Sujetos obligados y responsables, bases y tipos de

RQ1. What are the key explanatory variables for economic inactivity in the looking after home and family category amongst British Muslim women?

The answer for this question will be sought using binary and multivariate analysis of the range of variables identified as significant, or potentially significant, predictors of

economic inactivity in the literature review along with control variables. This phase of the project aims to make an original contribution to the statistical body of knowledge on the labour market outcomes of British Muslim women by focusing on the LAHF

category of economic inactivity. The multivariate modelling is expected to bring greater insight into the LAHF category due to the inclusion of measures of social capital, socio-economic status and religiosity in a single statistical model.

50 Figure 3.2 EMBES Survey Questions on religious affiliation, ethnicity and economic activity

The statistical modelling will include two stages: the sample for Stage A will include all ethnic minority (EM) women and will control for religious belonging; Stage B will include only Muslim women and will control for ethnicity. The extent of the Muslim penalty on LAHF will be assessed in Stage A and ethnic variations in the Muslim penalty will be assessed in Stage B. The two stages of modelling follow the method of Heath and Martin’s (2013) examination of the effect of religious belonging on some of the observed ethnic penalties in labour outcomes.

EMBES Question [survey question code] Response Categories Firstly, please could you look at this card

and tell me which of these best describes your ethnic group?

9 Asian or Asian British – Indian 10 Asian or Asian British – Pakistani 11 Asian or Asian British – Bangladeshi 12 Any other Asian/Asian British background BLACK

13 Black or Black British – Caribbean 14 Black or Black British – African

15 Any other Black/Black British background 16 Chinese

17 Any other ethnic group DK REF

Do you regard yourself as belonging to any particular religion?

Which of the descriptions on this card best applies to you? [eq65_1]

1 In paid work

2 In full-time education

3 Unemployed for six months or more 4 Unemployed for less than six months 5 Permanently sick or disabled

6 Retired

7 Looking after the home

8 Doing something else (WRITE IN) DK REF

51 Heath and Martin (2013) pooled the results of the 2005 and 2006 Annual Population Survey (APS). Along with other standard control variables such as age, education and gender, they controlled for marital status, dependent children and migrant generation.

They created two models: Model 1 excluded Muslim Pakistanis or Muslim

Bangladeshis due to ethnicity or religion being “inextricably confounded” for these groups, thereby examining only ethnic groups with religious diversity; Model 2

contained all ethno-religious groups, including Pakistanis and Bangladeshis (Heath and Martin 2013, p.1012). They found evidence for an overarching Muslim penalty within all ethnic groups for the outcome of economic inactivity amongst women (Heath and Martin 2013).

The statistical analysis will answer the research questions within the parameters set by the inclusion of selected independent variables. The selection of independent variables is driven by the theory and evidence evaluated in the literature review. Qualitative findings may bring additional explanatory variables to light, or, illuminate the reasons why some of the independent variables are significantly positively, or negatively, associated with LAHF.

Theme 2: Generational Change

The quantitative phase of research will address RQ2a and the qualitative phase will address RQ2b. Heath reminds us that the EMBES is a cross-sectional survey and as such, any conclusions on generational change should be treated as provisional due to the potential of within-group, or birth cohort, differences in each migrant generation (Heath 2014). There is little evidence of generational improvements in labour market outcomes for Muslims in Britain, particularly those of Pakistani and Bangladeshi ethnicities (Heath and Li 2008; Heath and Martin 2013; Cheung 2014).

It is useful to note how generational change has been measured in other studies. For example, Cheung (2014) used the EMBES 2010 dataset to assess generational change in labour market outcomes. She defined the first-generation as those who arrived in the UK at 12 years or older, the second-generation were all those who were born in Britain or arrived before the age of 11 (Cheung 2014). The results of this analysis showed that that substantial ethnic and religious penalties did not vary by generation and that Muslim women suffered the largest penalties (Cheung 2014).

Overall, there is a low response rate to questions about parental country of birth (30%) in the EMBES 2010, so it is not possible to identify third or 2.5 generation cases. The RQ2a. Is there evidence of generational change in the LAHF outcome?

RQ2b. Do the causes and experiences of economic inactivity differ by migrant generation or cohort?

52 large number of invalid (missing/not known/refused) responses to the question on parental country of birth is interesting and unexpected, as it is not a sensitive question in the same way that household income or even religious affiliation might be. The response rate to the question about the respondent’s own country of birth is better at 70%. Due to reduction in sample size, once all females of working age who are not either economically active or LAHF are excluded, it is likely that a more fine-grained analysis of generation may not be possible.

Figure 3.3 EMBES 2010 Survey Questions on Migrant Generation EMBES Question [survey question

code]

Response Categories

In which country […] were:

You [bq102_1]