Skip to main content

Effect of Air Pollution on the Stock Yield of Heavy Pollution Enterprises in China’s Key Control Cities Under Climate Change

  • Chapter
  • First Online:
Economic Impacts and Emergency Management of Disasters in China
  • 684 Accesses

Abstract

Under the background of climate change, the haze days in China have increased significantly, which seriously hinders the sustainable development of society and arouses wide attention from the public. However, the researches on the effect of air pollution on the stock yield of heavy pollution enterprise in key control cities are quite limited. Thus, this paper collects the AQI (air quality index) of key control cities (over prefecture-level) in China and the stock yields of listed heavy pollution enterprises in these cities from 2011 to 2016, and through multi-discontinuities regression model, testes the effect of air pollution on the stock yield of heavy pollution enterprise. The results show that: (1) severe air pollution (AQI = 300) has a significant negative influence on stock yield and the results are robust; (2) there is a time effect in the influence of air pollution on stock yield and the negative influence has become significant since 2013. This paper gives a brief discussion on the cause of it and suggests that severe air pollution should be strictly controlled. Only by facing air pollution seriously, can we eliminate air pollution with collective wisdom and concerted efforts and achieve the sustainable development of city. Being the first study to look into the effect of air pollution on stock yield in key control cities in China, this paper provides empirical reference for government supervision departments, stock investors as well as enterprises.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.healtheffects.org/Internationl/GBD-Press-Release.pdf.

  2. 2.

    Website: https://datacenter.mep.gov.cn/report/air.daily/air.dairy_api.jsp.

  3. 3.

    According to the Notice on Special Emission Limits on Air Pollutants, the six industries in major monitoring areas include thermal power industry, iron and steel industry, petrochemical industry, cement industry, non-ferrous metals industry, and chemical industry. The key control area contains 19 provinces (autonomous regions/municipalities). They are Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Guangdong, Liaoning, Shandong, Hubei, Hunan, Chongqing, Sichuan Province, Fujian, Shanxi, Shaanxi, Gansu, Ningxia, and Xinjiang.

  4. 4.

    According to the Industry Classification Standard for Listed Company (2012 Edition) issued by China Securities Regulatory Commission, the above six industries are further divided into 12 sub-industries: B07 (petroleum and natural gas extraction), B08 (ferrous metal mining), B09 (nonferrous metal mining), C19 (leather and fur products and shoes), C25 (petroleum processing, coking, and nuclear fuel processing), C26 (manufacture of chemical raw materials and chemicals), C28 (manufacture of chemical fibers), C29 (rubber and plastics products), C30 (manufacture of non-metallic mineral), C31 (ferrous metal smelting and rolling), C32 (Non-ferrous metal smelting and rolling), and D44 (production and supply of electricity and heat).

  5. 5.

    The bandwidths of the last two Discontinuities 200 and 300 are 50.

References

  • Abu, B. A., Siganos, A., & Vagenas-Nanos, E. (2014). Does mood explain the monday effect? Journal of Forecasting,33(6), 409–418.

    Google Scholar 

  • An, N., Wang, B., Pan, P., et al. (2017). Study on the influence mechanism of air quality on stock market yield and volatility: Empirical test from China based on GARCH model. Finance Research Letters,26, 119–125.

    Google Scholar 

  • Apergis, N., & Gupta, R. (2017). Can weather conditions in New York Predict South African stock returns? Research in International Business & Finance,41, 377–386.

    Google Scholar 

  • Arnott, R. D., Kelso, C. M., et al. (1989). Forecasting factor returns an intriguing possilbility. Journal of Portfolio Management,16(1), 28–35.

    Google Scholar 

  • Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance,61(4), 1645–1680.

    Google Scholar 

  • Banerjee, A. V. (1992). A simple model of herd behavior. Quarterly Journal of Economics,107(3), 797–817.

    Google Scholar 

  • Baylis, P., Obradovich, N., Kryvasheyeu, Y., et al. (2018). Weather impacts expressed sentiment. Public Library of Science One,13(4), e0195750. https://doi.org/10.1371/journal.pone.0195750.

    Article  Google Scholar 

  • Beecher, M. E., Eggett, D., Erekson, D., et al. (2016). Sunshine on my shoulders: Weather, pollution, and emotional distress. Journal of Affective Disorders,205, 234–238.

    Google Scholar 

  • Brollo, F., Perotti, R., et al. (2013). The political resource curse. The American Economic Review,103(5), 1759–1796.

    Google Scholar 

  • Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance,11(1), 1–27.

    Google Scholar 

  • Bullinger, M. (1990). Environmental stress: Effects of air pollution on mood. Neuropsychological function and physical state. In S. Puglisi-Allegra, & A. Oliverio (Eds.), Psychobiology of stress (Vol. 54, pp. 241–250).

    Google Scholar 

  • Cai, W. J., Li, K., Liao, H., Wang, H. J., et al. (2017). Weather conditions conducive to Beijing severe haze more frequent under climate change. Nature Climate Change,7, 257–262.

    Google Scholar 

  • Chen, Y. B. (2005). Mood fluctuations and volatility of asset prices. Economic Research (China),3, 36–45.

    Google Scholar 

  • Chen, Y., Jin, G. Z., Kumar, N., et al. (2012). Gaming in air pollution Data? Lessons from China. Social Science Electronic Publishing, 12(3), 1–43.

    Google Scholar 

  • Chen, X. Y., Zhang, T. Y., & Chen, D. H. (2001). Cross sectional analysis of expected stock returns: Evidence from Chinese stock market. Financial Research (China),6, 22–35.

    Google Scholar 

  • Chen, S. F., Xie, W., & Zhu, X. Q. (2011). On Chinese investors’ subjective concept of stock market under the expectation of adaptability. Economic Theory and Economic Management (China),7, 76–79.

    Google Scholar 

  • Coates, J., & Herbert, J. (2008). Endogenous steroids and financial risk taking on a London trading floor. Proceedings of the National Academy of Sciences,105(16), 6167–6172.

    Google Scholar 

  • Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under and overreactions. Journal of Finance,53(6), 1839–1885.

    Google Scholar 

  • Dash, S. R., & Maitra, D. (2017). Does sentiment matter for stock returns? Evidence from Indian stock market using wavelet approach. Finance Research Letters,26, 32–39.

    Google Scholar 

  • Ding, Z. G., & Suzhi, Z. (2005). Investor sentiment, intrinsic value estimation and stock price volatility. World Management (China),2, 143–145.

    Google Scholar 

  • Eagles, J. M. (1994). The relationship between mood and hours of sunlight in rapid cycling bipolar illness. Biological Psychiatry,36(6), 422–424.

    Google Scholar 

  • Evans, G. W., Jacobs, S. V., Dooley, D., & Catalano, R. (1987). The interaction of stressful life events and chronic strains on community mental health. American Journal of Community Psychology,15(1), 23–34.

    Google Scholar 

  • Fu, S. X., Zhang, B., & Zhang, W. B. (2011). Environmental regulation and “pollution heaven” effect of China’s industrial regional distribution. Journal of Shanxi Finance and Economics University (China),7, 8–14.

    Google Scholar 

  • Forgas, J. P., & Bower, G. H. (1987). Mood effects on person – perception judgments. Journal of Personality & Social Psychology,53(1), 53–60.

    Google Scholar 

  • Goetzmann, W. N., Kim, D., Kumar, A., et al. (2015). Weather-induced mood, institutional investors, and stock returns. Review of Financial Studies,28(1), 73–111.

    Google Scholar 

  • Guo, Y. J., & Zhang, Y. H. (2016). Will air quality affect the stock market? Journal of Financial Research (China),2, 71–85.

    Google Scholar 

  • Hahn, J., Todd, P., & Van der Klaauw, W. (2001). Identification and estimation of treatment effects with a regression-discontinuity design. Journal of Econometrica,69(1), 201–209.

    Google Scholar 

  • Harding, N., & He, W. (2016). Investor mood and the determinants of stock prices: An experimental analysis. Accounting & Finance,56(2), 445–478.

    Google Scholar 

  • Haritha, P. H., & Rishad, A. (2020). An empirical examination of investor sentiment and stock market volatility: Evidence from India. Financial Innovation,6(1), 34. https://doi.org/10.1186/s40854-020-00198-x.

    Article  Google Scholar 

  • He, Z. G. (2001). Empirical study on risk factors of Chinese stock market. Economic Review (China),3, 81–85.

    Google Scholar 

  • Hirshleifer, D. (2001). Investor psychology and asset pricing. Journal of Finance,56(4), 1533–1597.

    Google Scholar 

  • Hirshleifer, D., & Shurnway, T. (2003). Good day sunshine: Stock returns and the weather. Journal of Finance,58(3), 1009–1032.

    Google Scholar 

  • Hsiao, H. F., Xia, C. Y., Yuksel, S., & Dincer, H. (2020). Comparative analysis of investor sentiment with weather conditions using interval type 2 fuzzy hybrid decision making and regression methods: Evidence from Chinese stock market. Economic Computation and Economic Cybernetics Studies and Research,54(3), 263–278.

    Google Scholar 

  • Hu, W. Y., Huang, C. J., Chang, H. Y., et al. (2015). The effect of investor sentiment on feedback trading and trading frequency: Evidence from Taiwan intraday data. Emerging Markets Finance & Trade,51(1), S111–S120.

    Google Scholar 

  • Hu, X., Li, O. Z., & Lin, Y. (2014). Particles, pollutions and prices (pp. 1–60). Social Science Electronic Publishing.

    Google Scholar 

  • Huang, J. K., Xu, N. H., & Yu, H. H. (2020). Pollution and performance: Do investors make worse trades on hazy days? Management Science,66(10), 4455–4476.

    Google Scholar 

  • Isen, A. M. (1993). Positive affect and decision making. In Handbook of emotions (pp. 261–277).

    Google Scholar 

  • Jin, Z., Yang, Y., & Liu, Y. (2020). Stock closing price prediction based on sentiment analysis and LSTM. Neural Computing and Applications,32(13), 9713–9729.

    Google Scholar 

  • Kaplanski, G., & Levy, H. (2010). Sentiment and stock prices: The case of aviation disasters. Journal of Financial Economics,95(2), 174–201.

    Google Scholar 

  • Kong, D., Liu, S., & Dai, Y. (2012). Environmental policy, company environment protection, and stock market performance: Evidence from China. Corporate Social Responsibility and Environmental Management,21(2), 100–112.

    Google Scholar 

  • Lee, C., Shleifer, A., & Thaler, R. H. (1991). Investor sentiment and the closed-end fund puzzled. The Journal of Finance,46(1), 75–109.

    Google Scholar 

  • Lee, D. S. (2008). Randomized experiments from non-random selection in US House elections. Journal of Econometricsm,142(2), 675–697.

    Google Scholar 

  • Lepori, G. M. (2009). Environmental stressors, mood, and trading decisions: Evidence form ambient air pollution. Working papers series, Available at SSRN: http://ssrn.com/abstract=1284549.

  • Lepori, G. M. (2015). Investor mood and demand for stocks: Evidence from popular TV series finales. Journal of Economic Psychology,48, 33–47.

    Google Scholar 

  • Lepori, G. M. (2016). Air pollution and stock returns: Evidence from a natural experiment. Journal of Empirical Finance,35, 25–42.

    Google Scholar 

  • Levy, T., & Yagil, J. (2011). Air pollution and stock returns in the US. Journal of Economic Psychology,32(3), 374–383.

    Google Scholar 

  • Li, Y. X., & Liu, X. (1997). An empirical study on the impact of dividend policy on stock price. Journal of Chongqing University (China),20(5), 78–82.

    Google Scholar 

  • Li, Q., & Peng, C. H. (2016). The stock market effect of air pollution: Evidence from China. Applied Economics,48(36), 3442–3461.

    Google Scholar 

  • Li, X. D., & Wang, Y. N. (2002). An empirical study on the trading behavior of individual securities investors in China. Economic Research (China),11, 54–63.

    Google Scholar 

  • Lin, S., Yu, Q., Tang, Z. Y., et al. (2006). An experimental study on the “hot hand effect” and “gambler’s fallacy” of Chinese investors. Economic Research (China),8(2), 56–69.

    Google Scholar 

  • Lin, S., & Yu, Q. (2010). Bounded rationality, animal spirits and market crashes: An experimental study of mood swings and trading behavior. Economic Research (China),8, 115–127.

    Google Scholar 

  • Liu, Y. G., & Liu, M. G. (2015). Haze affected heavily polluting enterprises earnings management? Based on the political cost hypothesis. Accounting Research (China),3, 79–101.

    Google Scholar 

  • Lu, J. (2011). Study on the weather effect of Chinese stock market. China Soft. Science, 000(006), 65–78,192.

    Google Scholar 

  • Lucey, B. M., & Dowling, M. (2005). The role of feelings in investor decision-making. Journal of Economic Surveys,19(2), 217–237.

    Google Scholar 

  • Lundberg, A. (1996). Psychiatric aspects of air pollution. Otolaryngology - Head and Neck Surgery,114(2), 227–231.

    Google Scholar 

  • McCrary, J. (2008). Manipulation of the running variable in the regression discontinuity design: A density test. Journal of Econometrics, 142(2), 698–714.

    Google Scholar 

  • Mehra, R., & Sah, R. (2002). Mood fluctuations, projection bias, and volatility of equity prices. Journal of Economic Dynamic and Control,26(5), 869–887.

    Google Scholar 

  • Mulatu, A., Gerlagh, R., Rigby, D., & Wossink, A. (2010). Environmental regulation and industry location in Europe. Environmental and Resource Economics,45(4), 459–479.

    Google Scholar 

  • Naeem, M. A., Farid, S., Faruk, B., et al. (2020). Can happiness predict future volatility in stock markets? Research in International Business and Finance,101298. https://doi.org/10.1016/j.ribaf.2020.101298.

  • Nelson, S. (1903). The ABC of stock market speculatio. Fraser Publishing.

    Google Scholar 

  • Nowakowicz-Debek, B., Saba, L., & Bis-Wencel, H. (2004). The effects of air pollutants on the cortisol and progesterone secretion in Polar Fox (Alopex lagopus). Scientifur,28(3), 218–221.

    Google Scholar 

  • Oberndorfer, U., & Andreas, Z. (2006). Environmentally oriented energy policy and stock returns: An empirical analysis. ZEW working paper, 06–079.

    Google Scholar 

  • Papakyriakou, P., Sakkas, A., & Taoushianis, Z. (2019). The impact of terrorist attacks in G7 countries on international stock markets and the role of investor sentiment. Social Science Electronic Publishing,61, 143–160.

    Google Scholar 

  • Peng, Y. F., Tang, J. H., Fu, Y. C., et al. (2016). Analyzing personal happiness from global survey and weather data: A geospatial approach. Public Library of Science One,11(4), e0153638. https://doi.org/10.1371/journal.pone.0153638.

    Article  Google Scholar 

  • Rahman, M. L., & Shamsuddin, A. (2019). Investor sentiment and the price-earnings ratio in the G7 stock markets. Pacific Basin Finance Journal,55, 46–62.

    Google Scholar 

  • Saunders, E. (1993). Stock prices and wall street weather. American Economic Review,83(5), 1337–1345.

    Google Scholar 

  • Schottenfeld, R. S. (1992). Psychologic sequelae of chemical and hazardous materials exposures. In J. B. Sullivan & G. R. Krieger (Eds.), Hazardous materials toxicology (pp. 463–470). Baltimore: Williams & Wilkins.

    Google Scholar 

  • Sexton, A. L. (2012). Responses to air quality alerts: Do Americans spend less time outdoors? Human reactions and political economy. In Association of Environmental and Resource Economists, 2nd Annual Summer Conference, 3–5 June, Asheville, NC.

    Google Scholar 

  • Shan, L. W. (2011). Psychology or substance: The impact of Wenchuan earthquake on China’s capital market. Economic Research (China),4, 121–134.

    Google Scholar 

  • Shahzad, F. (2019). Does weather influence investor behavior, stock returns, and volatility? Evidence from the Greater China region. Physica A-Statistical Mechanics and Its Applications,523, 525–543.

    Google Scholar 

  • Shi, Y., Tang, Y. R., Cui, L. X., et al. (2018). A text mining based study of investor sentiment and its influence on stock returns. Economic Computation and Economic Cybernetics Studies and Research,52(1), 183–199.

    Google Scholar 

  • Song, J., Zhao, Y., & Wu, C. F. (2003). A model of leader-follower in the securities market. Systems Engineering-Theory & Practice (China),23(1), 1–8.

    Google Scholar 

  • Tan, S. T., & Chen, Y. Y. (2012). Investment experience can improve the income of investors: Based on the transaction records of investors. Economic Research (China),5, 164–178.

    Google Scholar 

  • Teng, M., & He, X. B. (2020). Air quality levels, environmental awareness and investor trading behavior: Evidence from stock market in China. Journal of Cleaner Production,244, 118663. https://doi.org/10.1016/j.jclepro.2019.118663.

    Article  Google Scholar 

  • Thaler, R. H. (1993). Advances in behavioral finance. Princeton University Press.

    Google Scholar 

  • Wang, M., & Sun, J. J. (2004). Stock market returns, volatility and the role of investor sentiment in China. Economic Research (China),10, 75–83.

    Google Scholar 

  • Wright, W. F., & Bower, G. H. (1992). Mood effects on subjective probability assessment. Organizational Behavior and Human Decision Processes,52(2), 276–291.

    Google Scholar 

  • Wu, Q., & Lu, J. (2020). Air pollution, individual investors, and stock pricing in China. International Review of Economics & Finance,67, 267–287.

    Google Scholar 

  • Wu, Y. R., & Han, L. Y. (2007). Incomplete rationality, investor sentiment and closed-end fund puzzle. Economic Research (China),3, 117–129.

    Google Scholar 

  • Xi, P. H., & Liang, R. B. (2015). The impact of air pollution on local environmental protection input–based on multiple breakpoint regression. Statistical Research (China),32(9), 76–83.

    Google Scholar 

  • Yang, X., Wang, X. Z., & Tang, X. X. (2004). Herding effects of individual and institutional investors in Chinese stock market. The Journal of Tsinghua University (China),12, 1610–1614.

    Google Scholar 

  • Ying, Q. W., Yousaf, T., ul Ain, Q., et al. (2020). Investor psychology, mood variations, and sustainable cross-sectional returns: A Chinese case study on investing in illiquid stocks on a specific day of the week. Frontiers in Psychology, 11, 173. https://doi.org/10.3389/fpsyg.2020.00173.

  • Yu, J. W., & Wang, C. C. (2011). Breakpoint regression and its application in economics. Economic Perspectives (China),2, 125–131.

    Google Scholar 

  • Zheng, S. Q., Zhang, X. N., & Sun, Y. (2016). The mechanism of the effect of air pollution on outdoor activities of urban residents. Journal of Tsinghua University (China),56(1), 89–96.

    Google Scholar 

  • Zhou, H. (1999). Study on the comprehensive index of the effect of climate change on human health. Climate and Environmental Research (China),4(1), 121–126.

    Google Scholar 

Download references

Acknowledgements

Shanshan Chen, Ge Gao, Yanmin Liu also made great contributions to this manuscript. We express our heartfelt thanks to them. This research was supported by: National Social and Scientific Fund Program of China (18ZDA052; 17BGL142; 16ZDA047); The Natural Science Foundation of China (91546117, 71373131).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xianhua Wu .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Wu, X., Guo, J. (2021). Effect of Air Pollution on the Stock Yield of Heavy Pollution Enterprises in China’s Key Control Cities Under Climate Change. In: Economic Impacts and Emergency Management of Disasters in China. Springer, Singapore. https://doi.org/10.1007/978-981-16-1319-7_15

Download citation

Publish with us

Policies and ethics