Does severe air pollution affect firm innovation: evidence from China

ABSTRACT

This study investigates the influence of air pollution on firm innovation by using Chinese listed firms. Our results indicate that firms headquartered in a city with severe air pollution tend to engage less in innovation activities. To more explicitly identify causality, we establish a 2SLS where the air quality is instrumented by the local thermal inversions. This negative effect is primarily driven by brain drain channels, specifically the migration of highly skilled employees. In addition, such a negative effect is more pronounced for firms with low employee salaries and those belonging to competitive industries. The results are robust to a variety of model specifications and alternative measures.

KEYWORDS:

• Air pollution
• human capital
• firm innovation
• brain drain

JEL CLASSIFICATION:

• G30
• Q53
• O31

Article highlights

• We study the effect of air pollution on innovation by using firm-level data in China.

• We find a negative causal effect of air pollution on firm innovation. To more explicitly identify causality, we establish a 2SLS where the air quality is instrumented by the local thermal inversions.

• The negative effect is primarily driven by the migration of highly skilled employees.

• The negative effect is greater for firms with low employee salaries and those belonging to competitive industries.

Acknowledgments

We acknowledge the helpful comments from Lihua Liu and Jingyi Xiong. This work was supported by the Fundamental Research Funds for the Central Universities, Zhongnan University of Economics and Law(2722020JCG082), the Humanities and Social Sciences Youth Foundation of Ministry of Education of China (17YJC790018), and the National Natural Science Foundation of China (71702061; 71874061; 71902185). All errors are our own.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The data can be downloaded at https://disc.sci.gsfc.nasa.gov/uui/datasets/M2I6NPANA_V5.12.4/summary?keywords=%22MERRA-2%22%20M2I6NPANA&start=1920-01-01&end=2017-01-16.

² Patents citation data are still not publicly available in China so far, we acknowledge the limitation and do hope to further develop new empirical proxies that better capture the extent of firm innovation activities when more data is available.

³ We also use the number of patents registered per sales as the measure of innovation (Acs and Audretsch, 1989) and find a robust negative effect of air pollution on firm innovation.

⁴ The AQI in China is constructed based on the concentration levels of six atmospheric pollutants: SO₂ (sulphur dioxide), NO₂ (nitrogen dioxide), PM₁₀ (particulate matter 10), PM_2.5 (particulate matter 2.5), CO (carbon monoxide), and O₃ (ozone). Before 2014, the Chinese government monitored only SO₂, NO₂, and PM₁₀ to construct the API that served as a summary measure of air quality in earlier years (Dong et al. 2019). The AQI and API are not directly comparable, but they are highly correlated (Zheng et al., 2014). For simplicity, we refer to both as AQI in the following discussion.

⁵ The HHI is calculated as the sum of the squares of the market shares of all firms in the industry.

⁶ The original data on thermal inversions are from MERRA-2, which divides the Earth by 0.5 degree χ 0.625 degree (around 50 km$\times$60 km) grid, and records the 6-hour air temperature at 42 layers ranging from the surface to 36,000 metres. Following Chen et al. (2017), we calculate the temperature difference using the temperature in the second layer (320 metres) minus the temperature in the first layer (110 metres) within in each 6-hour period. If the difference is positive, then thermal inversions and the value of the difference measure the inversion strength. If the difference is negative, then such a condition is normal, and we truncate the difference to zero. We aggregate all data from the grid to the city level and match them with other firm-level data.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities, Zhongnan University of Economics and Law [2722020JCG082]; Humanities and Social Sciences Youth Foundation of Ministry of Education of China [17YJC790018]; The National Natural Science Foundation of China [71902185,71702061,71874061].