Anonymity or Distance? Job Search and Labour Market Exclusion in a Growing African City (with Girum Abebe, Stefano Caria, Marcel Fafchamps, Paolo Falco, and Simon Quinn). Forthcoming, Review of Economic Studies. Coverage: voxdev, voxeu

Enabled to work: The impact of government housing on slum dwellers in South Africa (2020). Journal of Urban Economics 118.

Location, Search Costs and Youth Unemployment: Experimental Evidence from Transport Subsidies (2018). Economic Journal 128 (614), 2353-2379.

Economic Shocks and Labour Market Flexibility (with Julien Labonne) (2019). Journal of Human Resources 54 (1) 171-199. Online Appendix.


The demand for government housing: evidence from a lottery for 200,000 homes in Ethiopia. Coverage: The Guardian.

Matching Frictions and Distorted Beliefs: Evidence from a Job Fair Experiment. (with Marcel Fafchamps, Girum Abebe, Simon Quinn, Stefano Caria, Forhad Shilpi, and Paolo Falco). Updated November 2020.

Searching with Friends (with Stefano Caria and Marc Witte). -- R&R, Journal of Labor Economics.

The long-term impacts of industrial and entrepreneurial work: Experimental Evidence from Ethiopia. (with Chris Blattman and Stefan Dercon). Summary-- R&R, Journal of Development Economics.

Does Wealth Reduce Support for Redistribution? Evidence from an Ethiopian Housing Lottery. With Asbjørn G. Andersen, Tigabu Getahun, Andreas Kotsadam, Vincent Somville, and Espen Villanger.


Urban Public Works in Spatial Equilibrium: Experimental Evidence from Ethiopia (with Clement Imbert, Girum Abebe and Carolina Mejia-Mantilla)

Diversity, segregation and urban public goods: Evidence from randomly assigned public housing

Urban density and labour markets: Evaluating slum redevelopment in Addis Ababa (with Gharad Bryan)

GLM|LIC Project Page

All around the world, governments implement policies that influence where people live, particularly in dense urban neighbourhoods. These policies have important implications for the working of labour markets. Urban labour markets provide access to formal jobs without long commutes, access to customers and markets, and access to social networks that support labour markets, particularly in informal economies. Each additional person who lives in the city centre not only gains from these urban labour markets but also contributes to these agglomeration economies, imposing positive externalities on others. But increasing density in informal settlements can also have negative externalities in terms of congestion, health, and poor infrastructure, which could limit the potential of cities to create high productivity formal jobs. Estimating the scope and scale of these externalities is an empirical challenge. The government of Addis Ababa recently announced plans to redevelop large central areas of the city, which will lead to the relocation of 20,000 households out of informal settlements. Building on a sample of 30,000 geo-referenced surveys conducted in Addis before the announcement, we will estimate both the direct effect of being relocated out of a dense city centre, as well as the externalities of the relocations, on labour markets in the surrounding areas. We will draw on a variety of empirical techniques from labour and urban economics to estimate how these spillover effects extend over space.

Cost-effective panel data collection for Kampala (with Julia Bird, Gharad Bryan, and Astrid Haas)

IGC Project Page

The urban literature on developing country cities is still growing. One of the major constraints, however, is access to good quality data. Existing data sources are often costly or difficult to get, frequently do not measure prices, are not individual specific, do not allow for tracking of individuals, and are available infrequently and sporadically. As a result of this, predictions about the impacts of projects, such as transportation infrastructure, or policy changes in urban contexts are often based on models that have to infer key prices from location choices and must be calibrated to data that is up to 10 years old. Further, evaluations of projects are not able to make use of modern identification techniques such as synthetic controls which require long panels. In this project we test methods for collecting low-cost, high-frequency panel survey data that improves on existing data sources in three ways: 1) The data will provide information about prices, namely consumer prices, wages, and rents, at the individual and location level; 2) the data will allow for the creation of commuting flows at the individual or group level; 3) the data will allow for tracking of people when they move as well as places over time.