The carbon emission trading system profoundly impacts enterprises’ sustainable development as an important market incentive environmental regulation tool. Through data collected from Chinese A-share listed enterprises in Shanghai and Shenzhen from 2011 to 2019 and Bloomberg ESG score data, this paper empirically analyses the impact of carbon emission trading policy on enterprise ESG performance and its channel mechanism using the difference-in-difference (DID) method. Results of this study indicate that carbon emission trading policy improves enterprise ESG performance significantly, and robustness tests confirm these findings. Carbon emission trading policy can encourage enterprises to enhance their R&D investments and promote internal controls, ultimately enhancing their ESG performance. Additionally, carbon emission trading policy positively impacts ESG performance in low-carbon enterprises, enterprises where the CEO is separated from the company, enterprises with a high degree of digital transformation, and enterprises receiving high government subsidies. This paper extends our research into the economic implications of carbon emission trading policy, enriching the literature on market-based environmental regulation policies’ impact on enterprise ESG performance. With respect to governments’ use of carbon emission trading to regulate enterprises environmentally, this paper provides theoretical guidance. It has significant practical implications for improving enterprise ESG performance and sustainability.

This paper proposes a centralized data envelopment analysis (DEA) model for industrial optimization based on several different production technologies among several regions. We developed this model based on improved Kuosmanen environmental DEA technology, which avoids positive shadow price on undesirable outputs. We also designed a dual model for our centralized DEA model, and used it to analyze shadow prices on CO₂ emissions. We further employed the proposed model to determine the optimal path for controlling CO₂ emissions at the sector level for each province in China. At sectoral level, manufacturing showed the highest potential emissions reduction, and transportation was the largest accepter of emission quotas. At regional level, western and northeastern areas faced the largest adjustments in allowable emissions, while central and eastern areas required the least amount of adjustment. Because our model represents increase or decrease in emissions bidirectionally in terms of shadow price analysis, this setting makes the shadow price on CO₂ emissions lower than strong regulation (decreasing CO₂ emissions along with increasing value added) used by directional distance function (DDF).

This paper proposes a new non-radial biennial Luenberger energy and environmental performance index (EEPI) to measure the energy and environmental performance (EEP) change in various Chinese cities. The sources of EEP change, in terms of technical efficiency change and technological change, are examined by Luenberger EEPI. The contributions from specific undesirable outputs and energy inputs to the EEP change are identified by means of the non-radial efficiency measure. The proposed approach is applied to evaluate the EEP of the industrial sector in 283 cities in China over 2010–2014. Factors influencing the emission abatement potential are investigated by employing geographically weighted regression (GWR) model. We find that (1) changes in EEP can be attributed to technological progress but that technological progress slows down across the study period; (2) the soot emission performance experiences a downtrend among four specific sub-performances (i.e., energy, wastewater, SO₂ and soot performances) in line with the truth that severe haze happened frequently in China; (3) the best performers begin to move from the coastal to inland cities with the less resource consumption and higher ecological quality; (4) cities with the strongest positive effect in regards to pollution intensity on emission abatement potential are located in the areas around the Bohai Gulf, where air pollution is particularly severe.

In theory, the industrial agglomeration is a double-edged sword as there are both positive and negative externalities. China’s cities, with great disparities on degrees of the industrial agglomeration, often face different energy and carbon dioxide emission problems, which raise the question whether the industrial agglomeration promotes or inhibits energy efficiency and carbon dioxide emission. This paper explored the effects of the industrial agglomeration on carbon efficiency in China. Spatial econometric methods were implemented using panel data (2007–2016) of 285 cities above the prefecture level. The results revealed that industrial agglomerations have significant impacts on the urban carbon efficiency with significant spatial spillover effects. The agglomerations of the manufacturing and high-end productive service industries take positive effects on carbon efficiency while the low-end productive and living service industries take negative effects. As a comparison, we found that the agglomeration effects at the level of the megalopolis are greater than those at the national level, especially for the living services industry, in which the higher levels of agglomeration make the effects on carbon efficiency change from negative to positive. The divisions of labor for the central and common cities in the megalopolises are integrated into the industrial agglomeration. Furthermore, the fractional-order grey forecasting model is used in this paper. By the virtue of its advantage in dealing with small sample data which lack statistical rules, this paper makes an out-of-sample prediction of carbon efficiency and industrial agglomeration degree of Chinese cities. By adding the predicted results to the spatial correlation test, new evidence on the spatial correlation of carbon efficiency and spatial division of labor between cities is obtained. Based on the empirical results of the present study, we have proposed some policy recommendations.

The central problem of this study is to represent any holomorphic and square integrable function on the Kepler manifold in the series form based on Fourier analysis. Because these function spaces are reproducing kernel Hilbert spaces (RKHS), three different domains on the Kepler manifold are considered and the weak pre-orthogonal adaptive Fourier decomposition (POAFD) is proposed on the domains. First, the weak maximal selection principle is shown to select the coefficient of the series. Furthermore, we prove the convergence theorem to show the accuracy of our method. This study is the extension of work by Wu et al. on POAFD in Bergman space.

The assessment of the relationship between the innovative city pilot policy (ICPP) and urban resilience is crucial for enhancing cities’ ability to foresee, endure, and recover from various disruptive events. Despite the widespread implementation of the ICPP in China, it remains uncertain if this strategy will contribute to the development of urban resilience. Starting with data collected from 245 prefecture-level cities in China from 2004 to 2020, this paper initially evaluates the causal effect of the policy intervention using the difference-in-differences (DID) model and the propensity score matching-difference-in-differences (PSM-DID) method. A multi-dimensional urban resilience measurement index and a mediating effect model were constructed. The empirical results show that (1) the ICPP has a significant effect on urban resilience, which remains in force after a series of robustness tests, such as a placebo test and difference-in-differences machine learning (DML) approach; (2) regional R&D investment, technological talent attraction, green innovation capability enhancement, and information infrastructure development are identified as the mediating variable for the ICPP’s impact on urban resilience dimensions; and (3) heterogeneity study results show that the ICPP has a significantly greater impact on medium-sized cities, attributed to their capacity to enhance the resilience of cities with more growing space. Furthermore, cities with lower economic agglomeration saw a greater increase in urban resilience due to the ICPP. Accordingly, it is recommended to prioritize the allocation of innovative resources to non-coastal regions, cities with low economic agglomeration, and medium-sized cities. This study provides crucial recommendations for the enlargement of the ICPP’s scale and coordinated progress of China’s urban resilience.