Research

Segmented Labor Markets and Structural Transformation

Working draft, September 2026. Presented at the North American Meeting of the Urban Economics Association (Chicago, 2026) and the Dutch Urban Economics and Trade Workshop (2025, 2026).

Most urban growth this century will occur in developing economies. Whether this urbanization translates into sustained economic development depends on how quickly workers gain access to productive formal employment. I develop a dynamic spatial general equilibrium model with three types of labor markets: rural, urban informal, and urban formal. Migrants enter an informal queue, and formalization depends on informal labor congestion and the economy's ability to move informal workers into formal employment. I quantify the model for Ethiopia using novel geospatial and microdata. The speed of transition from informal to formal labor markets emerges as a key determinant of long-run structural transformation, economic growth and welfare: improvements to formalization raise the long-run urban formal labor share by 26 pp and real GDP by 13.1 percent relative to the baseline, while leaving the urban population share largely unchanged. The formalization rate also shapes both the effectiveness of economic policies and national resilience to climate shocks and conflict. Cities become engines of structural transformation not when workers arrive, but when labor markets absorb them into productive employment.

Paper (PDF, working draft, September 2026) · Online appendix (PDF) · Code (available soon) · Data (available soon)

(Mis)measuring Local Weather Shocks: Evidence from Drought and Migration in Ethiopia

with Michiel Gerritse and Frank van Oort · Under review

Presented at the 6th GCD Workshop on Regional Development and Innovation (A Coruña, 2024), the Regional Science Workshop on Remote-Sensed Identification and Networks (Oviedo, 2024), and the PSE Summer School on Migration (2023).

Extreme weather shocks strike locally, yet their effects are typically estimated from exposure aggregated across districts, regions or countries. We show that this aggregation systematically biases impact estimates and propose a simple correction. Using high-resolution rainfall and satellite-derived population data for more than 13,000 Ethiopian settlements (2000–2016), we find that drought reduces population in vulnerable settlements by about 2.5 percent, concentrated among working-age adults and coinciding with falling food production, income and health. Measured at progressively coarser scales, the impact disappears, even at resolutions common in the literature. We decompose the bias into three sources (partial exposure misclassified, local vulnerability averaged away, area weights misrepresenting where people live) and derive a fix: measure each shock at fine scale, weight by local vulnerability, then aggregate. The correction recovers estimates in areas roughly four times larger than those at which the standard binary indicator fails; simulations confirm its performance. Building exposure locally before aggregating is a low-cost change that can substantially improve empirical practice.

Paper (PDF, working paper, September 2026) · Code (available soon) · Data (available soon)

Memory, Expectations, and Climate Adaptation

with Frank van Oort · Pre-registered field experiment (AEA RCT Registry, 2026) · Draft, September 2026

Smallholder farmers face increasingly frequent weather shocks, yet take-up of insurance and other protection remains low. We show that part of this demand problem lies in how farmers form beliefs about future weather. In a survey experiment with 686 farmers in eastern Uganda, we elicit memories of past seasons and expectations for the coming one, benchmark them against remotely sensed weather records, and experimentally provide information on local weather history. Memory is strongly compressed, with large differences in the record becoming small differences in recall, and this compression carries into expectations, while memorable extreme events form a separate, less compressed channel. Beliefs matter: farmers expecting adverse weather plan more adaptation. A simple visual summary of local weather history moves expectations toward the record, most for those furthest away; literacy predicts accuracy but not responsiveness. Belief formation is thus a demand-side margin in climate adaptation, and accessible information a low-cost complement to protection policies.

Paper (PDF, working draft with online appendix, September 2026) · Photos from the field · Code (available soon) · Data (available soon)