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SPATIAL HEDONIC MODELS OF AIRPORT NOISE, PROXIMITY, AND HOUSING PRICES*

Authors


  • *

    The authors thank Deborah Roisman and Lesli Ott for excellent research assistance and the City of Atlanta Department of Aviation for noise contour data. Cohen acknowledges support from the Faculty Resource Network at New York University and the Federal Reserve Bank of St. Louis. The views expressed are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors.

Abstract

ABSTRACT Despite the refrain that housing prices are determined by “location, location, and location,” few studies of airport noise and housing prices have incorporated spatial econometric techniques. We compare various spatial econometric models and estimation methods in a hedonic price framework to examine the impact of noise on 2003 housing prices near the Atlanta airport. Spatial effects are best captured by a model including both spatial autocorrelation and autoregressive parameters estimated by a generalized moments approach. In our preferred model, houses located in an area in which noise disrupts normal activities (defined by a day–night sound level of 70–75 decibels) sell for 20.8 percent less than houses located where noise does not disrupt normal activities (defined by a day–night sound level below 65 decibels). The inclusion of spatial effects magnifies the negative price impacts of airport noise. Finally, after controlling for noise, houses farther from the airport sell for less; the price elasticity with respect to distance is −0.15, implying that airport proximity is an amenity.

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