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Measuring the impact of pollution on property prices in Madrid: objective versus subjective pollution indicators in spatial models

Author

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  • Román Mínguez
  • José-María Montero
  • Gema Fernández-Avilés

Abstract

Much work has been done in the context of the hedonic price theory to estimate the impact of air quality on housing prices. Research has employed objective measures of air quality, but only slightly confirms the hedonic theory in the best of cases: the implicit price function relating housing prices to air pollution will, ceteris paribus, be negatively sloped. This paper compares the performance of a spatial Durbin model when using both objective and subjective measures of pollution. On the one hand, we design an Air Pollution Indicator based on measured pollution as the objective measure of pollution. On the other hand, the subjective measure of pollution employed to characterize neighborhoods is the percentage of residents who declare that the neighborhood has serious pollution problems, the percentage being referred to as residents’ perception of pollution. For comparison purposes, the empirical part of this research focuses on Madrid (Spain). The study employs a proprietary database containing information about the price and 27 characteristics of 11,796 owner-occupied single family homes. As far as the authors are aware, it is the largest database ever used to analyze the Madrid housing market. The results of the study clearly favor the use of subjective air quality measures. Copyright Springer-Verlag 2013

Suggested Citation

  • Román Mínguez & José-María Montero & Gema Fernández-Avilés, 2013. "Measuring the impact of pollution on property prices in Madrid: objective versus subjective pollution indicators in spatial models," Journal of Geographical Systems, Springer, vol. 15(2), pages 169-191, April.
  • Handle: RePEc:kap:jgeosy:v:15:y:2013:i:2:p:169-191
    DOI: 10.1007/s10109-012-0168-x
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    Citations

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    Cited by:

    1. Ming-Yi Huang, 2023. "Analyzing the effects of green building on housing prices: case study of Kaohsiung, Taiwan," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1205-1235, February.
    2. Myung-Jin Jun, 2018. "Quantifying Welfare Impacts of Air Pollution in Seoul: A Two-Stage Hedonic Price Approach," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 1-25, June.
    3. Prendergast, Patrick & Pearson-Merkowitz, Shanna & Lang, Corey, 2019. "The individual determinants of support for open space bond referendums," Land Use Policy, Elsevier, vol. 82(C), pages 258-268.
    4. Wang, Jianing & Lee, Chyi Lin, 2022. "The value of air quality in housing markets: A comparative study of housing sale and rental markets in China," Energy Policy, Elsevier, vol. 160(C).
    5. José-María Montero & Gema Fernández-Avilés & Tiziana Laureti, 2021. "A Local Spatial STIRPAT Model for Outdoor NO x Concentrations in the Community of Madrid, Spain," Mathematics, MDPI, vol. 9(6), pages 1-33, March.
    6. Nicolás Durán & J. Paul Elhorst, 2023. "Induced earthquakes and house prices: the role of spatiotemporal and global effects," Journal of Geographical Systems, Springer, vol. 25(2), pages 157-183, April.
    7. 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.
    8. Yusep Suparman & Henk Folmer & Johan Oud, 2014. "Hedonic price models with omitted variables and measurement errors: a constrained autoregression–structural equation modeling approach with application to urban Indonesia," Journal of Geographical Systems, Springer, vol. 16(1), pages 49-70, January.

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    More about this item

    Keywords

    Housing prices; Environment; Subjective measure of pollution; Spatial hedonic models; Cluster; Kriging; Q51; R32; C23;
    All these keywords.

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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