A Dynamic Model of Demand for Houses and Neighborhoods

By Patrick J. Bayer, R. Mcmillan, A. Murphy, C. Timmins. 2016

251 citations recorded by the source corpus.

This paper develops a dynamic model of neighborhood choice along with a computationally light multi-step estimator. The proposed empirical framework captures observed and unobserved preference heterogeneity across households and locations in a flexible way. The model is estimated using a newly assembled data set that matches demographic information from mortgage applications to the universe of housing transactions in the San Francisco Bay Area from 1994- 2004. The results provide the first estimates of the marginal willingness to pay for several non-marketed amenities – neighborhood air pollution, violent crime and racial composition – in a dynamic framework. Comparing these estimates with those from a static version of the model highlights several important biases that arise when dynamic considerations are ignored.

View Paper: https://www.semanticscholar.org/paper/6e84b3e2cd1e03a438464dff80fb22dff0a4a5da

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Citations in the corpus

From Fog to Smog: the Value of Pollution Information (2019, background): “The housing analysis is a canonical example to study household preference for non-marketed environmental goods (Oates, 1969; Chay and Greenstone, 2005; Banzhaf and Walsh, 2008; Bayer et al., 2016).”
Out-migration, Wealth Constraints, and the Quality of Local Amenities (2014, background): “Our analysis also incorporates noneconomic factors as determinants of migration decisions, such as individuals' overall contentmentwith public services, security, or governance—factors shown by the literature on residential sorting and hedonic equilibrium to be of considerable value (Bayer et al., 2”
East-Side Story: Historical Pollution and Persistent Neighborhood Sorting (2016, unknown): “We also pre-sent a novel strategy to estimate a dynamic model of neighborhood choice with low data requirements (in contrast to Bayer et al. 2016).”