•This paper analyses the factors affecting CO2 emissions of OECD.•LMDI decomposition and decoupling analysis methods are combined.•We find that the impact of population distribution on CO2 emissions ...is negligible.•Energy intensity and per capita GDP are the main impact factors of CO2 emissions.•Technical factors have a greater impact on decoupling elasticity.
Under the framework of the Kaya identity, this paper uses the Logarithmic Mean Divisia Index (LMDI1Abbreviation: LMDI, the Logarithmic Mean Divisia Index.1) decomposition method to explore the impacts of CO2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita Gross Domestic Product (GDP2Abbreviation: GDP, Gross Domestic Product.2), population distribution, and population size on CO2 emissions in the Organisation for Economic Co-operation and Development (OECD3Abbreviation: OECD, the Organisation for Economic Co-operation and Development.3) from 2001 to 2015. Additionally, the Tapio decoupling analysis is used to explore the decoupling relationships between the above influencing factors and CO2 emissions. Moreover, the LMDI decomposition formula is embedded into the decoupling analysis to analyze the influences of technical and non-technical factors on above decoupling elasticity. The results indicate that energy intensity and per capita GDP are the main factors affecting CO2 emissions. The former is the main reason for the decrease in CO2 emissions, and the latter is the main reason for the increase in CO2 emissions. The impact of population distribution on CO2 emissions is negligible. The decoupling states between the overall CO2 emission intensity of fossil energy, energy consumption structure, energy intensity, per capita GDP, and population size and CO2 emissions during 2001–2015 are recessive decoupling, recessive decoupling, weak negative decoupling, strong decoupling, and strong decoupling, respectively. Moreover, the influence of technical factors is greater than that of non-technical factors, and their influence directions are always opposite. In addition to our primary contributions, there are three marginal contributions in this paper. First, the population distribution is included in LMDI factorization. Second, LMDI decomposition is combined with Tapio decoupling analysis to explore the decoupling relationships between CO2 emissions and the above factors. Finally, the findings related to the impacts of technical and non-technical factors are novel.
While local protectionism and market segmentation owing to fiscal decentralization are not conducive to broad economic development, they may be rational choices on a local scale. Based on a spatial ...Durbin model, we analyzed the relationship between environmental regulations and market segmentation in China using interprovincial panel data for 2004–2018. The results indicated that the “beggar-thy-neighbor” phenomenon persists in China; environmental regulations have a U-shaped impact on market segmentation, i.e., in most regions, environmental regulation can break down market segmentation. Regions with greater decentralization are better able to promote local market integration through environmental regulation, suggesting that local governments are better able to compensate for market failures when vested with greater power. Hence, we propose that the central government should improve performance evaluation indicators for local governments and grant them greater autonomy; additionally, local governments should increase the intensity of environmental regulations as appropriate, thereby promoting both environmental protection and the unification of domestic markets.
The International Clean Energy Market (ICEM) has emerged as one of the fastest-growing sectors in the energy industry. The increasing financialization and integration of the ICEM has meant that ...internal systemic risks have begun to surface, which can potentially seriously threaten the stable development of the ICEM. To explore systemic risk management strategies that can be enacted in the ICEM, this paper utilizes the Weighted Turbulence Model (WDTI) to measure the evolutionary characteristics of the systemic risk levels within the ICEM from 2012 to 2022. Subsequently, it explores spillover structure in the ICEM through volatility spillover effect (VSE). The results obtained indicate that the occurrence of systemic risk days in the ICEM is closely related to impact events, and its systemic risks are characterized by their rapid eruption, which can erupt more than twice. The volatility in any specific sub-sector within the ICEM can propagate throughout the entire system. The spillover pattern of volatility in the ICEM shows similarities across various economic cycles. The fuel cell market is specifically identified as the Systemically Important Market (SIM) within the ICEM. This paper establishes a theoretical foundation for managing systemic risk and ensuring the stability of ICEM.
•The overall systemic risk of the international clean energy market is measured.•The characteristics of each sub-sectoral clean energy market are revealed.•Clean energy is more vulnerable to the impact of systemic risk during the market downturn.•The energy efficiency markets are prone to spread risks to other types of markets.•Interdependence is more likely to occur in the same type of market.
•Lessons from three main ongoing international financing mechanisms have been drawn.•Thirty-one potential schemes have been proposed for sharing the burden of the GCF financing.•Weighting HR, UN, and ...GEF with the PSC method could yield the “most effective” scheme.•Developed parties are main provider of the GCF even if the donors include the emerging economics.•The decision of the United States to withdraw from climate finance will significantly increase the burden for other donors.
Asa key issue in recent international climate summits, the Green Climate Fund (GCF) is confronted with the problem of insufficient financing. This paper intends to explore several schemes for raising the public finance of the GCF among developed countries. Lessons from three main ongoing international financing mechanisms have been drawn, including the United Nations (UN) membership dues, Official Development Assistance (ODA), and the Global Environment Facility (GEF). The indexes that reflect historical emission responsibility (HR) and ability to pay (AP) are also used to share the burden. Results reveal that the ongoing international financing mechanisms vary in their burden sharing results and the shares of existing donors are driven by highly complex reasons. Weighting the HR, UN, and GEF approaches with the Preference Score Compromises (PSC) method could yield a compromise scheme in which the regional contributions are highly similar to those under the GCF initial resource mobilization from 2015 to 2018. GCF financing heavily depends on contributions from the developed countries even if the donor parties are extended to emerging economics. This paper also finds that the decision of the United States to withdraw from climate finance will significantly increase the burden for other donors, particularly for the European Union the contribution share of which is predicted to increase to nearly 14 percentage points. The schemes proposed in this study can provide a useful reference for GCF financing.
The integration of the circular economy (CE), a model promoting the cyclical use of resources, and Industry 4.0, an intelligent-based approach to manufacturing, is expected to achieve sustainability. ...Finding the most suitable path for technological progress and structural change to promote economic growth is the key to adopting Industry 4.0 technologies and successfully transforming to a CE, and thus, key to China achieving sustainable development quickly. This study identifies the joint effects of energy- and environment-biased technological progress and multi-dimensional industrial structural change on economic growth, and empirically verifies the specific effects within China. Our results are as follows. First, pollution abatement technological progress, backstop technological progress and autogenous structural ecologicalization are the main drivers of sustainable economic growth. Second, innovation policies have a positive impact on national economic growth by promoting pollution abatement technological progress. Finally, in sub-regions’ regression, backstop and environment technology, and structural ecologicalization promote eastern China’s economy, while policies drive environment technological progress and structural ecologicalization to stimulate economic growth in central and western China. Our results imply that policymakers should take into consideration the readiness levels of each region regarding the adoption of Industry 4.0 and circular economy, and that the government should consider and ensure the participation of all stakeholders, including firms.
•Focus on the economy’s driving forces under Industry 4.0 and circular economy.•Environment and new-energy technological progress promote economic growth in China.•Innovation policy drives economic growth by inducing biased technological progress.•Backstop and environment technological progress benefit eastern and central China.•Industrial policy works well on structural ecologicalization and regional economy.
To better analyze China's carbon neutrality target, this study investigates the effect of green innovation and investment in the energy industry on China's provincial and regional data from 1995 to ...2017. Using Westerlund and Edgerton's panel cointegration test, the authors found a stable long-run relationship between CO2 emissions and its determinants. We found that under major structural breaks at the local, regional, and global levels, such as the East Asian crises of 1997, the financial crises of 2007–2008, China's RMB exchange rate reform announced on August 11, 2015, and mild recession in 2001, CO2 emissions, income, green innovation, renewable energy use, and energy industry investment are cointegrated. The environmental Kuznets curve hypothesis is valid. In the long run, income, environmental innovation, investment in the energy industry, and renewable energy consumption are key contributors in explaining CO2 emissions. The empirical evidence from augmented mean group (AMG) is consistent with the estimates of CS-ARDL. Concerning practical implications, the findings suggest that there is a need to switch the Chinese economy to more sustainable sources of energy, a viable solution to abate environmental degradation. China should introduce and shift investments to green innovation.
•We explore factors that help to achieve the carbon neutrality target of China.•The novel panel data econometric tools were used for empirical analysis.•It confirmed the existence of the EKC hypothesis for provincial data of China.•Investment in energy and technological innovation helps to reduce emissions.•Renewable energy consumption also helps to achieve zero emissions target.
China has announced its commitment to peak carbon emissions before 2030 and reach carbon neutrality by 2060. However, market segmentation may hinder these achievements because it creates carbon ...leakage among provinces. This study empirically examines the impact of market segmentation on the effectiveness of environmental regulations based on a dynamic spatial panel approach using data for 30 Chinese provinces from 2004 to 2018. Our results showed that pure environmental regulation can significantly curb carbon emissions; however, under the influence of market segmentation, carbon emissions reduced in the region are released into the neighboring provinces through the carbon leakage pathway, while the total carbon emissions raised, leading to the “green paradox”. The study also showed that the “green paradox” effect of market segmentation is more pronounced for provinces with a higher share of secondary industries, suggesting industrial transfer as the primary pathway of carbon leakage between provinces in China. Therefore, to effectively avoid the green paradox phenomenon, it is necessary to continuously promote market unification, optimize the industrial structure, and establish a unified carbon reduction system. This study clarified the relationship between market segmentation and the green paradox, thereby providing insights for China to achieve its carbon emission reduction and carbon neutrality goals.
•We explore the dynamic correlation between market segmentation and carbon emissions.•Market segmentation may cause “green paradox".•Carbon emissions are released in adjacent provinces through carbon leakage pathways.•Industrial transfer is major pathway for carbon leakage between provinces in China.
This study breaks through the limitation of traditional analysis that only considers the economic development factors and further explains the reasons for the existence of inter-provincial market ...segmentation in China from the perspective of industrial transformation performance by combining environmental protection. The study examines panel data from 30 provinces in China from 2004 to 2017. It uses a super-efficiency slacks-based measure model to evaluate the performance of industrial transformation considering environmental protection and a fixed-effect model to analyze the impact of market segmentation on industrial transformation performance. The results show that market segmentation has an inverted "U" effect on the region’s immediate and future industrial transformation performance. That is, for most regions, market segmentation can significantly improve the performance of industrial transformation. For regions with higher environmental regulations, market segmentation is more conducive to the improvement of industrial transformation performance, which shows that local governments will give up some market efficiency while carrying out environmental protection. The research results not only confirm the relationship between market segmentation and industrial transformation performance but also have important promotional significance for China’s economic green development.
•The Super-SBM method was used to evaluate industrial transformation performance.•Market segmentation has an inverted "U" effect on industrial transformation.•Local governments enacting environmental protection may sacrifice market efficiency.•The losses from reduced market efficiency outweigh the gains from local protection.•Coordination by the central government is critical to eliminate local protection.
Decomposition analysis has become a popular tool to study CO2 emissions and, in this study, we developed a combined decomposition approach to emissions analysis by integrating the logarithmic mean ...Divisia index and production-theoretical decomposition analysis. Based on this novel approach, we investigated the driving factors of CO2 emissions in China over the latest Five-Year Plan period (2011–2015) and analyzed the inequality characteristics of such emissions. The results showed that 1) the peak value of CO2 emissions in China declined over the period; 2) the overall inequality presented a decreasing trend, whereas intragroup inequality presented a slightly increasing trend over the period; and 3) generally, the potential energy intensity effect contributed to the decrease in CO2 emissions in developed provinces, whereas the potential carbon factor effect accounted for the decrease in CO2 emissions in less-developed provinces. Based on our empirical results, we recommend that policy-makers consider several factors when implementing CO2 policies.
•A novel combined decomposition approach to emission analysis is developed.•The peak value of CO2 emissions in China declined from 2011 to 2015.•Inequality decreased overall, while intragroup inequality slightly increased.•Potential energy intensity decreased emissions in developed provinces.•Potential carbon factor decreased emissions in less-developed provinces.
With carbon pricing being implemented, current investment in carbon-intensive energy infrastructure will be exposed to carbon pricing risk, and some may even become stranded assets. In this work we ...build a real options-based model to quantify the implied risk for newly-built coal plants to become stranded assets by carbon pricing, and focus on the case of China, which is heavily relying on coal power and is introducing a nation-wide carbon market, to make a case study. The probability distribution over time for coal plant to become stranded is obtained, and the expected lifespan of newly-built plant is estimated in carbon pricing scenarios. Our results show that carbon pricing will increase the risk for coal plants to become stranded assets and the plant lifespan will be shortened accordingly. Moreover, higher carbon price and auction ratio of carbon permits will lead to higher stranding risk. Specially, in the case of full auction of carbon permits, with the average carbon price of 50 CNY/tCO2 observed in China's emission trading pilots being introduced, the expected lifespan is shortened by 3 years; further with the carbon price reaching 100CNY/tCO2, the expected lifespan is shortened by 10 years. Thus the implied risk of coal plants' becoming stranded assets by carbon pricing should be incorporated into the investment evaluation, to avoid making myopic and even wrong decision.
•The risk for China's coal plant to become stranded asset under carbon pricing is quantified•The probability distribution over time for coal plant to become stranded is obtained.•The expected lifespan of newly-built plant is estimated in carbon pricing scenarios.•Plant lifespan is expected to be shortened by 3 years under carbon price of 50 CNY/tCO2.
