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My research focuses on questions in labor economics and organizational economics across the economic development space. In my projects, I collaborate with large organizations to study the overarching question of why some people reach their potential in the labor market while others do not, to identify the frictions that prevent this, and explore how to alleviate them. My proposed research agenda over the course of the fellowship is to complete, and submit for publication, three working papers. The first of these provides evidence of the critical role of managers in matching workers to jobs within the firm using the universe of personnel records on 200k employees over ten years of a multinational firm. Leveraging exogenous variation induced by the rotation of managers across teams, I find that successful managers cause workers to reallocate within the firm through lateral and vertical transfers. This leads to large and persistent gains in workers' career progression and productivity. The results imply that the visible hands of managers match workers' specific skills to specialized jobs, leading to an improvement in the productivity of existing workers that outlasts the managers' time at the firm. The second paper continues the study of leadership in a very different context: Myanmar's labor movement. We conduct multiple field experiments by collaborating with a confederation of labor unions as it mobilizes garment workers in the run-up to a national minimum wage negotiation. First, we document that union leaders differ from the other workers along several traits that psychologists and sociologists have associated with the ability to influence collective outcomes. Second, by randomly embedding leaders in group discussions, we find that they help coordinate workers' views to build consensus around the unions' preferred minimum wage levels. Third, by conducting a mobilization experiment that features collective action problems, we show that leaders play a coordinating role also for workers' actions. The third paper starts with the fact that women's labor force participation varies widely across countries at every level of development. We ask how this affects gender diversity among employees, gender gaps, and firm productivity using five years of personnel records on over 100K employees of a multinational firm combined with the female to male labor force participation rate in the 101 countries where the firm operates. Structural estimates show that in a counterfactual world with no gender-specific barriers to labor force participation, firm productivity would be 32% higher for the same level of employment and the same wage bill. The findings suggest that selection is a powerful lens to understand the link between diversity and productivity. I also aim to prepare draft and publish the work on "Wage Setting in a Multinational Firm" as an AEA Papers & Proceedings publication, where I consider the role of multinationals in wage setting and how the wage policy is shaped by headquarter's strategy versus local adaptation, and how the worker skill level matters for this choice of "adopt versus adapt". In addition I will take forward three related projects that look at the role of cultural diversity in teams, of purpose workshops to improve worker motivation on the job and of volunteering initiatives for workers at risk of displacement to help them envision different career paths. I intend to closely interact with researchers at the IFS to expand my skill set, build networks also with the policy communities and brainstorm on these ideas and how to push them forward into complete academic papers.

The UK is increasingly ethnically diverse. There have been significant improvements in the economic and educational success of some ethnic minorities in recent years, but not all have shared in this success, and nor has educational success always translated into gains in the labour market. Substantial ethnic inequalities in multiple domains across the life course persist, and many continue across generations. The experience of different minority groups has varied in terms of whether and how far their economic outcomes have converged to those of the majority. There have been equally important differences within minority groups, between men and women and by social class background. Even as the extent of ethnic inequalities are recognised to be of public and political salience, the causes and solutions remain contested. Despite an important body of existing qualitative and quantitative research from multiple disciplines, substantial gaps in knowledge and for robust policy recommendations remain. The ambition of this project is to establish new, authoritative and policy relevant evidence and understanding in this contested area. We will do so by providing a detailed account of how ethnic economic inequalities emerge, evolve and are maintained across the life course at a level of detail and in ways not previously possible. We use newly available administrative and linked data tracking different life stages, alongside longitudinal survey data and new data collection. Developing an integrated programme of work across domains allows robust conclusions to be drawn about what drives disadvantage for different ethnic groups, and for men and women and different social classes within groups. We consider issues of identity and categorisation, the extent to which individuals identify with specific groups, the attitudes of the majority, and implications for how we understand ethnic inequalities. Looking over the course of life, we examine educational pathways and outcomes, contact with the criminal justice system, entry into the labour market and working careers, and the accumulation of wealth and its intergenerational transmission. We shed light on inequalities in school performance, the link between school exclusions and contact with the criminal justice system, the pathways into higher education and vocational training, and the impact of policy reforms. We look more broadly at how those leaving full-time education with different levels of qualifications fare in terms of the jobs they enter, their career progression, and the benefits their jobs provide in terms of training, pension rights and employment security. We examine how levels and sources of wealth differ across groups, and how they are differentially transmitted across generations. The comprehensive data we use enables us to provide innovative insights for policy and inform public debate and narratives on these issues by showing what factors are important at different stages, examining the role of individual and families, institutions such as schools, firms and employers, geographical location, networks and peers, as well as stereotyping and discrimination. The inter-disciplinary led team will build cumulative evidence to provide clear insights for policy as to what can mitigate inequalities and what policy levers are more or less effective. Given the complexity and salience of the issues involved, we will engage in deliberative discussions with stakeholders, the public, practitioners and policy-makers to inform and communicate reliable insights into the causes of systematically unequal outcomes, shaping understanding of effective ways and times at which to intervene. We will build capacity for a new generation of researchers to study and engage with these issues. Ultimately, we hope this will leave the UK better able to ensure economic opportunities are provided to all, harnessing all the talents of its increasingly diverse population.

The Covid pandemic brought about an unprecedented labour market shock. Job opportunities in sectors like hospitality disappeared overnight, whilst opportunities expanded in other sectors like driving and healthcare. This radical restructuring of the economy called for a new way of measuring the labour market prospects facing individuals that captured their widely-varying ability to adapt to the shock by moving into alternative lines of available work. Motivated by this, we developed a new worker-specific measure of labour market opportunities. Our measure is based on historical patterns of job-to-job moves, which we use to infer how suitable a given worker is for different types of jobs. Combined with high-quality data on vacancy postings, this allowed us to look beyond aggregate measures of labour market performance and quantify important differences in the labour market prospects facing different types of workers over the pandemic (Costa Dias et al 2021, Joyce et al 2022). While our innovation was triggered by the pandemic, the usefulness of our method is much more general and wide-ranging. Our method links the state of the labour market in one part of the economy to the rest of the economy, meaning that it could be used to answer questions like: how do shocks in retail affect wage pressures and career progression for delivery drivers? How do changes in the wider labour market affect the ability of the social care sector to recruit and retain workers? Our method further provides insights into the extent to which workers' skills align with the skills demanded by employers - the extent of labour market 'mismatch' - which has implications for productivity and economic growth. For example, if the older workers who have recently left the labour market were to come back, to what extent could this ease labour shortages in specific occupations? Where in the economy are skills shortages most acute, and what is the economic cost of mismatch in terms of aggregate productivity? The aim of this project is to extend and refine our new method, grounding it in a theoretical search and match model, and demonstrate its applicability to substantive questions and its advantages over traditional methods. We will refine our index to capture variation in opportunities arising from competition for jobs from different types of jobseekers, as well as variation in the skills demanded by employers (captured by our current index). We will then demonstrate its utility by applying it to empirical, policy-relevant questions like the ones above - in particular, in identifying the variation in labour market opportunities across workers and over time, and in quantifying the extent and economic cost of labour market mismatch in the economy. A key part of embedding this innovation within future research and statistical practice will be dissemination and engagement with others - not only after the project is done, but during its production, helping us to maximise its usefulness. The main target audiences will include the research community, statistical practitioners (e.g. ONS), and policy-makers - since the ultimate purpose of our innovation is to better guide policy-making, and through achieving impact on policy-makers we will further highlight the potential of our innovation within future research.

Geographical inequalities in the UK are large and persistent, and high by international standards. Previous research shows that most of the differences in earnings across places can be attributed to differences in skills: high-skilled people, who would earn more wherever they worked, are concentrated in certain places. Understanding why skills differ so much, and the link between people and places, is therefore key to understanding geographical inequalities and making progress on the levelling-up agenda. I propose to study the interplay between place, geographical mobility, social mobility and skills using rich administrative data in the Longitudinal Education Outcomes (LEO) dataset. This project will address the following research questions: 1. How do labour market opportunities facing young people differ across England? I will start by estimating earnings premiums across Travel-to-Work Areas, which capture how much a given individual can expect to earn in a certain location relative to some reference location. I will go beyond static, average effects by examining differences in career progression across places; persistent effects on career trajectories of having lived in London or other cities; the dispersion in expected earnings (risk) across places; and differences in place effects by educational background. 2. How mobile are young people in England, and how does this affect inequalities between places and socio-demographic groups? I will investigate how mobile young people in England are and the extent to which they move to places offering better labour market opportunities, documenting differences between groups in terms of educational, socio-economic and demographic background. I will examine the extent to which differences in migration patterns between groups can be explained by differences in place effects - for example, if high-skilled people gain more in earnings from moving to London - or whether they are likely to reflect differences in preferences or constraints, particularly the role of housing costs. I will decompose how much of the earnings differences between groups is due to differences in their migration patterns, and how much of geographical differences in earnings is due to selective migration after acquiring education. 3. Do differences in proximity to universities and local returns to higher education affect the educational choices of people growing up in different places? I will consider how local opportunities shape young people's decisions to acquire education in the first place, focusing on two channels. First, I will examine whether students who grow up in places that are far from (any, or high-quality) universities are less likely to go to university, conditional on prior attainment and their parental and school background, or settle for courses for which they are overqualified. Second, I will examine how returns to education vary across the country and whether those who grow up in places where degrees are not rewarded in the labour market are less likely to pursue higher education. In both cases I will consider whether the relationship is stronger for less mobile groups. I will work with policymakers (see letters of support) to co-design the research and ensure that both the findings and the potential of LEO data are well understood within government. This research will help policymakers advance the levelling up agenda, by (i) highlighting where a lack of universities or local economic opportunities constrains educational attainment; (ii) identifying socio-demographic groups who are particularly constrained by where they grow up, and would benefit from policies to reduce barriers to mobility; and (iii) shedding light on whether local skills provision will be effective at improving local economic outcomes, or whether - because of mobility and incentives to invest in education - skills policy must work alongside wider policies to equalise labour market opportunities.