Dual-circulation: influence mechanism of ETS's carbon reduction and its spatiotemporal characteristics based on intensity modified SDID model.

Traditional DID models overlook variations in policy intensity, causing estimation deviations from the actual situation and a limited understanding of the influence mechanism. In response, the Intensity Modified SDID Model is built to examine the influence mechanism of ETS's carbon reductions. Moreover, through model extensions, the study explores the spatiotemporal characteristics and heterogeneities of ETS's effects. Results show that: (1) "Dual-circulation" influence mechanism is confirmed, where ETS directly contributes to carbon reductions (2.70% to 10.0% impact) through external pathways, and internal pathways continuously strengthen reduction effects, comprehensive mechanisms are thereby formed and enhanced based on interaction among internal and external pathways. (2) Reasonable ETS levels are estimated and proposed to achieve "Dual Carbon Target", constraining nationwide carbon quotas by 20 billion tons/year, increasing carbon trading volumes by 80 thousand tons/year, and elevating the carbon trading prices by 100 RMB (14 USD) per ton. (3) ETS's carbon reduction effects are identified with temporal and spatial characteristics, temporally, effects peak in the 4th period (Event+4) but diminish in the 5th period (Event+5), spatially, effects peak in areas distancing around 1000 km but disappear beyond 1500 km. (4) ETS also has synergistic effects with atmospheric pollution reduction, including industrial emissions of sulfur dioxide and smoke (dust), but are insignificant to industrial emissions of wastewater and solid waste.

Market or regulation? The competition effect between green finance and environmental enforcement on environmental quality and its "dominate-follow" pattern.

Current research on environmental instruments often isolates the two mainstream types, market-based and regulation-based, overlooking their real-world interactions. In response, the intensity gap variable (EII_GAP) is constructed to link various instruments into a united system. Thus, based on the spatial econometrics of the spatial panel Durbin model (SPDM), the collective effects between market- and regulation-based environmental instruments on environmental quality are explored. Moreover, the political strategies for maximizing environmental benefits are discussed. Results show that the interaction pattern between market- and regulation-based environmental instruments on environmental quality is characterized by competition rather than cooperation. A unit widening in the intensity gap leads to 17 to 18% and 12 to 18% units of environmental quality improvement in local and adjacent areas, respectively. Furthermore, the "dominate-follow" approach as the most effective mode for maximizing environmental effects is proposed. This study recommends employing one type of instrument as the dominant while the other as the auxiliary. In provinces where one kind of environmental instrument takes domination, the environmental quality could be increased by around 8 to 113% after taking another contrary instrument as the auxiliary.

Uncertainty avoidance and investment underdiversification.

The relationship between the cultural dimension of uncertainty avoidance and investment underdiversification is examined. A theoretical link between uncertainty avoidance and ambiguity is established, that is, cultural uncertainty avoidance captures the aversion attitude towards ambiguity at the national group level, thus, cultural dimension of uncertainty avoidance influences investors' behavioral biases of home bias and the investment abroad concentration. The empirical results show that investment underdiversification is significantly and positively affected by the degree of uncertainty avoidance and robustness tests support this conclusion. A further analysis reveals that uncertainty avoidance moderates the effects of ambiguity on investment underdiversification, whereas the effects of uncertainty avoidance are mediated by the status quo bias.

Spatiotemporal consistency effect of green finance on pollution emissions and its geographic attenuation process.

Improving the ecological quality is one of the essential goals of green finance, while interaction between green finance and environmental development has not reached an agreement yet. Using the panel data of 30 provinces from 2010 to 2020, based on the advantage of PTRM-SPDM (Spatial Panel Threshold Durbin Model), this study empirically analyses the relationship between green finance and pollutants emissions from the perspective of the spatiotemporal combination process. After confirming the characteristics of nonlinear constraints and spatial spillovers between green finance and pollutants emissions, the spatiotemporal consistency effects are explored, and the geographic attenuation process, including spatial spillover boundary and influencing dense areas, is also calculated. Results show that: (1) with the development of green finance in China, the environmental effects of green finance transfer gradually from local to adjacent areas, the unit elasticity of green finance decreases by 0.15, 0.19, and 0.22 on emissions of industrial sulfur dioxide, wastewater, and dust in local areas, respectively, while increases by 0.64, 0.02, and 0.82 in neighbouring regions correspondingly. (2) from the evolution trend of the peak value of Kernel density, it could be captured that the overall degree improves and the regional gap narrows for China's green finance in the past decade. (3) the effects of green finance on pollutants emissions merely exist in areas with a radius of about 1500-1750 km and reach the peak in the vicinity of around 1450-1750 km.

Does financing constraints impact the Chinese companies' pollutants emissions? Evidence from a sample selection bias corrected model based on Chinese company-level panel data.

Most Chinese companies face financing constraints and thus lack sufficient funding for operations and investments that would better control their pollutant emissions. A sample selection bias corrected model is constructed to study the impact of financing constraints on the Chinese companies' pollutant emissions using company-level emissions data. The empirical results revealed that financing constraints increase the pollutant emissions of the Chinese companies, including the emissions of industrial wastewater, industrial solid waste, and sulfur dioxide. The heterogeneity analysis showed that the impacts of financing constraints on the pollutant emissions of companies operating in highly polluting industries and non-state-owned companies are more significant. And compared with internal financing, bank financing can better mitigate the impact of financing constraints on pollutant emissions through green loan projects. The results are stable after controlling for other important company factors and testing the robustness using the subdivided regression. Several political implications are drawn based on these findings that can help control the pollutant emissions of Chinese companies from the perspective of financing constraints.

Impact of green finance on economic development and environmental quality: a study based on provincial panel data from China.

The goal of green finance is to pursue the coordinated development of financial activities, environmental protection, and ecological balance. This study aims to examine the impact of green finance on economic development and environmental quality. Data concerning green finance, economic development, and environmental quality for 30 provinces and municipalities in China from 2010 to 2017 are used. First, the global principal component analysis is adopted to develop a green finance development index. Second, a model of the impact of green finance on economic development is constructed, which indicates that the development of green finance plays a role in promoting economic development. Next, emissions of industrial smoke (powder) dust, industrial solid waste, and carbon dioxide are used to represent the environmental variables, and a model of the impact of green finance on environmental quality is proposed. The model shows that green finance has a positive effect on environment improvement. However, the impact of green finance on environmental quality varies for different levels of economic development. Finally, based on the theory of the environmental Kuznets curve, a model of the impact of green finance on the relationship between economic development and environmental quality is developed. The model indicates that green finance can significantly improve this relationship, creating a win-win situation regarding economic development and the environment.