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Title: A DYNAMIC MODEL OF DEMAND FOR HOUSESAND NEIGHBORHOODS

Citation Type: Journal Article

Publication Year: 2016

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Abstract: This paper develops a dynamic model of neighborhood choice along with a com-putationally light multi-step estimator. The proposed empirical framework capturesobserved and unobserved preference heterogeneity across households and locations ina exible way. We estimate the model using a newly assembled data set that matchesdemographic information from mortgage applications to the universe of housing trans-actions in the San Francisco Bay Area from 1994 to 2004. The results provide therst estimates of the marginal willingness to pay for several non-marketed amenitiesneighborhood air pollution, violent crime, and racial compositionin a dynamic frame-work. Comparing these estimates with those from a static version of the model high-lights several important biases that arise when dynamic c onsiderations are ignored.

Url: http://onlinelibrary.wiley.com/doi/10.3982/ECTA10170/epdf

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Authors: Bayer, Patrick; McMillan, Robert; Murphy, Alvin; Timmins, Christopher

Periodical (Full): Econometrica

Issue: 3

Volume: 84

Pages: 893-941

Data Collections: IPUMS USA

Topics: Housing and Segregation, Methodology and Data Collection, Other

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