Abstract
Gender inequality has always been of vital significance in studies on the Chinese labourmarket, and recently, the motherhood penalty has drawn increasing attention. This research
aims to first explore the complexity of gender income inequality in China from an
intersectionality perspective and then pay particular attention to the motherhood penalty. It
begins with a discussion of gender income inequality, the motherhood penalty, and
intersectionality studies in the broader literature, and in particular, the Chinese context, and
explains how the used data and methods help to explore the overarching research questions.
Following that, this research contributes to the understanding of income inequality by applying
an innovative intersectionality quantitative method, the multilevel analysis of individual
heterogeneity and discriminatory accuracy (MAIHDA). The results confirm that the
intersectional effects among the social categories could shape individuals’ income and provide
new evidence that women stand in disadvantaged positions in the labour market.
Methodologically, it also confirms that MAIHDA is feasible in applying gender and inequalities
studies in China. Furthermore, efforts have been made to investigate the correlation between
the motherhood penalty and the ownership sectors, and the results provide new evidence that
women experience less gender inequality in government institutions and state-owned
enterprises than in the private sector. Finally, it also focuses on the labour market outcomes
of those who have just married or become mothers. The results indicate that high-income
women tend to have a more substantial motherhood income penalty, and late marriage could
bring women penalties on income. This thesis contributes to the study of gender inequality,
economic inequality, the motherhood penalty, and the practice of intersectionality theory in
China.
Date of Award | 1 Oct 2024 |
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Original language | English |
Awarding Institution |
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Supervisor | Wenfei Winnie Wang (Supervisor) & Maria Fannin (Supervisor) |