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How Does Air Pollution Influence Housing Prices in the Bay Area?

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  • Minmeng Tang

    (Department of Land, Air and Water Resources, University of California, Davis, One Shields Ave, Davis, CA 95616, USA)

  • Deb Niemeier

    (Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742, USA)

Abstract

In this paper we examine the effects of localized air pollution measurements on the housing prices in Oakland, CA. With high-resolution air pollution measurements for NO, NO 2 , and BC, we can assess the ambient air quality on a parcel-by-parcel basis within the study domain. We combine a spatial lag model with an instrumental variable method to consider both the spatial autocorrelation and endogeneity effects between housing prices and air pollution concentrations. To the best of our knowledge, this is the first work in this field that combines both spatial autocorrelation and endogeneity effects in one model with accurate air pollution concentration measurements for each individual parcel. We found a positive spatial autocorrelation with housing prices using Moral’s I (value of 0.276) with the total sample number of 26,386. Somewhat surprisingly, we found a positive relationship between air pollution and housing prices. There are several possible explanations for this finding. Homeowners in high demand, low-stock housing areas, such as our study, may be insensitive to air pollution when the overall ambient air quality is relatively good. It is also possible that under clean air conditions, low variability in pollutant concentrations has little effect on property values. These hypotheses could be verified with more high-resolution air pollution measurements with a diversity of regions.

Suggested Citation

  • Minmeng Tang & Deb Niemeier, 2021. "How Does Air Pollution Influence Housing Prices in the Bay Area?," IJERPH, MDPI, vol. 18(22), pages 1-13, November.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:22:p:12195-:d:683877
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    1. Runqiu Liu & Chao Yu & Canmian Liu & Jian Jiang & Jing Xu, 2018. "Impacts of Haze on Housing Prices: An Empirical Analysis Based on Data from Chengdu (China)," IJERPH, MDPI, vol. 15(6), pages 1-21, June.
    2. Ivar Ekeland & James J. Heckman & Lars Nesheim, 2004. "Identification and Estimation of Hedonic Models," Journal of Political Economy, University of Chicago Press, vol. 112(S1), pages 60-109, February.
    3. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    4. Kenneth Y. Chay & Michael Greenstone, 2005. "Does Air Quality Matter? Evidence from the Housing Market," Journal of Political Economy, University of Chicago Press, vol. 113(2), pages 376-424, April.
    5. Peter Tschofen & Inês L. Azevedo & Nicholas Z. Muller, 2019. "Fine particulate matter damages and value added in the US economy," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(40), pages 19857-19862, October.
    6. Ivar Ekeland & James J. Heckman & Lars Nesheim, 2002. "Identifying Hedonic Models," American Economic Review, American Economic Association, vol. 92(2), pages 304-309, May.
    7. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    8. Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
    9. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    10. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    11. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    12. Bayer, Patrick & Keohane, Nathaniel & Timmins, Christopher, 2009. "Migration and hedonic valuation: The case of air quality," Journal of Environmental Economics and Management, Elsevier, vol. 58(1), pages 1-14, July.
    13. Biao Sun & Shan Yang, 2020. "Asymmetric and Spatial Non-Stationary Effects of Particulate Air Pollution on Urban Housing Prices in Chinese Cities," IJERPH, MDPI, vol. 17(20), pages 1-23, October.
    14. Gonzalez, Fidel & Leipnik, Mark & Mazumder, Diya, 2013. "How much are urban residents in Mexico willing to pay for cleaner air?," Environment and Development Economics, Cambridge University Press, vol. 18(3), pages 354-379, June.
    15. Magdalena Ligus & Piotr Peternek, 2017. "Impacts of Urban Environmental Attributes on Residential Housing Prices in Warsaw (Poland): Spatial Hedonic Analysis of City Districts," Springer Proceedings in Business and Economics, in: Krzysztof Jajuga & Lucjan T. Orlowski & Karsten Staehr (ed.), Contemporary Trends and Challenges in Finance, pages 155-164, Springer.
    16. José-María Montero & Román Mínguez & Gema Fernández-Avilés, 2018. "Housing price prediction: parametric versus semi-parametric spatial hedonic models," Journal of Geographical Systems, Springer, vol. 20(1), pages 27-55, January.
    17. Piras, Gianfranco, 2010. "sphet: Spatial Models with Heteroskedastic Innovations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i01).
    18. David M. Drukker & Peter Egger & Ingmar R. Prucha, 2013. "On Two-Step Estimation of a Spatial Autoregressive Model with Autoregressive Disturbances and Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 686-733, August.
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