio of inactive to unemployed which varies by ethnic group


Independent variables

• Separate analyses for men and women• Age and age squared• Qualifications:

– degree, other, none• Whether born in UK; if not, age at arrival (<16,

16-30, over 30)• For women: whether married, whether has

dependent children

• 2nd generation = born in UK or arrived before age 5


Logistic regression models

Model 1: ethnicity alone

Model 2: reduced ethnic group and religion variables to deal with sparse cells – 7 ethnic and 3 religion groups

Model 3: combined ethno-religious group variable

All with the same control variables


Controls for age, age squared, highest quals, born in UK, married, dependent children

Ethnic group 3 Combined ethno-religious groups

Christian Muslim No religionBuddhist Hindu Sikh Jew ish Other religion

White British 0.00

Other White -0.05

White and Black Caribbean 0.45

White and Black African -0.18

White and Asian 0.17

Other Mixed 0.03

Indian 0.20

Pakistani 1.62

Bangladeshi 1.71

Other Asian 0.27

Black Caribbean/other black -0.06

Black African -0.08

Chinese 0.06

Other ethnic group 0.71

Main effects

1 Ethnicity only

2 Main effects

Women' s economic inactivity: log-odds





White British 0.00 0.00

Other White -0.05 -0.07


White and Black African -0.18


Other Mixed 0.03

Indian 0.20 -0.25

Pakistani 1.62

Bangladeshi 1.71

Other Asian 0.27 -0.04

Black Caribbean/other black -0.06 -0.03

Black African -0.08 -0.33

Chinese 0.06 -0.07

Other ethnic group 0.71 0.20

Main effects 0.00 1.46 0.22

1 Ethnicity only

2 Main effects






White British 0.00 0.00 0.00 1.27 0.23 0.17 0.28 0.21

Other White -0.05 -0.07 -0.05 1.46 0.04 0.12

White and Black Caribbean 0.45 0.54 0.40

White and Black African -0.18 -0.04

White and Asian 0.17 0.07

Other Mixed 0.03 -0.06

Indian 0.20 -0.25 -0.24 1.13 0.28 0.19 0.00

Pakistani 1.62 1.73

Bangladeshi 1.71 1.84

Other Asian 0.27 -0.04 -0.23 1.15 0.76 0.47 0.43

Black Caribbean/other black -0.06 -0.03 -0.03 0.21

Black African -0.08 -0.33 -0.40 1.36

Chinese 0.06 -0.07 0.08 -0.03 0.59

Other ethnic group 0.71 0.20 0.19 1.66 0.21


1 Ethnicity only

2 Main effects



Economic inactivity

• Muslim women very much more likely to be economically inactive

• Other Asian non-Christians less likely to be active than Christians

• Black African very diverse: Christians more likely to be active than white British Christians but Muslims less likely





White British 0.00

Other White 0.00


White and Black African 0.82


Other Mixed 0.10

Indian 0.33

Pakistani 1.03

Bangladeshi 1.07

Other Asian 0.27

Black Caribbean/other black 0.51

Black African 0.54

Chinese 0.15

Other ethnic group 0.83

Main effects

1 Ethnicity only

2 Main effects

Women' s unemployment: log-odds





White British 0.00 0.00

Other White 0.00 -0.02


White and Black African 0.82


Other Mixed 0.10

Indian 0.33 -0.03

Pakistani 1.03

Bangladeshi 1.07

Other Asian 0.27 0.05

Black Caribbean/other black 0.51 0.53

Black African 0.54 0.49

Chinese 0.15 -0.03

Other ethnic group 0.83 0.61


1 Ethnicity only

2 Main effects






White British 0.00 0.00 0.00 1.37 0.31 0.81 -0.22 0.61

Other White 0.00 -0.02 0.06 0.58 0.08 -0.52

White and Black Caribbean 0.53 0.91 -0.10

White and Black African 0.82 0.99

White and Asian 0.51 0.06

Other Mixed 0.10 0.50

Indian 0.33 -0.03 0.22 0.85 -0.27 0.38 0.44

Pakistani 1.03 1.14

Bangladeshi 1.07 1.21

Other Asian 0.27 0.05 -0.20 0.92 0.78 0.51 0.83

Black Caribbean/other black 0.51 0.53 0.50 0.93

Black African 0.54 0.49 0.48 1.32

Chinese 0.15 -0.03 0.02 0.13 0.83

Other ethnic group 0.83 0.61 0.61 1.55 0.81


1 Ethnicity only

2 Main effects



Women’s unemployment

• Muslims significantly more likely to be unemployed in all groups (except Other White)

• Among Indians Muslims, Hindus and Sikhs more likely to be unemployed than Christian or no religion

• Coeffs for Black Caribbean and Black African show strong ethnic effect on unemployment




White British 0.00 0.00 0.00 -0.14 0.01 0.01 0.04 0.01

Other White 0.09 0.11 0.10 -1.46 0.18 -0.12


White and Black African 0.11 0.04

White and Asian 0.03 -0.04

Other Mixed 0.01 -0.17

Indian 0.01 0.07 0.79 -0.29 -0.23 -0.36 0.16

Pakistani -0.26 -0.28

Bangladeshi -0.68 -0.68

Other Asian -0.22 0.04 0.23 -1.15 -0.76 -0.47 -0.43

Black Caribbean/other black 0.06 0.05 -0.02 0.32

Black African -0.06 0.33 0.25 -1.36

Chinese 0.15 0.07 -0.08 -0.04 -0.59

Other ethnic group -0.03 -0.20 -0.17 -0.17 -0.21

Main effects 0.00 -0.31 0.01

1 Ethnicity only

2 Main effects

Difference in log-odds between all women and 2nd generation: economic inactivity


Second generation women economic inactivity

• 2nd gen less different from women overall for most groups

• Muslims still more likely to be economically inactive but coefficients reduced

• Economic inactivity increased for Indian and Black African Christians




White British 0.00 0.00 0.00 -0.14 0.01 0.05 -0.21 0.01

Other White 0.08 0.09 0.08 -0.58 0.18 0.52


White and Black African 0.29 -0.99

White and Asian -0.35 -0.53

Other Mixed 0.32 0.29

Indian -0.14 -0.10 0.14 -0.21 -0.32 -0.27 -0.08

Pakistani -0.24 -0.24

Bangladeshi -0.55 -0.56

Other Asian 0.22 -0.05 0.20 -0.92 -0.78 -0.51 -0.83

Black Caribbean/other black 0.07 0.08 0.06 0.14

Black African 0.15 -0.49 0.21 -1.32

Chinese 0.21 0.03 -0.02 0.45 -0.83

Other ethnic group -0.09 -0.61 -0.17 0.39 -0.81

Main effects 0.00 -0.30 0.01

1 Ethnicity only

2 Main effects

Difference in log-odds between all women and 2nd generation: unemployment


Second generation women unemployment

• 2nd generation women generally less likely to be unemployed than women in general but some exceptions

• Muslims still more likely to be unemployed but coefficients reduced

• Black Caribbean and Black Africans still more likely to be unemployed


Conclusions

• Both ethnicity and religion are important in explaining differences in economic inactivity and unemployment rates among women

• Muslim women more likely to be inactive, or if active, to be unemployed than other religions

• Black Caribbean and Black African women more likely to be unemployed, irrespective of religion

• Main differences still apparent in the second generation


But….

• We don’t know what the mechanisms are for the differences

• Haven’t controlled for all the factors which might be relevant (eg language)

• Cultural differences might explain differences in economic activity but not clear how they would explain differences in unemployment

• Clear that there are major barriers to employment for Muslim women

LFS/APS user meeting 2 Dec 2008 1 Is ethnicity or religion more important in explaining inequalities...

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