Information on willingness-to-pay is key for public pricing and allocation of services but not easily collected. Studying land titles in Dar-es-Salaam, we ask whether local leaders know and will reveal plot owners’ willingness-to-pay. We randomly assign leaders to predict under different settings then elicit owners’ actual willingness-to-pay. Demand is substantial but below exorbitant fees. Leaders can predict the aggregate demand curve and distinguish variation across owners. Predictions worsen when used to target subsidies, but adding cash incentives mitigates this. We demonstrate that leader-elicited information can improve the public pricing of title deeds, raising uptake while maintaining public funds.

We model the building of a city, estimate parameters of the model, and calculate welfare losses from institutional frictions encountered in changing land-use. We distinguish formal and slum construction technologies; in contrast to slums, formal structures can be built tall, are durable, and non-malleable. As the city grows areas are initially developed informally, then formally, and then redeveloped periodically. Slums are modelled as a technology choice; however, institutional frictions in land markets may hinder their conversion to formal usage that requires secure property rights. Using unique data on Nairobi for 2003 and 2015, we develop a novel set of facts that support assumptions of the model, estimate all parameters of the model, and calculate welfare losses of conversion frictions. We track the dynamic evolution of the city and compare it with model predictions. In the core city formal sector, about a third of buildings were torn down over 12 years and replaced by buildings on average three times higher. For slums in older areas near the centre, even after buying out slumlords, overcoming institutional frictions would yield gains amounting to about $18,000 per slum household, thirty times typical annual slum rent payments.

Africa?s demand for urban housing is soaring, even as it faces a proliferation of slums. In this setting, can modest infrastructure investments in greenfield areas where people subsequently build their own houses facilitate long-run neighborhood development? We study Sites and Services projects implemented in seven Tanzanian cities during the 1970s and 1980s, and we use a spatial regression discontinuity design to compare greenfield areas that were treated (de novo) with nearby greenfield areas that were not. We find that by the 2010s, de novo areas developed into neighborhoods with larger, more regularly laid-out buildings and better-quality housing.