Abstract
The hedonic property value model is among our foremost tools for evaluating the economic consequences of policies that target the supply of local public goods, environmental services, and urban amenities. We design a theoretically consistent and empirically realistic Monte Carlo study of whether omitted variables seriously undermine the method’s ability to accurately identify economic values. Our results suggest that large gains in accuracy can be realized by moving from the standard linear specifications for the price function to a more flexible framework that uses a combination of spatial fixed effects, quasi-experimental identification, and temporal controls for housing market adjustment.
