Abstract/Summary

This thesis comprises of four empirical chapters which present an exploration of economic inequalities among men and women in White, Indian, Pakistani and Bangladeshi ethnic groups. Most ethnic minority groups on average have lower income than Whites, but there are also large differences in income within groups. The first empirical chapter investigates the extent to which total inequality is a consequence of income differences between and within population subgroups stratified by ethnicity and gender, more specifically whether total income inequality in the UK is explained more by income differences between ethnic groups, or a result of income differences within each ethnic group, taking gender into consideration. Following Shorrocks (1984), generalised entropy measures of income inequality are decomposed - first by ethnic group, second by ethnic group and gender - into two components: inequality between and within subgroup populations. Using UKHLS data from 2009-2010 for the UK, this chapter demonstrates that within-group income inequality, rather than between-group income inequality, is the main contributor to overall income inequality. The between-group inequality component for subgroup population decomposition by both ethnicity and gender accounts only for a very small part of the overall inequality. Income inequality among White, Indian, and Pakistani men are larger than income inequality for women in the same ethnic groups, whilst the opposite is true for the Bangladeshi ethnic group. In the second empirical chapter we employ regression-based decomposition techniques to explore the factors that contribute to explaining UK inequality among men and women within the Indian, Pakistani, Bangladeshi ethnic groups, alongside the White majority, all of which we found in the previous analysis to be characterised by large income inequality . Following Fields (2003), we measure the relative contributions of a set of factors to inequality in individual incomes using UKHLS data for 2009-2010. The explanatory variables are introduced in an income generating model and factor inequality weights are estimated to quantify the contribution of variables (education, employment status, unemployment, children, marital status, household size, housing tenure, region) to total income inequality. These variables account for between 34% and 53% of income inequality across our groups. The results suggest that the most relevant factors in explaining the observed inequality are employment status, education, number of dependent children and age; moreover, all factors are found to have an inequality-increasing effect for men and women across all ethnic groups. The remaining empirical chapters move away from decomposition analysis of income inequality to explore economic inequalities among couples. More specifically, the third empirical chapter considers gender inequalities in the division of housework among White and ethnic minority couples., always using UKHLS data for 2012-2013. We consider three main theoretical approaches: time availability, resource bargaining and gender identity, each theory describing a different mechanism through which the household divides housework. We find that resource bargaining theory is a consistent predictor of female share of housework among ethnic groups. We also find evidence of differences in the way the theories apply to the experiences of White and ethnic minority couples; the magnitude and significance of theories is different across couples in each ethnic group. Using a gender attitude score as a proxy for gender roles theory, we find that gender roles theory reflects the experience of White couples, where male gender attitudes have a larger effect on the division of housework compared to female gender attitudes. Importantly, we also identify differences in the significance of theories: whilst the gender role theory reflects the experiences of the Indian group, it does not reflect the experiences of Pakistani and Bangladeshi couples; similarly, time availability theory reflects the experiences of Pakistani couples but not that of Indian and Bangladeshi couples. The final empirical chapter aims to assess the gender-ethnicity inequality in financial decision making within the couple, again among the White, Indian, Pakistani, and Bangladeshi groups in the UK and using UKHLS data for 2012-2013. We find that ethnic minority women are less likely to take control of financial decision-making responsibility compared to White women, whilst ethnic minority men are more likely to take control of financial decision making compared to White men. Resource bargaining theory is found to be an important predictor of how White, Indian, and Pakistani ethnic groups share financial decision-making responsibility. Relative earnings are used as proxy to measure how financial decision-making responsibility is allocated as the wife’s earnings increase relative to her husbands. Higher female earnings relative to their husband increases the likelihood of the wife making main financial decisions and reduces the likelihood of the husband making main financial decisions for White and Indian couples. The effect of gender roles is consistent among White and Indian couples in determining financial decision-making, although gender roles theory appears to have a greater implication for Indian than for white couples for financial decision-making. Our theoretical proxies explain the least variation in financial decision-making for Bangladeshi couples, although the small sample size of the Bangladeshi couples is a likely contributor.