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The all‐sky Aerosol Direct Radiative Effect (ADRE) varies considerably among global climate models (GCMs), which results from differences in aerosol and atmospheric states and ADRE sensitivity to aerosol‐related radiative processes. This study uses a regression method to analyze the inter‐model spread of ADRE among the GCMs of the Sixth Coupled Model Intercomparison Projects (CMIP6). The key state variables examined include scattering and absorbing aerosol optical depth, surface albedo, and shortwave cloud radiative effect. We find that differences in state variables and radiative sensitivity explain 67% and 17%, respectively, of the global ADRE anomaly. The ADRE anomaly in different models is dominated by different factors, which sometimes leads to compensating effects. For the global mean ADRE anomaly, aerosol optical depth differences dominate in CNRM‐ESM2‐1 and GFDL‐ESM4 models, while ADRE sensitivity variations to aerosol‐only scattering effect dominate in HadGEM3‐GC31‐LL, MPI‐ESM‐1‐2‐HAM, and MRI‐ESM2‐0 models. Plain Language Summary Aerosols scatter and absorb solar radiation, impacting the Earth's climate. Global climate models differ in their quantification of this effect. The differences in quantification arise from different state variables, including the aerosol properties and atmospheric conditions. Additionally, the radiative sensitivity of aerosol effect to aerosol‐related physical processes varies with models. In this study, we identify the primary causes of the differences in aerosol radiative effect among climate models and quantify their respective impacts by using a regression method. We find that besides the aerosol optical depth, whose influence on aerosol radiative effect is well recognized, the radiative sensitivity of aerosol and surface interactions significantly contributes to the aerosol radiative effect differences in the latest climate models. Key Points A regression model is used to dissect the inter‐model spread of the all‐sky Aerosol Direct Radiative Effect (ADRE) in Sixth Coupled Model Intercomparison Projects Models The model explains 86% of ADRE inter‐model spread, with variances in state‐variable and radiative sensitivity contributing 67% and 17% each Differences in aerosol optical depth and ADRE sensitivity to aerosol‐surface interactions drive the spatial variance in global ADRE spread

Carbon risk has aroused widespread concern in society. With the implementation of carbon policy and the development of carbon market, the research on the impact of carbon risk on corporate financial behavior has become an important academic frontier issue. We examine the impact of carbon risk on firms' real earnings management before and after the Paris climate change agreement, signed by China in 2016. A difference-in-differences model is deployed by using a sample of Chinese A-share listed companies. We find that high-carbon-intensive firms engage in significant upward real earnings management compared to low-carbon-intensive firms to offset the negative impact of carbon risk by conveying the message of good corporate development to investors after signing the Paris Agreement. The above research findings still hold after the robustness tests. Further heterogeneity analyses show that the impact of carbon risk on firms' real earnings management is greater in the sample of non-state-owned firms. The above impact is more significant in firms with weaker corporate governance, implying that strong corporate governance constrains managers from engaging in real earnings management. Therefore, policymakers and regulators should pay attention to the 'strategic response' to earnings management of carbon-intensive firms, taking into account the nature of property rights, corporate governance to reasonably improve the policy design and regulatory direction.

This paper establishes DID and PSM-DID models to examine the effect of extreme weather on enterprise productivity, using empirical evidence from natural experiments of torrential rainstorm in Zhengzhou of China. Based on analysis of empirical results, we find that extreme weather has a negative impact on enterprise productivity, psychological capital plays a regulatory role in this influence, and decrements of enterprise productivity with high psychological capital is smaller than enterprises with low psychological capital. The results of this study provide empirical data support to understand the negative effect of extreme weather upon enterprise productivity and the positive role of employee psychological capital.

As an important driving force of China’s economic growth, foreign direct investment (FDI) may be affected by China’s low-carbon pilot policy. Therefore, this paper regards the low-carbon pilot policy as a quasi-natural experiment, and uses the difference-in-difference (DID) model and the panel data of 189 cities in China from 2011 to 2018 to explore the actual impact and intermediary mechanism of low-carbon pilot policy on FDI. The study found that low-carbon pilot policy has a significant promotion effect on FDI, and industrial optimization and upgrading is an important way. At the same time, we construct the difference-in-difference-in-difference (DDD) model, and discuss the heterogeneity of policy effect caused by resource endowments and the individual characteristics of government officials in the process of policy implementation. The results indicate that resource-rich cities can enhance the promotion effect of low-carbon pilot policy on FDI. Similarly, when the mayor of the pilot city is a female, or obtains a master’s degree or a doctorate degree, or majored in non-economics, respectively, the policy effect will be more obvious. In addition, in order to verify the reliability of the research conclusions, this paper also uses a placebo test and data truncation to conduct a series of robustness tests.

Corporate overseas investment is a pivotal element of the Belt and Road Initiative (BRI). As an all-round opening-up strategy, the BRI has brought new ideas to international cooperation, and Chinese enterprises should seize this opportunity to promote global sustainable development. Adopting the data of Chinese listed enterprises from 2011-2020, this paper investigates the impact of the BRI on corporate overseas investment (COI) and its mechanisms via exploiting the difference-in-differences model (DID). Results show that the BRI has significantly facilitated the COI along the routes. We observe that the findings still hold after a series of robustness tests. Mechanism analysis verifies that tax incentives and credit environment improvement are the main channels by which BRI enhances COI. Heterogeneity results reveal that this initiative is more prominent for small and medium-sized enterprises and enterprises in dominant industries. The extensive analysis suggests that from a sustainable development perspective, the BRI facilitates more overseas investment of enterprises in polluting or high energy-consuming industries; the COI is more affected by BRI in regions with more stringent environmental regulations. This study provides empirical evidence for BRI construction and regional development.

Based on the quasi-natural experiment of the establishment of the Yangtze River economic belt, this paper uses a difference-in-difference-in-differences model (DDD) to test the impact of regional integration on transboundary pollution. The results show that regional integration can significantly reduce transboundary water pollution. Regional integration reduces chemical oxygen demand (COD) by 0.357, ammonia nitrogen content (NH 3 -N) by 0.155, and dissolved oxygen content (DO) by 0.088 in the downstream of the provincial boundary. And regional integration has a long-term inhibitory effect on transboundary pollution. The heterogeneity results show that the regional integration has a stronger inhibition effect on the transboundary pollution of the middle and lower reaches of the Yangtze River economic belt and the tributaries. At the government level, regional integration can reduce transboundary pollution by strengthening the government’s environmental regulation and collaborative governance. At the industry level, it can inhibit transboundary pollution by promoting industrial structure optimization and green technology innovation. At the market level, regional integration can promote market competition to reduce transboundary pollution and expand market scale to intensify transboundary pollution. At the society level, regional integration can intensify transboundary pollution by promoting population agglomeration and effectively alleviate transboundary pollution by enhancing public environmental supervision.

PurposeThis study aims to empirically examine how blockchain, one of the emerging Industry 4.0 technologies, can combat climate change by improving their green innovation performance, particularly under conditions of policy uncertainty.Design/methodology/approachThis study utilizes the difference-in-difference-in-difference (DDD) method to explore the effect of blockchain on enterprises' green innovation performance. The analysis is based on data from Chinese-listed enterprises spanning the period from 2013 to 2021.FindingsFirst, the adoption of blockchain in enterprises registered in areas designated as low-carbon pilot cities can significantly improve their green innovation performance. Second, the enhancement of green innovation efficiency emerges as the primary driving force behind the adoption of blockchain, thereby leading to improved green innovation performance. Lastly, it is observed that blockchain adoption has a greater positive impact on improving green efficiency in private enterprises compared to state-owned enterprises in China.Practical implicationsFor managers, the findings can provide valuable insights to help them better prepare for the challenges and opportunities presented by the era of Industry 4.0. For policymakers, this study offers valuable insights into the interaction between new technologies in Industry 4.0 and the performance of green innovation, thereby aiding in the formulation of effective policies.Originality/valueThis study contributes to bridging the existing gap between the adoption of new technologies, such as blockchain, and their potential impact on climate change. Moreover, this research enriches practitioners' understanding of how new technologies in the era of Industry 4.0 can be applied to address significant challenges like climate change.

In the late stages of its industrialization, China’s economy still largely relies on energy. With increasing pressures to protect the environment and reduce carbon emissions, in 2013, the Chinese government officially issued four policies in succession to control total energy consumption. In this paper, we use the single difference model to estimate the average and dynamic economic impacts of such policies. We also introduce the energy dependence degree and divide all industrial sectors into two categories to estimate heterogeneous and dynamic policy effects based on the difference-in-differences (DID) model. Our empirical study shows that the implementation of energy consumption control policies results in a decrease in economic growth rates. Meanwhile, the negative dynamic economic effects of such policies decrease levels of volatility. Furthermore, such policies have heterogeneous economic effects on levels of energy dependence across sectors and have more significantly negative economic impacts on heavily energy-dependent industries but with hysteresis. Heterogeneous and dynamic economic effects on heavily energy-dependent industries are decreasing. We conclude with recommendations on ways to mitigate the negative effects observed.

Transport infrastructure connectivity (TIC) has strong endogeneity issues, making it difficult to directly assess its impact on local conflict resolution. This study presents new evidence of the effects of TIC on conflict resolution by conducting a natural experiment and applying machine learning methods to overcome the endogeneity issue. Based on global conflict data from 2010 to 2017, the empirical results show the following: (1) TIC can significantly improve countries’ global ranking for conflict resolution; in particular, the marginal benefit of developed countries is greater than that of developing countries. (2) The mechanism behind this effect is the promotion of trade facilitation, a more balanced employment ratio across genders, and improved income levels through TIC, which further enhances the conflict governance capacity of countries. In light of the findings, policy-makers should consider the opportunity to combine TIC with greater security for the realization of economic and social benefits, taking into account the significant opportunities for developing countries and the importance of balance across genders and income levels.

The carbon emission trading pilot policy is an important initiative to achieve synergistic economic-environmental development. Based on the data of 268 cities in China from 2006 to 2020, this paper analyzes the impact of carbon emission trading pilot policy on urban innovation capacity by using a time-varying difference-in-difference model. The study shows that, first, the implementation of the CETP improves the innovation capacity of cities, and the robustness test confirms the above findings. Second, the effect of the policy on enhancing urban innovation capacity is heterogeneous between the type of innovation and city type: the promotion of innovation capacity is stronger for utility model patents and non-capital cities. Third, there is a positive spillover effect of the implementation of the CETP on the promotion effect of the urban innovation capacity, which can lead to the improvement of the innovation capacity of neighboring cities. This paper has some reference value for building a unified carbon emission trading market and promoting low-carbon economic development within China.