Are the well-known facts about urbanization in the United States also true for the developing world? We compare American metropolitan areas with comparable geographic units in Brazil, China and India. Both Gibrat's Law and Zipf's Law seem to hold as well in Brazil as in the U.S., but China and India look quite different. In Brazil and China, the implications of the spatial equilibrium hypothesis, the central organizing idea of urban economics, are not rejected. The India data, however, repeatedly rejects tests inspired by the spatial equilibrium assumption. One hypothesis is that the spatial equilibrium only emerges with economic development, as markets replace social relationships and as human capital spreads more widely. In all four countries there is strong evidence of agglomeration economies and human capital externalities. The correlation between density and earnings is stronger in both China and India than in the U.S., strongest in China. In India the gap between urban and rural wages is huge, but the correlation between city size and earnings is modest. The cross-sectional relationship between area-level skills and both earnings and area-level growth are also stronger in the developing world than in the U.S. The forces that drive urban success seem similar in the rich and poor world, even if limited migration and difficult housing markets make it harder for a spatial equilibrium to develop.
We acknowledge support from the Taubman Center for State and Local Government. Chauvin acknowledges support from the Center for International Development at Harvard University. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w22002.ack NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
This paper examines why a larger share of COVID-19 deaths occurs among young and middle-aged adults in developing countries than in high-income countries. Using novel data at the country, city, and patient levels, we investigate the drivers of this gap in terms of the key components of the standard Susceptible-Infected-Recovered framework. We obtain three main results. First, we show that the COVID-19 mortality age gap is not explained by younger susceptible populations in developing countries. Second, we provide indirect evidence that higher infection rates play a role, showing that variables linked to faster COVID-19 spread such as residential crowding and labor informality are correlated with younger mortality age profiles across cities. Third, we show that lower recovery rates in developing countries account for nearly all of the higher death shares among young adults, and for almost half of the higher death shares among middle-aged adults. Our evidence suggests that lower recovery rates in developing countries are driven by a higher prevalence of preexisting conditions that have been linked to more severe COVID-19 complications, and by more limited access to hospitals and intensive care units in some countries.
This paper investigates what explains the variation in impacts of COVID-19 across Brazilian cities. I assemble data from over 2,500 cities on COVID-19 cases and deaths, population mobility, and local policy responses. I study how these outcomes correlate with pre-pandemic local characteristics, drawing comparisons with existing US estimates when possible. As in the United States, the connections between city characteristics and outcomes in Brazil can evolve over time, with some early correlations fading as the pandemic entered a second wave. Population density is associated with greater local impact of the disease in both countries. However, in contrast to the United States, the pandemic in Brazil took a greater toll in cities with higher income levels consistent with the fact that higher incomes correlate with greater mobility in Brazil. Socioeconomic vulnerabilities, such as the presence of slums and high residential crowding, correlate with higher death rates per capita. Cities with such vulnerabilities in Brazil suffered higher COVID-19 death rates despite their residents' greater propensity to stay home. Policy responses do not appear to drive these connections.
While there is evidence of gender differences in policy preferences and electoral strategic behaviors, less is known about how these differences play out during crises. We use a close election RD design to compare the performance of female- and male-led Brazilian municipalities during the COVID-19 pandemic. We find that having a female mayor led to more deaths per capita early in the first wave of the pandemic -a period characterized by great uncertainty about the severity of the disease and the effectiveness of containment policies. In contrast, having a female mayor led to fewer deaths per capita early in the second wave -a period where this uncertainty was reduced, and when the 2020 mayoral election took place. Consistent with the evolution of deaths, we find that female mayors were less likely to implement commerce restrictions at the beginning of the period, while they became more likely to do so at the end. We also show that the second-wave effect coincides with a lower tendency of the population in maleled municipalities to stay at home around election day. Both the first and second wave effects are driven by municipalities whose mayors were not term limited, and thus allowed to run for re-election. These findings suggest that the gender differences we observe stem from female and male mayors reacting differently to electoral incentives. While electorally motivated female mayors were more likely to delay restrictive policies at the beginning, electorally motivated male mayors were more likely to open-up the municipality closer to the election.
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