TY - JOUR AU - Bayer,Patrick AU - Keohane,Nathaniel AU - Timmins,Christopher TI - Migration and Hedonic Valuation: The Case of Air Quality JF - National Bureau of Economic Research Working Paper Series VL - No. 12106 PY - 2006 Y2 - March 2006 UR - http://www.nber.org/papers/w12106 L1 - http://www.nber.org/papers/w12106.pdf N1 - Author contact info: Patrick Bayer Department of Economics Duke University 213 Social Sciences Durham, NC 27708 Tel: 919/660-1832 E-Mail: patrick.bayer@duke.edu Nathaniel Keohane Environmental Defense Fund E-Mail: nkeohane@environmentaldefense.org Christopher Timmins Department of Economics Duke University 209 Social Sciences Building P.O. Box 90097 Durham, NC 27708-0097 Tel: 919/660-1809 Fax: 919/684-8974 E-Mail: christopher.timmins@duke.edu M2 - featured in NBER digest on 2006-03-20 AB - Conventional hedonic techniques for estimating the value of local amenities rely on the assumption that households move freely among locations. We show that when moving is costly, the variation in housing prices and wages across locations may no longer reflect the value of differences in local amenities. We develop an alternative discrete-choice approach that models the household location decision directly, and we apply it to the case of air quality in U.S. metro areas in 1990 and 2000. Because air pollution is likely to be correlated with unobservable local characteristics such as economic activity, we instrument for air quality using the contribution of distant sources to local pollution %u2013 excluding emissions from local sources, which are most likely to be correlated with local conditions. Our model yields an estimated elasticity of willingness to pay with respect to air quality of 0.34 to 0.42. These estimates imply that the median household would pay $149 to $185 (in constant 1982-1984 dollars) for a one-unit reduction in average ambient concentrations of particulate matter. These estimates are three times greater than the marginal willingness to pay estimated by a conventional hedonic model using the same data. Our results are robust to a range of covariates, instrumenting strategies, and functional form assumptions. The findings also confirm the importance of instrumenting for local air pollution. ER -