A Dynamic Model of Demand for Houses and Neighborhoods
开发了一个动态社区选择模型，利用社区选择和搬迁时间数据估计住房偏好、资产表现偏好和搬迁成本，并用于评估种族邻近、臭氧暴露和暴力犯罪等设施的支付意愿。
We develop a tractable model of neighborhood choice in a dynamic setting along with a computationally straightforward estimation approach. This approach uses information on neighborhood choice and the timing of moves to recover: (i) preferences for dynamically evolving housing and neighborhood attributes, (ii) preferences for the performance of housing as a financial asset (e.g., expected appreciation, volatility), and (iii) moving costs. The model and estimation approach are potentially applicable to the study a wide set of dynamic phenomena in housing markets and cities. We use our model to estimate the marginal willingness to pay for three (dis)amenities: living near neighbors from the same racial group, exposure to ground-level ozone, and proximity to violent crime. Consistent with theory, we find that a naive static model understates willingness to pay to avoid ozone and crime, but overstates willingness to pay to live near one’s own race. This has important implications for the class of static housing demand and hedonic models that are typically used to value all sorts of urban amenities.