Workers in developing countries face substantial constraints to job search. Many policies aim to lower search barriers and expand the wage sector, but the efficiency and optimality of these policies remain unclear. This paper develops a search-and-matching model that incorporates key features of developing economies including a large self-employment sector, savings-constrained households, and capital-constrained firms. Four search externalities --- two positive and two negative --- emerge, leading to inefficiency. After estimating the model using an experiment that provided search subsidies to job seekers in Ethiopia, I find that the optimal policy is a tax that substantially increases the cost of search, rather than a subsidy.
This paper studies the macroeconomic effects of publicly funded (’free’) secondary schooling in the developing world. Our analysis is based on an overlapping generations model of human capital accumulation that we estimate to match experimental evidence on the effects of scholarships for poor but talented students in Ghana. The model predicts that nationwide free secondary schooling increases average education levels but leads to only a modest gain in GDP per capita. The human capital gains from expanded education access are offset by lost income during schooling years and dampened by negative selection of new students entering secondary school. An alternative policy that spends the same resources improving school quality has significantly larger effects.
Many older adults in the United States delay medical treatment until they qualify for Medicare at age 65. This can greatly increase their healthcare costs as they forgo cheaper earlier treatment, replacing it with more expensive care later. This paper studies the aggregate implications of delayed care focusing on the effects of expanding access to public health insurance before age 65. I build an overlapping generations model with rich household heterogeneity that is estimated to match quasi-experimental evidence on delayed care. My results indicate that the cost-savings are small, and expansion is unlikely to pay for much of its cost.
The COVID-19 pandemic has already led to dramatic policy responses in most advanced economies, and in particular sustained lockdowns matched with sizable transfers to much of the workforce. This paper provides a preliminary quantitative analysis of how aggregate policy responses should differ in developing countries. To do so we build an incomplete-markets macroeconomic model with epidemiological dynamics that features several of the main economic and demographic distinctions between advanced and developing economies relevant for the pandemic. We focus in particular on differences in population structure, fiscal capacity, healthcare capacity, the prevalence of “hand-to-mouth” households, and the size of the informal sector. The model predicts that blanket lockdowns are generally less effective in developing countries at reducing the welfare costs of the pandemic, saving fewer lives per unit of lost GDP. Age-specific lockdown policies, on the other hand, may be even more potent in developing countries, saving more lives per unit of lost output than in advanced economies.
Short Publications: [ CEPR COVID Economics ] [ VoxEU ] [ ProMarket ]
Sparse grids are useful for solving large economic models but require knowledge of the value function at carefully chosen gridpoints. Endogenous grid methods avoid numerical optimization but relinquish control over the grid on which updated values are returned. This paper presents a method that resolves this tension, allowing both to be implemented together. The envelope condition provides a guess of the policy function that can be used to control the grid on which the updated value function is known. Although not correct in general, this guess will be correct after convergence is achieved, ensuring that the fixed point of the method solves the desired Bellman equation. The result is a fast and robust method for solving medium-dimension economic models.
The macroeconomic effects of the COVID-19 pandemic were most severe for emerging market economies, representing the middle of the world income distribution. This paper provides a quantitative economic theory for why emerging markets fared worse, on average, relative to advanced economies and low-income countries. To do so we adapt a workhorse incomplete-markets macro model to include epidemiological dynamics alongside key economic and demographic characteristics that distinguish countries of different income levels. We focus in particular on differences in lockdown stringency, public insurance programs, age distributions, healthcare capacity, and the sectoral composition of employment. The calibrated model predicts greater output declines in emerging markets, as in the data, and greater excess mortality, albeit to a smaller extent than what is observed in the data. Quantitatively, stricter lockdowns and a higher share of jobs requiring social interaction explain a large fraction of the especially severe outcomes in emerging markets. Low-income countries fared relatively better mainly due to their younger populations, which are less susceptible to the disease, and larger agricultural sectors, which require fewer social interactions.
Does unreliable electricity hold back economic modernization by discouraging technology adoption? This project answers this question by measuring the effect of long-run differences in electrical reliability. We leverage the presence of “feeder borders” in Nairobi, Kenya where two distinct medium-voltage powerlines meet. Buildings along these borders can be geographically adjacent, separated by only a small path, but “electrically distant”, experiencing very different levels of reliability. Using administrative data on the universe of feeder-level outages in Kenya, we identify over 200 borders that exhibit large, persistent differences in reliability. Comparing technology usage and economic outcomes for households and firms residing near these borders (surveys in progress) allows us to measure the causal impact of reliability differences.
Self Employment, Micro-Entrepreneurship, and Development (with Austin Davis and Eric Hsu) STEG Pathfinding Paper, March 2023