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Title
Essays on Technology Adoption and Urbanization in East Africa |
Full text
https://escholarship.org/uc/item/6vc0j2sx; https://escholarship.org/content/qt6vc0j2sx/qt6vc0j2sx.pdf |
Date
2024 |
Author(s)
Agness, Daniel |
Contributor(s)
Magruder, Jeremy |
Abstract
Low and middle-income countries are urbanizing rapidly, and nowhere is urbanizing faster than Sub-Saharan Africa. The rush of urbanization presents multiple challenges to policymakers, including how to accommodate rural-to-urban migrants in growing cities while simultaneously improving productivity and promoting food security for those who remain in the agricultural sector. This dissertation speaks to each of these areas. In Chapter 1, I study the intergenerational impacts of public housing expansion in Addis Ababa, Ethiopia ' one of Africa's fastest growing cities. In Chapters 2 and 3, I study technology adoption and agricultural infrastructure expansion in Kenya. Combining the two helps us to make sense of the simultaneous and potentially competing challenges faced by governments in low-income countries during a period of rapid structural transformation. Using tools drawn from the literatures on labor and urban economics, and combining large-scale survey activities with administrative and spatial data, the dissertation employs natural experiments, randomized controlled trials, and structural models to identify causal effects and answer policy-relevant questions.In Chapter 1, 'Housing and Human Capital: Condominiums in Ethiopia', co-authored with Tigabu Getahun, we evaluate a major government response to the pressures of urbanization: the largest expansion of public housing on the African continent. The policy subsidizes homeownership, allowing households to move from low-quality housing or to use their unit as an income generating asset. We make use of the lottery mechanism that has been used to allocate these units to more than 200,000 households in Addis Ababa, Ethiopia, over the past 15 years. To do so, we combine extensive surveys from 2,987 households, surveys with children of affected households, and administrative data collected in collaboration with policy partners to study how this policy has impacted the human capital accumulation of children.We find large and positive effects of a housing policy in a low-income setting. Specifically, we show that children in lottery winning households experience 4.5-11% increase in school attendance, a 10.5% increase in secondary school completion rates, and a 16% increase in post-secondary school matriculation. Our surveys allow us to observe additional measures of human capital that are typically unavailable to researchers using only administrative data. Namely, we show evidence of improved cognition and socio-emotional development for children in lottery winning households, as well as increases in aspirations. We make use of spatial and temporal variation to disentangle mechanisms and reach a novel conclusion: policy impacts are driven by children in households that own and occupy the unit that they win. This rules out the possibility that treatment acts through a wealth effect alone and suggests that neighborhoods of residence may play an important role. We then adapt a structural model of selection from new work in the policy evaluation literature to characterize patterns of selection and estimate margin-specific treatment effects. To our knowledge, our work represents the first use of these methods in the evaluation of a policy in a low-income setting.My second chapter, 'New Technology and Network Change', uses dyadic regressions, a social network panel, and a randomized controlled trial to show how networks respond to the introduction of a new technology. Technology recipients become more central within village networks, driven both by differential maintenance of existing links and through the creation of new ones. I apply these results to a peer effects model with directed networks and show that failing to consider network change overestimates treatment effects and that failing to account for new connections due to the intervention underestimates the importance of peer effects.In my third chapter, coauthored with Travis Baseler, Sylvain Chassang, Pascaline Dupas, and Erik Snowberg, 'Valuing the Time of the Self-Employed', we consider a critical but understudied component of policy evaluations ' people's value of their own time. Accurately estimating the value that the self-employed assign to their own time is essential for estimating the profitability and welfare impacts of interventions. The majority of the literature assumes this value to be zero, which may explain low adoption of seemingly profitable technologies that require increases in worker time. The market wage is likely to be a poor reference in low-income settings, where labor market frictions inhibit individuals from easily converting their time into a wage. To make progress on this question, we use choice data from farming households in Kenya and a structural model to identify behavioral wedges in choices. Accounting for these wedges, we estimate that valuing the time of the self-employed at 60% of the market wage is a reasonable rule of thumb.Together, the three chapters of my dissertation highlight the two-sided policy challenge presented by urbanization and structural transformation in East Africa. Applying econometric methods and experimentation, we focus on communities, both rural and urban, to shed light on how they function and adapt, and how they shape human welfare. |
Subject(s)
Economics; Ethiopia; Housing; Social Networks; Technology Adoption; Urbanization |
Language
en |
Publisher
eScholarship, University of California |
Type of publication
etd |
Format
application/pdf |
Rights
public |
Identifier
qt6vc0j2sx |
Repository
Berkeley - University of California
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Added to C-A: 2024-10-02;09:55:28 |
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