Air Pollution and the Effects on House Prices: A Push for Sustainability

Abstract

Environmental sustainability has become an important issue of concern throughout many countries. Among the many sources of concern include air pollution, the effects of which are often capitalized into house prices. In this article, we focus on air pollution in the city of Changsha, China, and the impacts of new pollution regulations on the relationship between pollution exposure and house sales prices. We use the Air Quality Index (Aqi) data from 10 air quality monitoring stations in Changsha to interpolate a previous 12-month average Aqi value for each dwelling unit in the city, based on geographical location. Controlling for important house characteristics such as the living area and the distance to the nearest subway stations, we use the Blue Sky Protection Campaign action plan (BSPC) as the quasi-natural experiment to identify the causal effect of air pollution on house prices. We find dwelling units that were previously in relatively higher-polluted neighborhoods saw their values increase by about 2% after the pollution regulation was implemented, which is statistically significant. This implies China could achieve greater housing wealth for its homeowners by implementing further pollution restrictions, both in Changsha and perhaps also in other parts of the country. Other Asian countries could potentially learn from the results of this analysis.

Keywords:

• Sustainability
• air pollution
• China
• house prices

Acknowledgments

Ping Feng thanks the support from the Key Project of the Education Department of Hunan Province (Project Number. 22A0224) and the Natural Science Foundation of Changsha (Project Number. kq2208238). Ziqi Zhou thanks the support from the Postgraduate Research Innovation Program at Changsha University of Science and Technology (CXCLY2022113). Brandon Peate provided excellent GIS support.

Disclosure Statement

No potential conflict of interest was reported by the author(s)

Notes

1 See https://english.www.gov.cn/state_council/ministries/2018/02/04/content_281476036003188.htm.

2 See http://www.gov.cn/xinwen/2018-02/01/content_5262720.htm

3 The national ecological environment quality profile in 2020, The Ministry of Ecological Environment.

4 Data source: News report released by Ecology and Environment Department of Hunan, http://sthjt.hunan.gov.cn/sthjt/xxgk/xwdt/szxw/202009/t20200903_13698104.html.

5 We estimate one specification with the total residential price as the dependent variable, and separately, another specification with the unit price as the dependent variable (measured in 10,000 yuan per square meter).

6 See Qian (2008), Nunn and Qian (2011), and Feng et al. (2023) for similar estimation strategies.

7 In 2021, Changsha had a total permanent population of 10.2393 million and a GDP of 1327.07 billion yuan. The data comes from the National Bureau of Statistics and Changsha Municipal Bureau of Statistics.

8 GCJ-02 is a coordinate system of the Geographic Information System developed by the National Bureau of Surveying and Mapping of China.

9 Therefore, the monitoring data of air quality stations is the primary data for evaluating air quality. The assessment of air quality is obtained by urban air quality monitoring stations through fixed-point, continuous or timed sampling measurement, and analysis of pollutants present in the atmosphere and air. CNEMC’s air quality monitoring network consists of more than 1400 stations in China (Zheng et al., 2019). The air quality monitoring stations are located in the built-up areas of each city, with relatively uniform distribution, covering all built-up areas.

10 The data from other monitoring stations have similar patterns.

11 See the details about the plan at: https://www.gov.cn/zhengce/content/2018-07/03/content_5303158.htm or http://english.www.gov.cn/policies/latest_releases/2018/07/03/content_281476207708632.htm.

12 The authors thank an anonymous reviewer for pointing out that this interpretation is conditional on the rank invariance assumption, which is a strong assumption to break but hard to test in reality because a treatment can make a subject move up in ranking in the distribution. For more information, please see Liao and Zhao (2019) and Callaway and Li (2019).

Additional information

Funding

This study was supported by the Key Project of the Education Department of Hunan Province (Project Number. 22A0224) and the Natural Science Foundation of Changsha (Project Number. kq2208238), The Postgraduate Research Innovation Program at Changsha University of Science and Technology (CXCLY2022113).