Air Pollution Lowers Chinese Urbanites’ Expressed Happiness on Social Media

Posted: 11 Nov 2019

See all articles by Siqi Zheng

Siqi Zheng

Massachusetts Institute of Technology (MIT) - Center for Real Estate; Massachusetts Institute of Technology (MIT) - Department of Urban Studies & Planning; Hang Lung Center for Real Estate, Tsinghua University

Jianghao Wang

Chinese Academy of Sciences (CAS) - Institute of Geographic Sciences and Natural Resources Research (IGSNRR)

Cong Sun

Shanghai University of Finance and Economics

Xiaonan Zhang

Tsinghua University - Department of Construction Management

Matthew E. Kahn

University of Southern California; National Bureau of Economic Research (NBER)

Date Written: October 29, 2019

Abstract

High levels of air pollution in China may contribute to the urban population’s reported low level of happiness1–3. To test this claim, we have constructed a daily city-level expressed happiness metric based on the sentiment in the contents of 210 million geotagged tweets on the Chinese largest microblog platform Sina Weibo4–6, and studied its dynamics relative to daily local air quality index and PM2.5 concentrations (fine particulate matter with diameters equal or smaller than 2.5 μm, the most prominent air pollutant in Chinese cities). Using daily data for 144 Chinese cities in 2014, we document that, on average, a one standard deviation increase in the PM2.5 concentration (or Air Quality Index) is associated with a 0.043 (or 0.046) standard deviation decrease in the happiness index. People suffer more on weekends, holidays and days with extreme weather conditions. The expressed happiness of women and the residents of both the cleanest and dirtiest cities are more sensitive to air pollution. Social media data provides real-time feedback for China’s government about rising quality of life concerns.

Suggested Citation

Zheng, Siqi and Wang, Jianghao and Sun, Cong and Zhang, Xiaonan and Kahn, Matthew E., Air Pollution Lowers Chinese Urbanites’ Expressed Happiness on Social Media (October 29, 2019). Available at SSRN: https://ssrn.com/abstract=3477352

Siqi Zheng (Contact Author)

Massachusetts Institute of Technology (MIT) - Center for Real Estate ( email )

Building 9-323
Cambridge, MA 02139
United States

HOME PAGE: http://https://siqizheng.mit.edu/

Massachusetts Institute of Technology (MIT) - Department of Urban Studies & Planning ( email )

77 Massachusetts Avenue
Cambridge, MA 02139
United States

Hang Lung Center for Real Estate, Tsinghua University ( email )

HeShanHeng Building
Beijing, 100084
China

HOME PAGE: http://https://siqizheng.mit.edu/

Jianghao Wang

Chinese Academy of Sciences (CAS) - Institute of Geographic Sciences and Natural Resources Research (IGSNRR) ( email )

Beijing
China

Cong Sun

Shanghai University of Finance and Economics ( email )

777 Guoding Road
Shanghai, AK Shanghai 200433
China

Xiaonan Zhang

Tsinghua University - Department of Construction Management ( email )

Heshanheng Building
Tsinghua University
Beijing, 100084
China

Matthew E. Kahn

University of Southern California ( email )

2250 Alcazar Street
Los Angeles, CA 90089
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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