How do geographically concentrated income shocks influence the long-run spatial distribution of poverty within a city? We examine the impact on housing prices of a cholera epidemic in one neighborhood of nineteenth century London. Ten years after the epidemic, housing prices are significantly lower just inside the catchment area of the water pump that transmitted the disease. Moreover, differences in housing prices persist over the following 160 years. We make sense of these patterns by building a model of a rental market with frictions in which poor tenants exert a negative externality on their neighbors. This showcases how a locally concentrated income shock can persistently change the tenant composition of a block. (JEL D62, O18, R21, R31)

Researchers and policymakers often rely on the infant mortality rate as an indicator of a country's health. Despite arguments about its relevance, uniform measurement of infant mortality is necessary to guarantee its use as a valid measure of population health. Using important socioeconomic indicators, we develop a novel method to adjust country-specific reported infant mortality figures. We conclude that an augmented measure of mortality that includes both infant and late fetal deaths should be considered when assessing levels of social welfare in a country. In addition, mortality statistics that exhibit a substantially high ratio of late fetal to early neonatal deaths should be more closely scrutinized.

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We combine data on beliefs about the origin of the 2014 Ebola outbreak with two supervised machine learning methods to predict who is more likely to be misinformed. Contrary to popular beliefs, we uncover that, socio-demographic and economic indicators play a minor role in predicting those who are misinformed: misinformed individuals are not any poorer, older, less educated, more economically distressed, more rural, or ethnically different than individuals who are informed. However, they are more likely to report high levels of distrust, especially towards governmental institutions. By distinguishing between types of beliefs, distrust in the central government is the primary predictor of individuals assigning a political origin to the epidemic, while Muslim religion is the most important predictor of whether the individual assigns a supernatural origin. Instead, educational level has a markedly higher importance for ethnic beliefs. Taken together, the results highlight that government trust might play the most important role in reducing misinformation during epidemics.

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