With the fast-growing consumption of automobiles in China, vehicle fumes appear to be one of the major contributors to PM_2.5 (fine particles with a diameter of 2.5 μm or less) emissions. As a type of green transportation, Chinese urban subway transit has developed rapidly in recent years. This paper estimates the effect of urban subway openings on PM_2.5 concentrations in Chinese cities. Using daily air quality data for 29 Chinese cities from 2013 to 2018, and using regression discontinuity design, we find that new subway openings reduce PM_2.5 concentrations by an average of 18 μg/m³. The potential mechanism for this emission reduction is due to the offset in on-road transportation, and the use of cleaner energy. Also, central heating in winter, population scale, and city tier play crucial roles in the emission-reducing effect of subway openings. A series of robustness tests are conducted to support the fundamental empirical results. Targeted policy implications, such as optimizing the planning of urban subway construction and road network, fostering awareness of green travel, and promoting the innovation of emission-reducing technologies, are suggested for sustainable development in Chinese cities.

This paper studies the impact of the COVID-19 pandemic on the sustainability of Chinese economic growth, government debt, and income inequality by constructing a new Keynesian dynamic stochastic general equilibrium (NK-DSGE) model. The choice of monetary policy targets is then analyzed to hedge the impact of the pandemic. We find that: (1) the aggregate demand and labor demand shocks caused by the COVID-19 pandemic posed serious challenges to the sustainable development of the economy and debt, and increased social inequality; (2) when the impact of the pandemic is mainly reflected in the recession in aggregate demand, monetary policy should pay more attention to the target of price stability; (3) when the impact of the pandemic is mainly reflected in a decline in labor demand, monetary policy should focus more on the target of economic growth; (4) when the pandemic has a significant impact on both aggregate demand and labor demand, a monetary policy which focuses more on the target of economic growth is conducive to minimizing welfare losses. Targeted policy implications, such as selecting monetary policy targets according to different manifestations of the impact of the COVID-19 pandemic and placing emphasis on monetary policy tools to stimulate consumption, alleviate unemployment, and alleviate social inequality, are suggested to improve the sustainability of the Chinese economy.

The effectiveness of government environmental policies is pivotal to environmental quality and provides the reference for further policy design. This paper estimates the effect of comprehensive demonstration of fiscal policy for ECER (Energy Conservation and Emission Reduction) on pollution emissions in Chinese cities with the sample period from 2003 to 2016, which is an important practice for policy integration. We find that this policy reduces the industrial SO₂ (sulfur dioxide) emission by 23.8% on average and the industrial wastewater emission by 17.5% on average. This policy, implemented by Chinese government, has effectively achieved its target for emission reduction. A series of robustness checks are also conducted to verify the baseline results. Mechanism analysis indicates that this policy has the effect by the change in the industry structure and the enhancement of fiscal capacity, especially the capacity of fiscal revenue. Some policy recommendations, such as laying emphasis on the policy integration, integrating the financial resources of governments and expanding the demonstration effect, are proposed in order to facilitate green development in Chinese cities.

With the explosion of social media, consumers’ minds have become important assets in brand competitions. Determining a brand’s competitive structure based on consumers’ desires is particularly important to effectively establish a brand and maintain sustainable competitiveness. The traditional methods of determining brand competitiveness are costly and time-consuming. In this study, we propose an efficient, systematical, highly automated, and real-time method to determine brand competitiveness based on consumers’ brand associations with the brand’s social tags. Using a set of 45 brands in the automobile industry and around 50,000 social tags, we compared our brand competitiveness determination method with data provided by Interbrand and directly elicited survey data, finding a significant correlation and a better predictive power in consumers’ perceived brand competitiveness than the traditional method. Our proposed method enables managers to create and maintain sustainable brand advantages in consumers’ minds.