Utilizing microevaluation data on the extent to which firms advance the achievement of the UN’s Sustainable Development Goals (SDGs) provided by Robeco, this paper examines the influence of corporate sustainability on stock price performance and its underlying economic mechanisms. The empirical results suggest that firms’ sustainability has a significant negative effect on excess returns, particularly the contribution of firms to the social dimension of sustainability. Firms’ SDG performance can alleviate financing constraints and reduce financial risk, but it does not significantly enhance financial performance, leading to market capital outflows from high SDG-performing firms, especially from individual investors. Furthermore, our results suggest that high SDG-performing firms are undervalued and do not increase the information content in their stock prices, which may be the main reason for the negative effect of SDG performance. We also conduct a series of heterogeneity tests, which show that firms from regions with high environmental regulatory intensity and less economic development, as well as heavily polluting firms and firms with poorer information environments, experience greater negative effects. These findings have implications for investors to properly understand corporate sustainability and for regulators to promote the development of a low-carbon economy.

Climate change presents a global threat, prompting nations to adopt low-carbon development pathways to mitigate its potential impacts. However, current research lacks a comprehensive framework capable of integrating multiple variables and providing dynamic optimization capabilities. This article focuses on designing pathways for developing a low-carbon economy to tackle climate challenges. Specifically, we construct a low-carbon economy model that incorporates economic, environmental, social, energy, and policy factors to analyze the drivers of economic growth and carbon emissions. We utilize economic model predictive control and tracking model predictive control to optimize development pathways aligned with various low-carbon targets, creating and validating a comprehensive framework for low-carbon policy design using historical data from China. This study highlights significant advantages in analyzing low-carbon pathways through advanced techniques like hierarchical regression and model predictive control, providing a robust framework that enhances our understanding of causal relationships within the LCE system, captures system feedback, dynamically optimizes pathways, and accommodates diverse policies within a comprehensive low-carbon economy system.

The pilot carbon emission trading schemes (ETSs) of China were created to combat climate change in a cost-effective and economically efficient manner, and their potential impact on regulated firms has drawn increasing attention. This study is conducted to provide empirical evidence on the effect of China’s pilot ETSs on firm-level financial performance during the period from 2008 to 2017. The empirical results show that the ETS pilots have a positive impact on firms’ profitability and value, and a negative impact on operational costs. We also find that the ETS pilots improve total factor productivity (TFP) but that changes in technology have an indirect suppressing effect on the relation between the ETS and short-term financial performance, providing support for the weak version of the Porter Hypothesis. Further, we show that the carbon emission price has a negative impact on firms’accounting-based performance but increases firms’ market value. Finally, we find evidence that, in contrast to state-owned enterprises (SOEs), non-SOEs do not experience significant improvements in their financial performance, led by the ETS pilots. Our findings have policy implications for firms’sustainable development and the transition to a low-carbon economy.