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American Economic Review: Vol. 102 No. 5 (August 2012)
AER Volume. 102, Issue 5 |
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A Rational Expectations Approach to Hedonic Price Regressions with Time-Varying Unobserved Product Attributes: The Price of Pollution
Article Citation
Bajari, Patrick,
Jane Cooley Fruehwirth,
Kyoo il Kim, and
Christopher Timmins. 2012. "A Rational Expectations Approach to Hedonic Price Regressions with Time-Varying Unobserved Product Attributes: The Price of Pollution."
American Economic Review,
102(5): 1898-1926.
DOI: 10.1257/aer.102.5.1898
DOI: 10.1257/aer.102.5.1898
Abstract
We propose a new strategy for a pervasive problem in the hedonics literature: recovering hedonic prices in the presence of time-varying correlated unobservables. Our approach relies on an assumption about home buyer rationality, under which prior sales prices can be used to control for time-varying unobservable attributes of the house or neighborhood. Using housing transactions data from California's Bay Area between 1990 and 2006, we apply our estimator to recover
marginal willingness to pay for reductions in three of the EPA's "criteria" air pollutants. Our findings suggest that ignoring bias from
time-varying correlated unobservables considerably understates the benefits of a pollution reduction policy. (JEL D12, D84, Q53, Q58, R21)
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Authors
Bajari, Patrick (U MN)
Fruehwirth, Jane Cooley (U Cambridge)
Kim, Kyoo il (U MN)
Timmins, Christopher (Duke U)
Fruehwirth, Jane Cooley (U Cambridge)
Kim, Kyoo il (U MN)
Timmins, Christopher (Duke U)
JEL Classifications
D12: Consumer Economics: Empirical Analysis
D84: Expectations; Speculations
Q53: Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
Q58: Environmental Economics: Government Policy
R21: Urban, Rural, Regional, and Transportation Economics: Housing Demand
D84: Expectations; Speculations
Q53: Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
Q58: Environmental Economics: Government Policy
R21: Urban, Rural, Regional, and Transportation Economics: Housing Demand

