Based on panel data from 2000 to 2015, this study estimates the green total factor productivity (GTFP) of each of the 11 provinces in the Yangtze River economic belt using z slacks-based measure in ...data envelopment analysis model. The influences of fiscal decentralization and environmental regulation on GTFP are analyzed by calculating the environmental regulation intensity and degree of fiscal decentralization and by constructing a panel quantile regression model. The results indicate that fiscal decentralization can stimulate GTFP growth, but this effect declines when the quantile value increases. Appropriate fiscal decentralization can improve GTFP, while excessively strong fiscal decentralization becomes an obstacle to GTFP. This study also established a certain range within which local governments' fiscal freedom can be increased to stimulate GTFP growth. Finally, this study estimates the GTFP under the dual constraints of pollution emissions and economic growth and links the improvement of GTFP with environmental regulation and China's unique economic decentralization system, thereby providing practical support for the governance of environmental pollution in China.
•Environmental regulation's GTFP stimulation rises when the quantile increases.•Environmental regulation increases environmental cost and reduces short-term GTFP.•In general, fiscal decentralization is not conducive to the growth of GTFP.•An appropriate level of regulation and decentralization can improve GTFP.•The Porter hypothesis holds in the Yangtze River economic belt.
•Proposes a Ray slack-based model drawing on polar coordinates theory.•Evaluates China's provincial environmental efficiency using Ray slack-based model.•Environmental efficiency is the highest in ...the east and lowest in central regions.•Detects environmental efficiency–economic growth relationship with spatial effect.•Identifies ways to develop environmental efficiency and regional economies.
The Chinese economy has been experiencing rapid growth since the implementation of the reform and opening-up policy. However, at the same time, it faces issues regarding resource savings and environmental protection, which are important aspects of the new industrialization. Therefore, this study conducts data envelopment analysis (DEA) to evaluate the environmental efficiency of Chinese regions. Certain existing DEA models account for undesirable outputs and do not elucidate the weak disposable relationship between undesirable and desirable outputs. Thus, polar theory is introduced among the DEA modeling in this study. First, drawing on stochastic frontier analysis, Ray stochastic frontier analysis, and DEA, we propose a Ray slack-based model (RSBM) to evaluate provincial environmental efficiencies in China from 2004 to 2012. Subsequently, an RSBM-Malmquist–Luenberger (total factor productivity) index is structured. Finally, economic growth, environmental efficiency, and energy consumption are analyzed using spatial panel econometrics. As this study treats industrial waste as undesirable outputs, the RSBM results show that the environmental efficiencies in the east are the highest, while those in the central regions are the lowest. The spatial econometric analysis reveals that the ratios of direct to total elasticity and those of direct to total effect for capital, labor, and energy input variables are fixed. Furthermore, the study provides policy implications and suggestions for future research.
•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.
Many countries like China are in a dilemma between economic growth and environmental deterioration (e.g., smog weather). Simultaneously, a growing people concern the product's environmental ...performance along with their improving environment awareness. This paper focuses on the impacts of carbon footprint and low-carbon preference on the production decision of emission-dependent firms in the cap-and-trade system. The cap-and-trade system uses the total “cap” to attain environmental goals and allows “trade” to achieve the effective scheduling through market regulation. Under this mechanism, through analyzing the influence of carbon footprint and low-carbon preference on the market supply and demand, we build a production optimization model and develop the optimal decisions. Several interesting management insights on environmental preference and policy are concluded.
Abstract
This study seeks to estimate the carbon implications of recent changes in China’s economic development patterns and role in global trade in the post-financial-crisis era. We utilised the ...latest socioeconomic datasets to compile China’s 2012 multiregional input-output (MRIO) table. Environmentally extended input-output analysis and structural decomposition analysis (SDA) were applied to investigate the driving forces behind changes in CO
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emissions embodied in China’s domestic and foreign trade from 2007 to 2012. Here we show that emission flow patterns have changed greatly in both domestic and foreign trade since the financial crisis. Some economically less developed regions, such as Southwest China, have shifted from being a net emission exporter to being a net emission importer. In terms of foreign trade, emissions embodied in China’s exports declined from 2007 to 2012 mainly due to changes in production structure and efficiency gains, while developing countries became the major destination of China’s export emissions.
•Carbon emissions from energy consumption of 282 prefecture-level cities in China were calculated.•A new method for calculating carbon emission factors for electricity is proposed.•Extending the ...Atkinson Index to the application of Carbon Fairness.•Measured the inequality and fairness indicators of carbon emissions from energy consumption at the prefecture-level city level in China.
This paper focuses on the conceptualization and quantification of carbon emission inequality and fairness from energy consumption. In order to more accurately measure the carbon emissions generated by electricity consumption in each city, we firstly propose a new method for calculating the carbon emission factor for electricity, and calculates the carbon emissions from energy consumption in 282 prefecture-level cities in China from 2003 to 2019. Through the application of the Theil-Kaya decomposition mechanism and the improved Atkinson index, we conducted an in-depth study of the carbon emission inequality and fairness indicators from energy consumption. The results show that (1) Although China's overall inequality has declined, it remains significant in the western region, with its inequality indicator fluctuating from 0.548 in 2003 to 0.683 in 2019.(2) The decomposition of the drivers of inequality indicators shows that the contribution of GDP per capita to inequality is increasingly being replaced by energy intensity and the energy carbon emission factor, with energy intensity emerging as the main driver, contributing more than 40% to inequality in 2019, both overall and in the three regions.(3) The results for the fairness indicator, on the other hand, show a certain degree of divergence. Further Dynamic Time Warping fitting analysis shows that regardless of how the public's sensitivity to carbon emissions varies, the change trends of the fairness and inequality indicators for carbon emissions in the eastern region show a high degree of convergence, even in the two most extreme cases. The fit is poorest in the western region, but improves significantly if public's sensitivity to carbon emissions increases. (4)To sum up, some policies that are consistent with the context of the times, such as the East-West regional counterparts and the construction of a new type of power system, are worthy of priority consideration by the Government.
China has entered the economic transition in the post-financial crisis era, with unprecedented new features that significantly lead to a decline in its carbon emissions. However, regional disparity ...implies different trajectories in regional decarbonisation. Here, we construct multi-regional input-output tables (MRIO) for 2012 and 2015 and quantitatively evaluate the regional disparity in decarbonisation and the driving forces during 2012-2015. We found China's consumption-based emissions peaked in 2013, largely driven by a peak in consumption-based emissions from developing regions. Declined intensity and industrial structures are determinants due to the economic transition. The rise of the Southwest and Central regions of China have become a new feature, driving up emissions embodied in trade and have reinforced the pattern of carbon flows in the post-financial crisis period. Export-related emissions have bounced up after years of decline, attributed to soaring export volume and export structure in the Southeast and North of the country. The disparity in developing regions has become the new feature in shaping China's economy and decarbonisation.
•Our findings indicate that the prevention and control of the COVID-19 pandemic are not directly related to city size, but city governance capacity.•We identify three main mechanisms by which urban ...governance affects the prevention and control of the COVID-19 pandemic.•This paper makes marginal contributions to existing studies related to the importance of urban governance for timely crisis responses.
This study analyzed the effects of urban governance and city size on COVID-19 prevention and control measures. Based on real-time data in 276 prefecture-level Chinese cities, we used the ordinary least squares plus robust standard error strategy. It was found that: (1) despite the non-significant effect of city size, urban governance capacity was an important factor affecting the prevention and control of the COVID-19 pandemic; urban governance capacity was particularly significant in the late control of the pandemic, but not significant in the early prevention; for every unit increase of urban governance capacity, the number of recovered COVID-19 cases per capita increased by 2.4%. Moreover, (2) the influence mechanism of anti-pandemic measures in cities could be divided into the workforce, financial, and material effects, and their contribution rates were 26.15%, 32.55%, and 37.20%, respectively; namely, the effective/timely assistance from Chinese central government regarding the workforce, financial, and material resources in key pandemic areas and nationwide played a major role in pandemic control. Additionally, (3) cities with a high level of smart city construction were more capable of enhancing the pandemic prevention and control effect, indicating that smart city construction is conducive to enhanced coping with public crises.
Using provincial data on energy-related CO2 emissions in China from 1997 to 2014 and the CO2 emission Gini coefficient (CEG), this study evaluates China's spatial inequality in energy-related CO2 ...emissions. Further, we decompose this inequality and its variation from the perspectives of production and residential energy consumption, using the source decomposition and source increment decomposition methods. This paper presents a new CEG source increment decomposition method that can achieve complete decomposition. The results reveal a downward trend in China's overall, production sector and residential sector CO2 emissions inequality. Although the Gini coefficient of CO2 emissions from the residential sector is larger than that from the production sector, the contribution of the latter to the overall CEG is higher. The impacts of the spatial inequality of CO2 emissions from China's production and residential sectors depend on the type of energy. The concentration effect is the primary factor responsible for inducing changes in China’s overall and production sector CO2 emissions inequality, but it is not the only dominant factor for the residential sector CO2 emissions inequality.
•We propose a CO2 emission Gini coefficient source increment decomposition method.•We decompose emissions inequality by production and residential consumption.•Residential emissions inequality is greater than production and overall inequality.•Production emissions inequality contributes more to overall emissions.•The concentration effect leads to production and overall inequality changes.
In this paper, we respectively decompose and study different effects of technological progress on carbon emissions in China based on the combination of the logarithmic mean Divisia index method, the ...Solow residual model, and spatial econometrics. Furthermore, we propose an improved approach to estimate the rebound effect index. By comparing the different effects of technological progress on carbon emissions, our results indicate that China's overall domestic technological progress reduced its carbon emissions over this period. As for the rebound effect index, the estimated results are higher than in previous studies because of the spatial rebound effect, which was ignored by previous studies. Regionally, although the eastern region had high rebound effects, the western region is at the greatest risk from the rebound effects. Finally, we present specific environmental policy proposals for China's sustainable development based on empirical results.
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