Research

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

WORKING PAPERS

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)
R&R, Review of Economic Studies.

Coverage: voxdev,  voxeu


Enabled to work: The impact of government housing on slum dwellers in South Africa 
R&R, Journal of Urban Economics
. Older version: CSAE WPS/2015-10 

Can the state improve the lives of slum dwellers by supplying formal housing otherwise not provided by the market? Or will state-built housing, priced at the cost of production, be beyond the willingness to pay of poor households or built in the wrong location? To answer these questions, I study a lottery for large-scale government housing in Ethiopia. Winners of the lottery are sold apartments on the outskirts of the city. They then have the choice to move in or rent out these units. By moving in they pay a high implicit price in forgone rent determined by the market, which I find to exceed the cost to the state of providing the housing. I find that nearly half of lottery winners trade slum housing in the city centre for improved housing on the outskirts of cities. In addition, they make upgrades to their apartments, adding a number of amenities that they did not enjoy in their slum housing and did not come with government housing. I argue that this reveals unmet demand for improved housing and suggests that informal housing is a sub-optimal outcome for a large proportion of slum-dwellers in this setting. Moving to sites far from the city centre does not negatively affect labour supply or earnings. Although social lives are less vibrant in the new housing estates, lottery winners report significant reductions in conflict with neighbours and increased willingness to contribute to public goods.
Coverage: The Guardian. 

Good neighbours make good fences: randomly allocated neighbours and local public goods in urban Ethiopia. 
Draft available.
How does the composition of residents in urban neighbourhoods affect the provision of local public goods? In developing countries where the state does not always provide adequate local sanitation, security and maintenance goods, local communities’ well-being may depend on their ability to coordinate to provide these goods for themselves. Housing and urban policy influence how the inhabitants of diverse and unequal cities are distributed across neighbourhoods. I study a lottery for state-built housing in Ethiopia that randomly assigns groups of households to apartment blocks in newly built neighbourhoods. I collect data on the universe of randomly assigned households in 250 housing blocks at the time that they move in. I combine this with detailed data on the quality of local public goods at the time of moving in and two years later, from a specifically designed neighbourhood survey and household self-reports. I find clear evidence that the composition of neighbours affects local public good provision, in terms of building maintenance and beautification of public spaces, as well as self-reported community cohesion and willingness to contribute to public goods. Specifically, buildings with higher poverty rates and with lower rates of owner-occupation have significantly worse maintenance and community space improvements. By contrast, I find no evidence that ethnic diversity affects community and public goods outcomes.
 
(with Marcel Fafchamps, Girum Abebe, Simon Quinn, Stefano Caria, Forhad Shilpi, and Paolo Falco)
Submitted.

(with Stefano Caria and Marc Witte)
Submitted.

The long-term impacts of industrial and entrepreneurial work: Experimental Evidence from Ethiopia (with Chris Blattman and Stefan Dercon)
Draft available.

Can one-time interventions help poor and underemployed youth overcome barriers to wage or self-employment? We study the effects of two interventions across five sites in Ethiopia: a  start-up grant of \$300 plus business training (intended to relieve capital constraints); and a one-time industrial job offer (intended to help low-skilled youth with no formal work experience gain entry into the formal sector). Among young, mostly female, job applicants in Ethiopia, we randomly assigned them to the start-up grant, job offer, or a control group. After one year, grant recipients were more likely to be self-employed and had a third greater earnings than controls. Those offered industrial jobs were somewhat more likely to be working in the industrial sector, but the offer had no impact on incomes and adverse effects on health. After five years, all these effects dissipated. We find nearly total convergence in incomes, health, occupational choice, and hours of work between in all experimental conditions. Over time, the control group overcame entry barriers to self-employment and wage work, and in part caught up to the start-up group in incomes and employment. Many of those in the start-up arm also exited their enterprises over time and saw their real incomes and employment fall. Those offered the industrial job tended to exit the sector over time. We see no long-term effects on ill health, though this could be in part because some of the control group found work in industry as well.


Private costs and social benefits of workfare: Evidence from urban Ethiopia 
(with Girum Abebe and Carolina Mejia-Mantilla)
Draft available soon.

WORK IN PROGRESS


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