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Measuring the welfare cost of air pollution in Shanghai: evidence from the housing market

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  • Jie Chen
  • Qianjin Hao
  • Chamna Yoon

Abstract

The purpose of this study is to quantify the marginal willingness to pay (MWTP) for clean air in China. We provide the first estimate of MWTP for clean air by implementing a hedonic method using housing price and air quality data from Shanghai. Our estimates imply that air pollution has a significant and negative impact on housing price. We also find that the willingness to pay for better air quality varies significantly across different income groups. This paper helps to deepen our understanding of the economic impacts of air pollution in emerging Asian metropolises where residents are suffering from the most severe respiratory health problems.

Suggested Citation

  • Jie Chen & Qianjin Hao & Chamna Yoon, 2018. "Measuring the welfare cost of air pollution in Shanghai: evidence from the housing market," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 61(10), pages 1744-1757, August.
    • Handle: RePEc:taf:jenpmg:v:61:y:2018:i:10:p:1744-1757
    DOI: 10.1080/09640568.2017.1371581
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    Cited by:

    1. Haiyong Zhang & Sanqin Mao & Xinyu Wang, 2021. "How Much Are People Willing to Pay for Clean Air? Analyzing Housing Prices in Response to the Smog Free Tower in Xi’an," IJERPH, MDPI, vol. 18(19), pages 1-16, September.
    2. Chen, Jie & Chen, Yu & Hill, Robert J. & Hu, Pei, 2022. "The user cost of housing and the price-rent ratio in Shanghai," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    3. Ramesh Chandra Das & Tonmoy Chatterjee & Enrico Ivaldi, 2022. "Nexus between Housing Price and Magnitude of Pollution: Evidence from the Panel of Some High- and-Low Polluting Cities of the World," Sustainability, MDPI, vol. 14(15), pages 1-18, July.
    4. Liu, Yanan & Tang, Yugang, 2021. "Epidemic shocks and housing price responses: Evidence from China's urban residential communities," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    5. Zou, Guojian & Lai, Ziliang & Li, Ye & Liu, Xinghua & Li, Wenxiang, 2022. "Exploring the nonlinear impact of air pollution on housing prices: A machine learning approach," Economics of Transportation, Elsevier, vol. 31(C).

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