Estimating Neighborhood Choice Models: Lessons from a Housing Assistance Experiment
利用住房援助实验数据估计邻里选择模型，发现限制补贴用于更低贫困社区会降低参与率并增加平均贫困暴露，种族限制则无显著影响。
We use data from a housing-assistance experiment to estimate a model of neighborhood choice. The experimental variation effectively randomizes the rents which households face and helps identify a key structural parameter. Access to two randomly selected treatment groups and a control group allows for out-of-sample validation of the model. We simulate the effects of changing the subsidy-use constraints implemented in the actual experiment. We find that restricting subsidies to even lower poverty neighborhoods would substantially reduce take-up and actually increase average exposure to poverty. Furthermore, adding restrictions based on neighborhood racial composition would not change average exposure to either race or poverty.