Disasters are frequent and clearly harmful in developing countries, but precisely estimating their overall cost and distributional impact is challenging. This paper proposes a microsimulation approach to do so rapidly, borrowing concepts from both poverty analysis and urban economics. Because housing prices reflect the present value of a specific bundle of living conditions, local earnings opportunities, and local access to services, their change in the aftermath of a disaster can be interpreted as a measure of the welfare cost incurred by households. A hedonic pricing function is used to estimate such changes based on the destruction experienced by the dwellings themselves, but also on the overall destruction suffered by their surrounding areas. The first element captures the damage from worse living conditions, whereas the second captures the loss from diminished earnings opportunities and access to services. The proposed approach is illustrated by estimating the cost of the 2015 Gorkha earthquakes in Nepal. Overall, the estimated impact is comparable to that from the official assessment. But its spatial distribution is significantly different due to the pivotal influence of neighborhood effects.