With the outbreak of COVID-19 (Corona Virus Disease, 2019), China adopted traffic restrictions to reduce the spread of COVID-19. Using daily data before and after the outbreak of COVID-19, an exogenous shock, this paper analyzes the effects of private vehicle restriction policies on air pollution. We find that the private vehicle restriction policies reduce the degree of air pollution to a certain extent. However, their effect varies with other policies implemented in the same period and the economic development of the city itself. Through the analysis of different categories of restrictions, we find that restriction policy for local fuel vehicles and the restriction policy based on the last digit of license plate numbers have the best effect in reducing air pollution. Under the background of COVID-19 epidemic and the implementation of private vehicle restriction policies and other traffic control policies during this period, we have also obtained other enlightenment on air pollution control.

Using data from 3212 enterprises in China's A-share market during the 2007-2018 period, this paper investigates the relationship between green innovation (GI) and enterprise value by using ordinary least squares (OLS) and two-stage least squares (2SLS) regression. We find that for every 1% increase in the proportion of the number of the enterprise's green patent applications, the enterprise value (Tobin's Q) will increase by 0.023. Moreover, GI still has a positive lag effect on enterprise value after 2 to 6 years. However, the positive effect of GI on enterprise value may only exist in young non-state-owned enterprises. At the same time, GI has better performance in heavy pollution industries and non-high-tech industries. Moreover, we prove that the improvement of profitability may be a mechanism for GI to affect enterprise value, with a mediating effect accounting for 26.1% of the total effect. The finding on the causal relationship between GI and enterprise value in this study is of great significance for further understanding of the practical value of GI and has certain reference value for the formulation of incentive policies for different industries and enterprises.

Using the data of Chinese listed enterprises in 2007-2020, we investigate the relationship between green innovation (GI) and enterprise reputation via OLS regression, IV-Lasso, and random forest. Findings show that GI can improve enterprise reputation, and it has a significant positive lag effect. Additionally, we compare the different effects of green patent applications and approved green patents. A possible mechanism is that GI reduces the pollution emission of enterprises. GI also performs better in improving the reputation of coastal enterprises, state-owned enterprises and large-scale enterprises, and old enterprises. Our finding on the causal relationship between GI and enterprise reputation is of great significance in further understanding the practical value of GI activities, and it has certain reference value for the policy formulation of governments and decision making of enterprises.

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