Ask a Local: Improving the Public Pricing of Land Titles in Urban Tanzania
研究在坦桑尼亚达累斯萨拉姆，通过让当地领导预测土地所有者对土地权证的支付意愿，发现他们能准确预测总体需求曲线，但用于补贴分配时准确性下降，而现金激励可缓解这一问题。
Abstract 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.