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The carbon emissions trading system (CETS) is a crucial market-based tool aimed at achieving the goals of “carbon peaking” and “carbon neutrality”, and plays a pivotal role in promoting the green development of the logistics industry. The green total factor productivity (GTFP) of the logistics industry is a key indicator used to measure the green development level of the logistics industry. The research on the CETS and the GTFP in the logistics industry(LGTFP) is currently lacking. Accurately assessing the impact of CETS on LGFP is crucial for improving the construction of the CETS and promoting the green transformation of the logistics industry. Utilizing a combined approach of system dynamics and econometrics, this study examines the effects of CETS on the LGFTP. In this study, the impact mechanism of CETS on the LGTFP is analyzed by constructing a causal relationship diagram using system dynamics theory. And then, we construct a multi-period differencein- difference (DID) model using panel data from 30 Chinese provinces spanning from 2010 to 2020 to verify the impact of CETS on LGTFP. The findings reveal that: (1) CETS significantly promotes LGTFP, and this conclusion is consistent even after conducting robustness tests. (2) Green technological innovation is identified as the primary influencing mechanism of CETS in enhancing LGTFP, while industrial upgrading does not play a positive mediating role, contrary to established studies. (3) Heterogeneity analysis reveals that CETS has a significant promotion effect on LGTFP in central and western regions, and resource-based provinces, but not yet in eastern regions and non-resource-based provinces. Based on the empirical analysis, we propose relevant policy recommendations to improve China’s CETS and promote the improvement of LGTFP. [ABSTRACT FROM AUTHOR]

Coal-based cities, compared with others, are generally deemed to face double pressure from both emission reduction and economic development, indicating the great practical significance to explore high-quality development methods for China's goal of carbon neutrality. As previous studies have verified, technological innovation exerts the driving effect on total factor productivity, yet the impact mechanism between green innovational technology and carbon emission performance (TFCEP) of coal-based cities remains rather a blank area. Given this, the super-SBM model was applied to measure the TFCEP of 47 typical coal-based cities in China from 2013 to 2016. Furthermore, the econometric model was employed to analyze the impact mechanism of TFCEP. Finally, the heterogeneity effects of green technology within different regulation levels on TFCEP through mechanism analysis were revealed. The results indicate that: (1) The TFCEP of coal-based cities in the northeast, west and east regions is on the rise, while the central region shows a gradual decline trend. The relationship between TFCEP and urban development stage shows a U-shaped curve. (2) The heterogeneous effects of green innovational technology on TFCEP were revealed. The innovation compensation effect mainly occurs in coal-based cities with relatively loose environmental regulation level. the driving effect of green technologies featured by breakthrough innovations on TFCEP is greater than that of green technologies featured by conceptual design. (3) The openness has proved to be an important channel for green innovational technologies affecting TFCEP. Therefore, to advocate high-quality green development in coal-based cities, the government can choose to increase financial support for local green technology breakthroughs and reduce dependence on foreign technologies. [ABSTRACT FROM AUTHOR]

Purpose: The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development. Design/methodology/approach: In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China's green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively. Findings: After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas. Originality/value: Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model. [ABSTRACT FROM AUTHOR]

The energy saving and emissions reduction of the construction industry are crucial for China to achieve the "carbon peaking and carbon neutrality" goals. In order to promote the green development of the life cycle of the construction industry and improve the efficiency of emissions reduction. This paper examines the spatial-temporal distribution of life cycle carbon emissions in China's construction industry (LCCECI) from 2004 to 2018. It uses the SBM-Malmquist total factor productivity (TFP) index to measure technological progress and establishes the spatial econometric model based on the STIRPAT model. The study investigates the driving factors of the LCCECI at the provincial and regional levels, aiming to provide suggestions for low-carbon development in the construction industry. The research results are as follows. © The growth in the SBM-Malmquist TFP index of the construction industry distinctly curbs the LCCECI. © Total population and urbanization level are not the primary driving factors for the LCCECI. The growth of per capita GDP significantly induces the LCCECI, while concurrently exhibiting a notable inhibitory effect on the LCCECI of neighboring regions. © The improvement of the SBM-Malmquist TFP index is conducive to the reduction of the LCCECI in the three major regions. The per capita GDP has the largest positive driving effect of the LCCECI in the eastern region, and the urbanization level the urbanization rate only significantly inhibits the growth of the LCCECI in the central region. [ABSTRACT FROM AUTHOR]

Based on the data of listed companies in China's iron and steel industry from 2007 to 2020, the article investigates the impact mechanism and the path of action of China's carbon emissions trading pilot on the green total factor productivity of iron and steel enterprises by constructing a multi-period difference-in-difference model difference-in-differences. The study finds that: 1) China's iron and steel enterprises significantly improve their green total factor productivity driven by the carbon trading pilot, and the findings pass the corresponding robustness tests. 2) the mechanism analysis indicates that the carbon trading pilot promotes the green total factor productivity of iron and steel enterprises by forcing the technological progress of enterprises. 3) The heterogeneity analysis shows that the positive effect is more significant for large iron and steel enterprises with high social responsibility rating and high local government competition intensity, but not for small enterprises with low social responsibility rating and low local government competition intensity. 4) the dynamic effect shows that there is a certain lag in the promotion effect of the carbon emission trading pilot on the green total factor productivity of iron and steel enterprises, but its long-term effect is more obvious. This paper puts forward corresponding suggestions for accelerating the construction of a national unified green and low-carbon market system and actively promoting the deepening of the "dual-carbon" goal. [ABSTRACT FROM AUTHOR]

The carbon emissions trading scheme (CETS) in China is an important market-based environmental policy mechanism for decreasing carbon emissions. This paper calculates the total factor carbon productivity (TFCP) based on data from 275 cities in China from 2007 to 2020 using the DEA method and investigates the impact of the CETS on regional TFCP using the differences-in-differences (DID) method, all against the backdrop of carbon peaking and carbon neutrality. The research findings reveal that CETS has consistently improved TFCP in pilot cities, and this conclusion has held up following a number of robustness tests. Temporal heterogeneity experiments demonstrate that as implementation time increases, the enhancing effect takes on an inverted "U-shaped" structure with a 7-year effective lifetime. Spatial heterogeneity studies reveal that as one moves away from the pilot cities, the policy effect on surrounding cities' TFCP is inhibited, followed by facilitation. CETS policies can influence regional TFCP through the effects of green innovation and industry upgrading, according to mediation mechanism testing. We present policy recommendations based on the research findings for meeting the "dual" carbon goals and strengthening the carbon trading mechanism. [ABSTRACT FROM AUTHOR]

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A significant industrial transformation in China's tourism sector is currently taking place in response to carbon peak and carbon neutrality targets. This paper applies the data envelopment analysis (DEA) model to calculate the efficiency of the tourism industry under carbon emission constraints and further investigates its influencing factors through the Tobit regression. The results are as follows: (1) The tourism efficiency under carbon emission constraints of China from 2000 to 2019 showed a trend of first rising and then declining, and there were obvious regional differences; (2) from 2000 to 2019, the total factor productivity of tourism in China increased significantly, while the contributions of technical progress, pure technical efficiency, and scale efficiency decreased sequentially; (3) the factors of industrial structure, transportation convenience, economic development level, degree of opening to the outside world, and the level of scientific and technological development have varying degrees of influence on tourism efficiency. Based on the analysis results, this paper puts forward several policy suggestions on tourism efficiency and low-carbon development. The findings of this paper have some bearing on developing nations' efforts to boost tourism efficiency and realize high-quality industry growth within the framework of sustainable development. [ABSTRACT FROM AUTHOR]

To measure and analyze the evolution characteristics and influencing factors of China's industrial green development level is of great significance in achieving carbon neutrality goal. Based on the panel data from 2000 to 2018 of 30 provinces in China, this research uses the super slack-based measuring model and the Malmquist-Luenberger index to calculates China's industrial green total factor productivity and to describe its evolution characteristics using the kernel density function and moreover uses the Spatial Durbin model and the partial differential method to explores its main influencing factors. This study finds that China's overall industrial green development level is not high but shows an upward trend year by year; carbon emissions, fiscal decentralization, and urbanization are not conducive to improving the national industrial green development level, whereas economic development, foreign direct investment, industrial structure, and technological progress are positive contributors. At the same time, the level of economic development and technological progress have significant direct and spatial spillover effect. Our findings also provide some policy implications for improving China's industrial green development. [ABSTRACT FROM AUTHOR]

Nearly 40 percent of worldwide energy and process-related CO2 emissions are produced by the construction sector. China's construction industry is the largest in the world, with Chinese construction enterprises completing a total output value of RMB 26.39 trillion in 2020; these buildings contribute to about 20 percent of China's overall carbon emissions and 20 percent of the global total emissions. There is an urgent need to prove whether construction enterprises are benefiting from the carbon trading policy. Compared to the traditional method, a double difference model can be used to highlight the consequences of different states of construction enterprises' responses to carbon trading regimes. In this study, we examine the following results based on cross-sectional data collected from 2006 to 2021, from listed construction enterprises: (1) Existing carbon emission policies have had a significant impact on the improvement of construction enterprises' total factor productivity. This improvement is more pronounced in large state-owned enterprises in particular. (2) Construction enterprises' greater involvement in carbon trading income is most strongly influenced by their green innovation level. (3) Construction enterprises located in eastern and central China benefit significantly from carbon trading, but construction enterprises based in the west do not. The research result indicates that future incentive initiatives should pay more attention to western regions and privately owned building enterprises. The leading role of large state-owned building enterprises should be reinforced. [ABSTRACT FROM AUTHOR]

Circular economy plays an important role in carbon emissions reduction. To understand how the development of circular economy in China improve the carbon productivity is of great significance to realize China's carbon peak and carbon neutrality goals. Due to the late introduction of the concept of carbon productivity, only a few studies have preliminarily analyzed the impact of the overall development of circular economy on carbon productivity at the macro level, but they ignored the different impact of different dimensions of the circular economy indicator system on carbon productivity at the micro level. In this context, this paper analyzes the impact of circular economy on carbon productivity by constructing an index evaluation system for the carbon reduction effect of circular economy through the two dimensions of resource efficiency and economic benefits and using the total factor carbon productivity measured by the DEA-Malmquist model and also analyzes the untapped potential of circular economy in different regions, which is expected to provide policy reference for how to achieve green and sustainable development in China under low-carbon constraints. Results show that first, the development of circular economy positively affects carbon productivity, and such promotion effect gradually strengthens with time. Meanwhile, the proposed indices demonstrate varying effects, with the resource efficiency indices outperforming the economic efficiency indices. Second, the varying degrees of circular economy development across regions lead to variations in the carbon reduction effect of circular economy on carbon productivity. Specifically, compared with the eastern and central regions, the western region shows the greater untapped potential of the circular economy. Identifying priorities for circular economy development, developing a circular economy in accordance with the local conditions, developing and utilizing advanced carbon emissions reduction technologies, and opening up further to the outside world have important theoretical value and practical significance for exploring the carbon emission reduction effect of circular economy. [ABSTRACT FROM AUTHOR]

Can China's carbon trading policy promote regional green total factor productivity? What are the specific influencing processes and mechanisms between the two? In this paper, we construct an indicator framework for China's green total factor productivity from the perspective of green development, which comprehensively considers various inputs and outputs. This paper uses a more scientific Super-EBM model considering the mixed distance to accurately measure the regional green total factor productivity in China. The static and dynamic effects and multiple mediating effects of carbon trading policy on green total factor productivity were studied by using DID model combined with stepwise regression method. The robustness of the results was tested by parallel trend test and placebo test. The mediating effects of total energy consumption, energy consumption structure, technological innovation and the moderating effects of financial development level and intellectual property protection degree are studied. The results show that carbon trading policy significantly improves China's regional green total factor productivity. The effect of carbon trading policy on green total factor productivity in pilot areas increased to decreased; Total energy consumption and energy consumption structure have a partial intermediary effect on the relationship between carbon emission trading policy and regional green total factor productivity in China, while technological innovation has a masking effect. Regional financial development level and intellectual property protection intensity play a moderating role in the relationship between carbon emission trading policy and regional total factor productivity. Based on the above conclusions, some suggestions are put forward for the improvement of China's carbon trading policy system. [ABSTRACT FROM AUTHOR]

Based on panel data from 30 provinces from 2001 to 2018 in China, this paper explores the effects and mechanisms of green urbanization on the forestry green total factor productivity (FGTFP) in the context of carbon neutral strategy using a two-way fixed effects model and instrumental variables. The results show that: Firstly, as a sector with ecological and economic benefits, ignoring carbon sink output tends to make FGTFP overestimated. Secondly, green urbanization has a significant positive contribution effect on FGTFP, and this finding still holds after a series of robustness tests including instrumental variables. Thirdly, green urbanization can indirectly promote FGTFP by stimulating the integration of forestry and tourism and strengthening environmental regulations. Fourthly, there is regional heterogeneity in the impact of green urbanization on FGTFP, i.e., the promotion effect of green urbanization on FGTFP is more significant in non-state forest areas compared with state-owned forest areas. Based on the above conclusions, the following countermeasures are proposed: firstly, attaching importance to green urbanization and strengthening environmental constraints; secondly, relying on green urbanization to drive the integration of forestry and tourism; thirdly, actively promoting the construction of green urbanization and green development of forestry in non-state forest areas, while vigorously developing the carbon sink economy to crack the transformation dilemma of backward state forest areas. [ABSTRACT FROM AUTHOR]

The carbon trading system affects all aspects of the economy and society profoundly. Agriculture, as a high-carbon-emitting industry, has been hard-hit. China's agricultural activities will emit about 820 million tons of carbon dioxide equivalents, accounting for 7% of the country's total carbon emissions. In order to develop a green and low-carbon economy and control greenhouse gas emissions, China officially launched the pilot carbon emissions trading policy in 2013. The effects and mechanism of this on agricultural carbon emissions are still unclear. Herein, this paper uses China's provincial panel data from 2000 to 2019 to measure agricultural green total factor productivity regarding the implementation of China's carbon emissions trading pilot policy in 2013 as a quasi-natural experiment, and uses PSM-DID robustness analysis to evaluate the effect of China's carbon emission rights trading pilot policy on agricultural green total factor productivity in pilot areas. The propensity score method is a type of statistical method that uses nonexperimental or observational data for intervention-effect analysis, which reduces the effects of bias and allows for more reasonable comparisons between treatment and control groups. "Difference in difference" is an approach to policy-effect evaluation based on a counterfactual framework to assess the change in the observed factors in both cases of policy occurrence and nonoccurrence. PSM-DID is a combination of PSM and DID using the PSM method to match each treatment group sample to a specific control group sample, which can solve the problem of self-selection bias in the DID method and assess the policy implementation effect more accurately. This study found that China's carbon emissions trading pilot policy has significantly improved China's agricultural green total factor productivity. Further impact mechanism tests show that China's carbon emissions trading pilot policy will improve agricultural green total factor productivity through environmental protection policies and technological innovation. Finally, this paper puts forward corresponding countermeasures and suggestions based on the research results. [ABSTRACT FROM AUTHOR]

On the one hand, economies, particularly developing ones, need to grow. On the other hand, climate change is the most pressing issue globally, and nations should take the necessary measures. Such a complex task requires new theoretical and empirical models to capture this complexity and provide new insights. Our study uses a newly developed theoretical framework that involves renewable energy consumption (REC) and total factor productivity (TFP) alongside traditional factors of CO2 emissions. It provides policymakers with border information compared to traditional models, such as the Environmental Kuznets Curve (EKC), being limited to income and population. Advanced panel time series methods are also employed, addressing panel data issues while producing not only pooled but also country-specific results. 20 Renewable Energy Country Attractiveness Index (RECAI) nations are considered in this study. The results show that REC, TFP, and exports reduce CO2 emissions with elasticities of 0.3, 0.4, and 0.3, respectively. Oppositely, income and imports increase emissions with elasticities of 0.8 and 0.3. Additionally, we show that RECAI countries are commonly affected by global and regional factors. Moreover, we find that shocks can create permanent changes in the levels of the factors but only temporary changes in their growth rates. The main policy implication of the findings is that authorities should implement measures boosting TFP and REC. These factors are driven mainly by technological progress, innovation, and efficiency gains. Thus, they can simultaneously reduce emissions while promoting long-run green economic growth, which addresses the complexity mentioned above to some extent. • The CO2 effects of renewable energy consumption (REC) and total factor productivity (TFP) are assessed. • 20 out of the top 40 Renewable Energy Country Attractiveness Index (RECAI) countries are considered. • A newly developed theoretical framework of CO2 and advanced panel methods are used. • It is found that TFP, REC, and exports reduce CO2, whereas income and imports increase. • Main policy insight is that TFP and REC should be boosted as they reduce CO2 while promoting growth. [ABSTRACT FROM AUTHOR]

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms' optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings. Fig. 1. Introduction of the research questions Fig. 2. Framework of this paper. [Display omitted] • Carbon emission trading and green certificate trading policies were introduced into a dynamic CGE model. • The comprehensive performance of different scenarios were measured using total factor productivity index. • The policy effects of different scenarios were explored from 2020 to 2060. • The even more effective reform measures were adopt, within a single policy. • A sensible mix were proposed, within different policies. [ABSTRACT FROM AUTHOR]

Extant studies focus on the impact of environmental regulation on regional economic growth or environmental pollution, and a lot of research outcomes have been made. However, from the perspective of corporate green sustainable development, the question of whether carbon emission trading represents a "green blessing" remains unclear. To address this issue, we employ a staggered difference-in-differences model to investigate the effects and mechanisms of the carbon emissions trading pilot policy (CETPP) on the green total factor productivity (GTFP) of listed manufacturing companies in China. Our results demonstrate that: a) CETPP can effectively promote corporate GTFP, and the robustness of this result is verified through a series of checks; b) the mediating role of environmental, social, and governance (ESG) performance is critical in the relationship between CETPP and corporate GTFP, with environmental and governance performance serving as two key transmission channels; and c) CEO green experience and public environmental concern both play the moderating roles on the relationship between CETPP and GTFP; d) CETPP has a stronger positive impact on GTFP of private enterprises and enterprises in the maturity life cycle; and e) CETPP has a spatial spillover effect on GTFP, and the effect will decay as spatial distance increases. Our study offers both theoretical and practical implications for enterprises to achieve their green economic development objectives, so as to promote China's high-quality development. • We find that carbon emission trading pilot policy (CETPP) has a positive impact on the corporate green total factor productivity (GTFP). • We estimate the mediating effect of environmental, social, and governance (ESG) performance on the relationship between CETPP and corporate GTFP. • We explore the positive moderating effect of CEO green experience and public environmental concern on the relationship between CETPP and corporate GTFP. • We show that the impact of CETPP on GFTP of private enterprises and enterprises in the maturity life cycle. • We further find that there is spatial spillover effect of CETPP on GTFP, and the effect will decay with the increasing spatial distance. [ABSTRACT FROM AUTHOR]

In the context of green economy development, efforts and measurements aimed to balance the relationship between the economy and environment have been vigorously promoted. Among these regulations, the policy of China's carbon emissions trading (CET) pilot, one of the market-based environmental regulations, is favorable for China to take a path that can trigger both improvement of environmental quality and optimization of economic structure. In this paper, we adopt the slacks-based measure and data envelopment analysis (SBM-DEA) model considering the undesired output and the Luenberger function to measure and decompose the green total factor productivity (GTFP) and verify the policy effect of CET on environment, economy and productivity through difference-in-differences (DID) approach. The results showed are as follows: (1) the policy of CET has promoted the reduction of carbon emission, whereas its impact on the industrial output is not significant. (2) We show that in the short turn, the CET policy does not immediately contribute to improvement of GTFP, whereas its effect on technological progress decomposed of GTFP is positive. The results indicate that CET regulation has produced environmental dividend and improved the technological progress, but there is no Porter effect. Overall, our results provide actual evidence for deepening the nationwide carbon emission trading system. [ABSTRACT FROM AUTHOR]

Digital development is critical for achieving coordinated regional economic growth, energy conservation, and emissions reduction, which makes it a viable method for achieving carbon neutrality and peaks. This study investigates the impact of the digital economy on urban total factor productivity and carbon emissions, as well as its mechanism, from 2011 to 2019 by developing a digital economy evaluation index system. We find that the growth of the digital economy can increase urban total factor productivity while lowering carbon emissions and also has a significant spatial spillover effect on regional economic growth, energy conservation, and emissions reduction. The main influencing mechanism is that the digital economy accelerates marketization by encouraging industrial structure upgrades and technological progress, which results in higher total factor productivity and lower energy consumption. In terms of the spatial distribution, the digital economy promotes total factor productivity more in the central and western regions and large cities and promotes carbon emission reduction less in the eastern regions and smaller cities. The findings extend the benefits of the digital economy beyond economic and social welfare benefits and serve as a model for achieving a win–win situation in terms of both economic growth and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

Ensuring the coordinated development of carbon emissions and green economy has important implications for China's sustainable development. For examining the coordinated development between carbon emissions and green economy in China and its influencing factors, this study assessed the coupling coordination degree (CCD) between carbon emission intensity (CEI) and green total factor productivity (GTFP) using the coupling coordination degree model (CCDM), revealed the spatiotemporal evolution law of CCD using a spatial correlation model and empirically examined their influencing factors using the spatial Durbin model (SDM) to test influencing factors. The following findings were made: (1) The green economy in China synchronously developed with carbon emission reductions from 2000 to 2020. (2) CCD has global spatial concentration effects, and the objects are divided into three categories: cold spots, hot spots, and random distributions. (3) Government scale expansion, transportation volume increase, industrial agglomeration, and urbanization are all not conducive to CCD, but population density and industrial structure upgrading have opposite effects. To promote the coordinated development of carbon emissions and green economy, we can improve the efficiency of energy utilization and reduce carbon emissions, by using clean energy, adopting clean production technology, increasing non-productive public investment in environmental protection, industrial agglomeration in reasonable space, and improving the moderate population agglomeration. Our findings offer valuable insight for understanding the relationship between carbon emission reduction and green economic development. They will allow authorities to take specific actions to ensure the coordinated development of CEI and GTFP. [ABSTRACT FROM AUTHOR]

Achieving the win-win goal of sustainable economic growth and carbon neutrality is a sustainable development challenge facing all countries worldwide. This study examines the impact of carbon emission trading pilot policy on green development performance, aiming to provide experience for developing countries to reduce carbon emissions and achieve carbon neutrality goals. Based on the panel data of 30 provinces from 2010 to 2017 in China, green development performance (GD) is deconstructed into green total factor productivity (GTFP) and carbon emissions intensity (CEI), DEA-DDF-Malmquist index model and PSM-DID (Propensity Score Matching-Differences-in-Differences) model are adopted to explore the policy assessment and impact of the carbon emission trading pilot, which verifies the influence of the pilot policy on GTFP and CEI between experimental group and the control group. The empirical results showed that the carbon emission trading pilot policy could not effectively improve the green total factor productivity and carbon emissions reduction in the pilot areas, R&D intensity improvement, technology introduction improvement, and industrial structure optimization have positive and significant promoting effects on GTFP, the optimization of energy structure and industrial structure contributes to the carbon emissions reduction. This study provides information and decision-making references to address the challenge of climate change, energy conservation, and emission reduction, as well as a scientific basis for expanding pilot policies for China. • The carbon emission trading pilot has limited impact on GD in China. • R&D, FI and IS have significant positive promoting effects on GTFP. • ES and IS have significant inhibitory effect on GICE. • Providing reference for developing countries in energy conservation & emission reduction. [ABSTRACT FROM AUTHOR]

The implementation of the carbon trading system has a great impact on all aspects of the economy and society. Agriculture, which accounts for 34% of global carbon emissions, has also been hit hard as a high carbon emitting industry (Crippa M, 2021). This study uses agricultural green total factor productivity as an important indicator of agricultural green sustainable development, and analyzes the impact of China's carbon trading system on agricultural green total factor productivity, which can provide a reference for other countries that want to improve agricultural sustainable development and implement carbon trading. In this paper, the producer theory is used to build the basic model, and the differences-in-differences (DID) method is used to analyze the provincial data samples in China from 2000 to 2020. It is found that: the implementation of carbon trading pilot policy has a significant promotion effect on agricultural green total factor productivity; and after the implementation of carbon trading policy, with the advancement of time, under the constraint of reducing carbon quota, the promotion effect of agricultural green total factor productivity becomes stronger and stronger. Even in the regions without carbon trading pilot program, the policy spillover effect will also be obvious and promote the development of green total factor productivity of agriculture in this area. [ABSTRACT FROM AUTHOR]

Based on the tightening regulation of carbon emissions, China has launched the pilot carbon emission trading scheme (CETS) since 2013. There is growing empirical evidence of the actual effect of CETS to promote enterprises' productivity which is characterized by total factor productivity (TFP). However, most studies ignored the further analysis of influence mechanisms. This paper aims to explore the impact of CETS on the TFP of enterprises and discuss the mediating role of government participation and carbon trading market efficiency. Using data from A-share listed enterprises from CETS-covered enterprises, this paper employed a combination of the propensity score matching (PSM) and difference-in-differences (DID) strategies and found that the CETS has a statistically significant positive impact on the TFP of enterprises, and the positive effect has been maintained for six years since its inception. The moderation analysis indicated that: (1) two dimensions of government participation in terms of the market incentive and government supervision significantly moderate the positive impact of CETS on TFP of enterprises; (2) two dimensions of carbon trading market efficiency in terms of the market scale and liquidity significantly moderates the positive impact of CETS on TFP of enterprises. In light of Chinese pilots CETS policy, the study highlights the important moderating roles of government participation and high carbon trading market efficiency on enterprise's TFP. [Display omitted] • Chinese pilots CETS significantly improved the TFP of enterprises by 9.48%. • The government participation moderates the positive impact of CETS on enterprises' TFP. • The higher carbon trading market efficiency is, the greater the moderating effect of CETS on TFP is. [ABSTRACT FROM AUTHOR]