This paper studies the effects of social learning on the transmission of Covid-19 in a network model. We calibrate our model to detailed data for Cape Town, South Africa and show that the inclusion of social learning improves the prediction of excess fatalities, reducing the best-fit squared difference from 20.06 to 11.28. The inclusion of social learning both flattens and shortens the curves for infections, hospitalizations, and excess fatalities. This result is qualitatively different from flattening the curve by reducing transmission probability through non-pharmaceutical interventions. While social learning reduces infections, this alone is not sufficient to curb the spread of the virus because learning is slower than the disease spreads. We use our model to study the efficacy of different vaccination strategies and find that a risk-based vaccination strategy–vaccinating vulnerable groups first–leads to a 50% reduction in fatalities and 5% increase in total infections compared to a random order benchmark. By contrast, using a contact-based vaccination strategy reduces infections by 9% but results in 64% more fatalities relative to the benchmark.

This paper estimates foreclosure discounts in Cape Town, South Africa, a rare institutional setting where, until 2019, foreclosure auctions occurred without reserve prices. Using newly constructed data linking sheriff auction notices to the universe of property transactions, rich property characteristics, and municipal service request records that proxy for time-varying property condition, I document large foreclosure discounts that vary by empirical approach. In a cost-adjusted hedonic framework that accounts for buyer-incurred transaction costs such as auction commissions, tax arrears, and eviction costs, properties sold at foreclosure auction transact at a discount of 14.5 per cent relative to comparable non-foreclosed sales. In contrast, repeat-sales estimates that difference out time-invariant property characteristics yield substantially larger discounts of 30.2 per cent. Accounting for transaction costs dramatically reduces estimated foreclosure discounts: relative to baseline specifications, discounts fall by roughly a factor of three in the hedonic model and by more than half in the repeat-sales framework. Taken together, these results suggest that the economically relevant foreclosure discount lies between a conservative lower bound that nets out foreclosure-specific costs and a higher bound that may additionally reflect unobserved deterioration not fully captured by observable measures of property condition. The magnitudes documented here are large relative to settings with reserve prices and highlight the importance of auction design and consumer protection, particularly in recourse mortgage systems.

We incorporate a general model of frictions into the bunching-based elasticity estimator. The new estimator replaces bunching-window bounds with a “lumpiness parameter” and uses fewer parameters than the conventional approach while delivering additional economically-interpretable quantities such as the size of frictions and unobserved adjustment costs. The model matches rich observed bunching patterns such as sharp-peaked diffuse bunching around tax kinks and depressed density in notch-adjacent dominated regions. We apply the estimator to canonical settings including the U.S. EITC kink, and to administrative tax data from South Africa, where we uncover novel insights on unobserved VAT compliance costs and kink misperceptions.

Emerging markets are characterized by frequent periods of large and unexpected exchange rate depreciations. These events create opportunities for foreign investors to purchase domestic assets at a discount, especially if these assets have sticky prices. We show this to be the case in the housing market in Cape Town, South Africa. Using property transaction data, I find that foreign non-residents buy more properties following large exchange rate depreciations—in the lower quartile of month-on-month changes. I find no evidence of a similar effect for other buyers, suggestive of strong exchange rate-related motives. Using these depreciations as demand shocks to foreign non-resident buyers, I find that this increased demand leads to an increase in house prices of 3.39%. I find that foreign non-resident buyers pay 10.42% more than other buyers for otherwise identical properties and that this tendency to pay a premium accounts for around 27% of the observed causal impact of foreign demand on house prices.