Research
I am in the 5th year of an Economics PhD at Cornell University, where I am finishing my dissertation focusing on labour economics.
Causal Mediation in Natural Experiments (2025, JMP).
Applied econometrics paper showing how mediation works (or does not work) in a quasi-experimental setting — and what to do about it.
Working paper here, and slides here.
Extended Abstract
Natural experiments are a cornerstone of applied economics, providing settings for estimating causal effects with a compelling argument for treatment randomisation, but give little indication of the mechanisms behind causal effects. Causal Mediation (CM) is a framework for sufficiently identifying a mechanism behind the treatment effect, decomposing it into an indirect effect channel through a mediator mechanism and a remaining direct effect. By contrast, a suggestive analysis of mechanisms gives necessary but not sufficient evidence. Conventional CM methods require that the relevant mediator mechanism is as-good-as-randomly assigned; when people choose the mediator based on costs and benefits (whether to visit a doctor, to attend university, etc.), this assumption fails and conventional CM analyses are at risk of bias. I propose an alternative strategy that delivers unbiased estimates of CM effects despite unobserved selection, using instrumental variation in mediator take-up costs. The method identifies CM effects via the marginal effect of the mediator, with parametric or semi-parametric estimation that is simple to implement in two stages. Applying these methods to the Oregon Health Insurance Experiment reveals a substantial portion of the Medicaid lottery's effect on subjective health and well-being flows through increased healthcare usage --- an effect that a conventional CM analysis would mistake. This approach gives applied researchers an alternative method to estimate CM effects when an initial treatment is quasi-randomly assigned, but a mediator mechanism is not, as is common in natural experiments.The Direct and Indirect Effects of Genetics and Education (2025).
I investigate the extent that genes associated with education affect labour market outcomes, using random genetic inheritance as a natural experiment and adjusting various statistical concerns.
Draft in preparation.
Extended Abstract
Social science genetics has shown genes matter for education and labour market outcomes, but has little credible evidence on the economic mechanisms beneath these findings. I use plausibly random deviation from parents as a natural experiment for the Education PolyGenic Index (Ed PGI) to estimate the causal effect of genes associated with years of education, with data from the UK Biobank. I then decompose the total genetic effects into a direct genetic effect and an indirect education pathway using a causal mediation framework that allows for selection into education. A credible mediation analysis requires causal estimates of the returns to education, which I import from a meta-analysis of over one hundred estimates from the economics literature. The Ed PGI increases labour market earnings primarily through higher education attendance, with at least 60% of the total effect operating through education. The remainder is consistent with small direct genetic effects; education-linked genes are more about returns to higher education, and less about direct genetic effects. These findings reframe the usual focus in social science genetics by shifting from asking if genes matter to how they matter --- not as deterministic forces, but as factors that influence human capital decisions within institutional constraints. By using causal methods that account for individual choice in education, rather than assuming genetic determinism, this research provides a richer understanding of how biological inheritance, human capital decisions, and institutional structures interact to shape labour market inequality.Less Funding, More Lecturers, and Fewer Professors (2024).
Empirical economics paper connecting stagnating US higher education funding with substituting professors for lecturers.
Working paper here.
Extended Abstract
Public universities employ more lecturers and fewer professors today than at any other point in the last thirty years, relative to student enrolment. At the same time, state funding for higher education has stagnated. This paper shows that the decline in state funding led to a substitution away from professors toward lecturers at US public universities. Using a shift-share approach to instrument for state funding, I find that universities employ 4.4% more lecturers per student following a 10\% funding cut. This shift is accompanied by a reduction in assistant and full professors by 1.4% and 1.2% per student, respectively. These effects are concentrated to 1990--2009, with waning national trends for 2010 and onwards. Incumbent professors' salaries, promotion rates, and quit rates at Illinois universities remain unaffected by large funding cuts in the 2010s, indicating that the substitution arose from limiting the hiring of new professors. Stagnating state funding impacts public universities and faculty, likely contributing to deteriorating student outcomes at public universities since the 1990s.Food Insecurity Among US Military Veterans (2025).
Joint with Seungmin Lee (Notre Dame), Chris Barrett, John Hoddinott (Cornell), Matthew Rabbitt (USDA).
Empirical economics project measuring food insecurity among military veterans, using newly crafted data from the PSID to causally measure the impact of military service on food insecurity outcomes.
Draft in preparation.
Extended Abstract
There is a growing perception that United States military veterans are underserved once they retire from the services. They experience higher rates of homelessness, disability, and suffer higher rates of food insecurity during service. This paper examines the long-term effects of military service on food insecurity, examining whether military veterans exhibit higher rates of food insecurity than non-veterans. Military-veteran-headed households experienced better food security outcomes than non-veteran-headed-households, and correspondingly participate less than non-veteran households in food insecurity targeted welfare programmes. We use the Vietnam-era lottery draft to infer causal effects, and find that military service has no effect on food insecurity. Our results suggest policies that assist currently enlisted service members, and those unlikely to head traditional households, are most effective at tackling food insecurity discrepancies.Market Interventions in a Large-Scale Virtual Economy (2022).
Joint with Peter Xenopoulos, Claudio Silva (NYU). ArXiv paper here.
Study of large market interventions in an online multiplayer game’s economy, and the causal effects on market activity. Combines insights from applied economics and data science in the study of virtual games.