Air pollution, stock returns, and trading activities in China☆

Health Damage of Air Pollution, Governance Uncertainty and Economic Growth

The evaluation of environmental and health governance processes is an important part of the innovation and perfection of modern governance systems. Based on the macropanel samples, this paper analyzes the impact of the health damage caused by air pollution (APHD) on economic growth and the related mechanisms accordingly using the moderate model and the threshold model. The results can be concluded as follows: (1) After locking in the health damage perspective, the APHD has a negative impact on economic growth. When other conditions are met, economic growth will significantly drop by 1.233 percent for each unit increase in the APHD index. (2) There is a moderate effect of governance uncertainty in APHD on economic growth with different characteristics. The combination of governance uncertainty and APHD can significantly inhibit economic growth, and this moderating effect has different impacts due to heterogeneous conditions. Spatially, this inhibitory effect is significantly obvious in the eastern, central, and western regions, while the negative effect is significant in areas north of the Huai River with medium and low self-defense ability. Additionally, compared with the delegating of governance power at the municipal level, when the governance power is delegated at the county level, the interaction between the governance uncertainty constructed by income fiscal decentralization and APHD has a less negative economic effect. (3) There is a threshold effect under the conditions of a low level of decentralization of prevention and control, a high level of investment in governance, and a low level of APHD. However, under the condition of a certain APHD level, when the decentralization level of pollution control is higher than 7.916 and the input level of pollution control in GDP is lower than 1.77%, the negative moderating effect can be effectively reduced.

Is air pollution politics or economics? Evidence from industrial heterogeneity

This paper checks the asymmetrical impact of Beijing's and Shanghai's air quality (AQ) on cross-industries stock returns (SR) by using the quantile-on-quantile (QQ) regression method. The major empirical findings as shown as followings. There are heterogeneous responses from SR to AQ within the same city. Different links are discovered for Beijing and Shanghai within the same industry. Air pollution does not have political or economic properties for all industries. Our research provides useful contributions compared with past literature. First of all, we distinguish whether air pollution is political or economic. Apart from psychology and physiology, government intervention and economic expectation are also important components in interpreting the influence from AQ to SR. Second, this study adequately considers the heterogeneity of industries. Industries differently react to the identical extrinsic shock, depending on the nature of their industry. Besides, the QQ approach captures quantile-varying relationship between variables, and does not need to consider structural fracture and time lag effects. The practical significance is that investors need to focus on national industrial policies, and avoiding biased decisions in stock market from air pollution.

How does public environmental supervision affect the industrial structure optimization?

Based on the panel data of 278 prefecture-level cities in China from 2005 to 2017, this study takes the environmental information disclosure policy implemented in 2008 as a quasi-natural experiment and uses the difference-in-difference method to examine the impact of public environmental supervision on industrial structure upgrading. This study found that public environmental supervision has indeed significantly promoted the industrial structure optimization. It is noteworthy that, the impact of public environmental supervision on industrial structure optimization is heterogeneous across regions and corresponding to the intensity of environmental regulations. Public environmental supervision in the eastern region has significantly promoted the optimization of the industrial structure, while the promotion effect in the central and western regions is not obvious. Besides, the effect of public environmental supervision is more significant in the cities with relatively tight traditional environmental regulations. The mechanism analysis shows that public environmental supervision promotes industrial structure upgrading mainly by influencing the level of urban technological innovation, and the level of technological innovation plays an intermediary role between public environmental supervision and industrial structure optimization. This study has important reference significance for further improving the environmental information disclosure system and constructing an environmental governance system with the government as the leading body, enterprises as the main body, and the public as the common participation.

Air pollution, investor sentiment and stock liquidity

With the aggravation of air pollution, the impact of air pollution on the stock market, especially from the perspective of investor sentiment, has been of great concern and widely discussed. Based on data from China's A-share listed firms from January 1, 2016, to December 31, 2020, the relationship between urban air pollution and stock liquidity of listed firms and the internal mechanism is examined. Firstly, based on local preference theory, we start by predicting the impact of air pollution on stock liquidity. We, then, build a regression model for air pollution and stock liquidity, introducing the intermediary effect model to detect the relationship between the two and its mechanism. Finally, by subdividing the samples, we discuss the differential impact of air pollution on stock liquidity under different circumstances. We found that when air pollution worsens it reduces stock liquidity. The results of the mechanism analysis show that investor sentiment plays an intermediary role in the process of air pollution affecting stock liquidity, and pessimism induced by air pollution can reduce stock liquidity. Heterogeneity test results show that there are differences in the impact of air pollution on stock liquidity between heavily polluting firms and non-heavily polluting firms, different industries, different city sizes, and different levels of air pollution, has a greater effect in non-heavily polluting enterprises, manufacturing and other industries, medium sized cities and light pollution. The results of this research have important reference value for environmental protection departments to establish and improve air pollution monitoring systems and for listed firms to improve stock liquidity and deal with the environmental financial risks appropriately.

Firm-level short selling and the local COVID-19 pandemic: Evidence from China

Short seller trading behavior attracts much attention, especially when negative shocks occur. Recent literature has focused on the impact of the COVID-19 pandemic, an unprecedented shock, but evidence on short sellers' reactions is quite scarce. This paper investigates how short sellers responded to the local COVID-19 pandemic in China. Empirical results show that greater numbers of newly confirmed COVID-19 cases in listed firms' headquarters locations are associated with more subsequent short selling of those firms. The results hold after addressing other potential concerns. In addition, the impact of the local COVID-19 pandemic on short selling is stronger for firms with weaker financial conditions, in more vulnerable industries, and with higher risks of a stock price crash. The impact is alleviated after lifting the lockdown restrictions in Wuhan and becomes insignificant in later outbreaks. Overall, our findings support the informational role of short sellers within the context of the COVID-19 pandemic.

Air Pollution, Environmental Violation Risk, and the Cost of Debt: Evidence from China

Although a firm’s exposure to air pollution-related risk has become an important factor that creditors cannot ignore in the procedure of lending decision making with the aggravation of air pollution, empirical evidence on whether and how air pollution affects the cost of debt has been relatively scarce. Employing a series of Chinese listed firms from the main board of the Shanghai and Shenzhen Stock Exchanges covering 2014 to 2018, our research responds to this research gap by exploring how air pollution-induced environmental violation risk affects the cost of debt by constructing an assessment system of firms’ environmental violation risk. The results shed light on an issue that firms exposed to higher concentrations of air pollution may suffer a higher environmental violation risk, resulting in a higher debt cost. In addition, a further analysis shows that environmental regulatory pressure and heavily polluting firms enhance the influence of air pollution on the cost of debt, while state-owned firms and firms’ economic contributions weaken the influence of air pollution on the cost of debt. Our research is conducive to highlighting not only the importance of environmental governance for mitigating the cost of debt to the firms exposed to air pollution, but also its importance to creditors exposed to their clients’ environmental violation risk and default risk.

How Air Quality Affect Health Industry Stock Returns: New Evidence From the Quantile-on-Quantile Regression

This paper discusses the asymmetric effect of air quality (AQ) on stock returns (SR) in China's health industry through the quantile-on-quantile (QQ) regression method. Compared to prior literature, our study provides the following contributions. Government intervention, especially industrial policy, is considered a fresh and essential component of analyzing frameworks in addition to investors' physiology and psychology. Next, because of the heterogeneous responses from different industries to AQ, industrial heterogeneity is thus considered in this paper. In addition, the QQ method examines the effect of specific quantiles between variables and does not consider structural break and temporal lag effects. We obtain the following empirical results. First, the coefficients between AQ and SR in the health service and health technology industries change from positive to negative as AQ deteriorates. Second, AQ always positively influences the health business industry, but the values of the coefficients are larger in good air. In addition, different from other industries, the coefficients in the health equipment industry are negative, but the values of the coefficients change with AQ. The conclusions provide important references for investors and other market participants to avoid biased decisions due to poor AQ and pay attention to government industrial policies.

The Effect of Air Quality and Weather on the Chinese Stock: Evidence from Shenzhen Stock Exchange

We investigated the impact of air quality and weather on the equity returns of the Shenzhen Exchange. To capture the air quality and weather effects, we used dummy variables created by employing a moving average and moving standard deviation. The important results are as follows. First, in the whole sample period (2005–2019), we find that high air pollution and extremely high temperature have significant and negative influence on the equity returns. In the sub-period I (2005–2012), the 11-day model and 31-day model show that high air pollution have significant and negative impacts on the Shenzhen stock returns. Second, the results of the quantile regression show that high air pollution have significant and negative effects during bullish market phase, and extremely high temperature have significant and negative effects during bearish market phase. This implies that the air quality and weather effects are asymmetric. Third, the weather effect of the abnormal temperature on the stock returns is greater in severe bearish market. Whereas the effect of the air pollution on the stock returns is greater in the bullish market. Fourth, the least squares method underestimates the air quality and weather effects compared to the quantile regression method, suggesting that the quantile regression method is more suitable in analyzing these effects in a very volatile emerging market such as the Shenzhen stock market.

Extreme Temperatures and Firm-Level Stock Returns

By linking stock returns with weather conditions from 2007 to 2019 in China, we study how firm-level stock returns react to extreme temperatures. Based on a multivariate ordinary least squares regression model with fixed effects, empirical results show that firm-level stock returns decrease with exposure to extreme temperatures. We further explore the heterogeneity in the temperature-return relation to enrich our understanding of the economic mechanism behind it. The impact of extreme temperatures on abnormal stock returns is more pronounced in smaller, younger, more volatile, less profitable firms and firms with more intangible assets. The results indicate that the investor mood likely plays a role in the extreme temperature effect. The impact of extreme temperatures holds after addressing a series of concerns. Overall, our paper provides additional firm-level evidence on the environment-induced mood effect in the stock market.

The non-linear effect of environmental regulation on haze pollution: Empirical evidence for 277 Chinese cities during 2002-2010

Numerous studies have examined the correlation between economic growth and air pollution, but few focuses on the nexus between environmental regulation and <2.5 μm (PM_2.5) fine particle matter. Using Spatial Durbin Model (SDM) and Spatial Two-stage Least Squares (2SLS) methods to analyze 277 Chinese cities over the period 2002-2010, this paper finds inverted U-shaped relationships between PM_2.5 concentration and formal/informal environmental regulations for the whole and eastern and western regions. By removing the depression year of 2008, regulation effect on pollution strengthened, indicating that the main task for local governments in crisis is to avoid GDP decline rather than official promotion. Further, green technological innovation and industrial structure optimization induced by environmental regulation is shown to be beneficial for haze pollution mitigation. Some policy recommendations are proposed in conclusion.

The asymmetric effect of air quality on cross-industries' stock returns: evidence from China

This paper offers a perspective for the link between air quality and stock returns in China through quantile Granger causality test. Compared to previous studies, the study makes the following innovations. Given the Chinese government plays an important role in economic development, its industrial policies are regarded as a new indispensable supplement of analysis framework apart from investor mood. Next, due to different reflections from cross-industries for different AQ levels, the industry heterogeneity is further considered. Also, nine industries are chosen as a sample, including environmental protection, wind power equipment, steel, photovoltaic equipment, thermal power, tourism, coal, medical service, and medical equipment. Besides, the quantile Granger causality test is robust to misspecification errors when detecting the potential dependence structure between the variables of air quality and stock returns. The empirical results show that the causal link exists in all industries, except medical service. Meanwhile, this impact presents asymmetrical features that when air quality is unhealthy, it has an influence on stock returns of the remaining eight industries. It can be explained by increasing cortisol level, more stringent environmental protection, and industrial policies. These conclusions have essential implications for market participants due to the fact that air quality generates various influences on the stock market. That is why a sustainable environmental design, strict regulatory framework, and special monitoring activities should be highly regarded in China.