I am an economist studying how contracts and firm-to-firm relationships shape trade and development. My work uses a combination of quantitative models, administrative data, and field experiments.
I received a PhD in Economics from MIT in May 2025. Prior to that, I completed Bachelor’s and Master’s degrees at the London School of Economics.
I am British and Canadian, which has given me a lifelong interest in international football, queuing, and apologising.
We study search and trust frictions in international sourcing, and whether the rapid growth of "social commerce" in lower-income countries can alleviate them. Guided by a dynamic model of relational contracting, we run a field experiment with 1,862 garment firms in Senegal, randomly matching them to suppliers in Türkiye (search) and varying information about supplier type (adverse selection) and incentives (moral hazard). New supplier connections expand access to foreign varieties and quality, but the additional information about supplier trustworthiness is necessary for building lasting and profitable relationships. Structural estimates imply that both adverse selection and moral hazard substantially limit trade.
Adverse selection and moral hazard are severe in trade and reinforce each other, but firms in LMICs are increasingly using ``social commerce'' as a decentralized, network-based way to mitigate them.
The core ingredient of modern quantitative trade models is cross-country heterogeneity in productive capabilities across goods. In workhorse models this heterogeneity is assumed to follow specific functional forms---such as i.i.d. Frechet or Pareto---but little is known about how these models' counterfactual predictions would change under alternative distributional assumptions. We fill this gap by estimating sharp bounds on counterfactuals across all distributions within given neighborhoods of the workhorse model. Importantly, our method only considers distributions that can generate baseline equilibria that exactly match all trade flow data points, and hence reproduce empirical facts such as the amount of openness, the fit of the gravity equation, and the estimated trade elasticity. Our estimated bounds on the gains from trade are wide, even for small departures from the workhorse model: the upper bound is more than four times that of the workhorse model (so trade can be much more valuable than typically thought) and the lower bound is zero (so trade can even generate no gains). Imposing high-level restrictions on the distributions considered---for example, maintaining Frechet/Pareto marginals but relaxing independence, or vice versa---does little to shrink these bounds.
The estimates of gains from trade produced by workhorse quantitative trade models are highly sensitive to deviations from the typical maintained assumptions, such as Frechet or Pareto productivity.
Princeton Summer Trade Workshop
June 2026
Latest Version: June 2026 (substantially revised!)
We embed a field experiment in a nationwide recruitment drive for a new health care position in Zambia to test whether career benefits attract talent at the expense of prosocial motivation. In line with common wisdom, offering career opportunities attracts less prosocial applicants. However, the trade-off exists only at low levels of talent; the marginal applicants in treatment are more talented and equally prosocial. These are hired, and perform better at every step of the causal chain: they provide more inputs, increase facility utilization, and improve health outcomes including a 25 percent decrease in child malnutrition.
Contract design not only screens and incentivizes a given pool of agents, but also affects who applies in the first place: emphasizing career benefits for a healthcare job in Zambia made the pool of applicants more talented, leading to large improvements in health outcomes.
Awarded the Arrow Award for the best paper published in health economics in English in 2020 by the International Health Economics Association.
Selected Work in Progress
The Aggregate Consequences of Relational Contracting with Pulak Ghosh
Abstract
Most trade takes place in buyer–seller relationships that expand gradually over time. A growing body of empirical evidence suggests that this pattern may reflect the importance of relational contracting: when formal enforcement is limited, continued trade itself provides incentives. Using rich firm-to-firm trade data from India, I show that value traded in a typical relationship approximately doubles over the course of a year, that this growth curve is flatter in states with stronger contract enforcement, and that this growth curve is invariant to firm size. These facts mean that adjustments to trade shocks are inherently dynamic, as firms must build trust with new suppliers. To quantify the aggregate consequences of these micro-level adjustments, I develop a dynamic multi-country general-equilibrium model that embeds optimal relational contracts within a tractable Eaton–Kortum-style framework, generating endogenous growth in traded quantities as relationships age. Using the microdata to estimate the model, I compare the dynamic vs static welfare consequences of a landmark Indian domestic integration reform.
Trade Credit and Digital Records: Evidence from Cote d’Ivoire with Deivy Houeix
Abstract
Trade credit—suppliers allowing buyers to purchase inventory now and pay later—is central to firm-to-firm commerce but depends on trust. In settings with limited contract enforcement, suppliers often ration credit to unfamiliar buyers, limiting firm growth and creating barriers to entry. We study whether firms can use increasingly available mobile payments records to signal creditworthiness to potential suppliers or lenders---an open finance model---and how this affects relationship development and firm- and market-level outcomes. We collaborate with a large mobile money provider in Cote d'Ivoire to build and evaluate a tool for firms to provided verified disclosures, as well as a fintech specializing in trade credit to study how specialized intermediaries use such records. We run an RCT with 2,000 retailers in the packaged drinks sector, where we randomize whether firms can access the new disclosure tool and whether we connect them with the specialized trade credit lender. Pilot results show that the ability to do verified disclosures increases supplier willingness to extend credit by 20 percentage points. The full RCT is active, with outcomes of interest including credit access, supplier relationships, product varieties, prices, stockouts, and profits and sales.
Abstract
We examine the impact of trade liberalization on structural change patterns in India. Leveraging district-level variations in sectoral composition, we find that districts with greater tariff reductions experienced larger declines in manufacturing employment shares. By extending Matsuyama's 1992 model of deindustrialization to include a non-tradable service sector, we demonstrate analytically and through simulations that India's observed deindustrialization and service-led growth can be qualitatively attributed to trade liberalization. We aim to structurally estimate the model parameters to quantify the role of trade liberalization in driving these structural changes.
