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Gender gaps in labour market outcomes remain persistent features of economies worldwide and show substantial spatial variation.
My PhD develops a comprehensive body of evidence on the magnitude, spatial variation, and drivers of gender inequality across labour markets in the UK. It consists of three empirical chapters, each employing secondary data and established econometric methods.
- Gender Pay Gaps Across Areas in Britain
Research Question: Why do gender pay gaps vary across areas in Britain?
Data: Annual Survey of Hours and Earnings 2022 (secure)*
Methodology: Oaxaca-Blinder decompositions
Findings:
There is considerable variation in Gender Pay Gaps across areas in Britain.
This variation is obscured at more aggregate geographical levels.
Gender differences in where individuals work account for most of the observed variation across areas.
Inequality is relatively consistent across areas in Britain
Not all variation in this measure of inequality can be solely attributed to discrimination
*This work is based on data from the Annual Survey of Hours and Earnings, produced by the Office for National Statistics (ONS) and supplied by the UK Data Archive. It is accessed via the Secure Data Service (SDS) and I am grateful for their support. These data are Crown Copyright and have been used by permission. The use of these data in this work does not imply the endorsement of ONS or the SDS in relation to the interpretation or analysis of the data. This work uses research datasets which may not exactly reproduce National Statistic aggregates.
2. Commuting and the Gender Pay Gap in the UK
Research Questions: What drives the Gender Pay Gap in Commuting in the UK? To what extent does commuting drive the Gender Pay Gap in the UK?
Data: Quarterly Labour Force Survey 2022 - 2023 (End User Licence)
Methodology: Oaxaca-Blinder decomposition, Two-Stage Least Squares (2SLS), Instrumental Variables
Findings:
There is a substantial raw mean commuting gender gap in the UK. Key determinants of commute time include educational attainment, occupation, and region, with limited influence from household characteristics.
A large share of the commuting gender gap remains unexplained, likely reflecting unobserved preferences, unmeasured characteristics, or stochastic factors.
To address potential endogeneity between commuting and wages, I instrument individual commute time using the average commute time of workers in the same one-digit SIC industry sector.
The analysis suggests that gender differences in commute times explain 10.14% of the raw Gender Pay Gap - a contribution comparable to the impact of public sector employment on the GPG.
These findings indicate that, even as commuting behaviours evolve in the post-pandemic context, commuting remains an important yet relatively overlooked driver of the Gender Pay Gap, with implications for understanding wage-setting mechanisms and the spatial inequalities that sustain gender gaps in the labour market.
3. Evaluating the Childcare Offer for Wales on Employment Rates
3. Evaluating the Childcare Offer for Wales on Employment Rates
Research Question: How does the Childcare Offer for Wales influence parental employment rates?
Data: Annual Population Survey 2013-2022 (secure)*
Methodology: Regression Discontinuity Design; Staggered Difference-in-Differences
Findings:
Both analytical approaches suggest that eligibility for 30 hours free childcare in Wales has had minimal impact on parental employment rates and usual hours worked.
Several fcators may explain these limited effects:
Parental employment rates in Wales were already high before the Offer's introduction.
The timing of the Offer may be too late to prevent some parents from leaving the labour force following childbirth.
The Offer may not be sufficiently generous or flexible to enable parents' return to work.
Wales already had a well-established private childcare market prior to the policy.
Statistical power may also be limited due to small sample sizes.
An evaluation of the Offer must consider outcomes beyond labour market responses, including supporting child development and school readiness.
The research highlights the ongoing need for policymakers to consider the design and objectives of childcare policies and underscores the importance of developing comprehensive data infrastructure to systematically collect data on childcare policy uptake, participation rates, and broader socio-economic outcomes.
*This work is based on data from the Annual Survey of Hours and Earnings, produced by the Office for National Statistics (ONS) and supplied by the UK Data Archive. It is accessed via the Secure Data Service (SDS) and I am grateful for their support. These data are Crown Copyright and have been used by permission. The use of these data in this work does not imply the endorsement of ONS or the SDS in relation to the interpretation or analysis of the data. This work uses research datasets which may not exactly reproduce National Statistic aggregates.
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