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Using panel data of 11 provinces in the western region of China, the paper empirically analyzes the influence of public environmental participation on the effectiveness of pollution governance. Based on documents from provincial governments in Western China, the paper uses Nvivo software to extract keywords about local governments' attention to the environment and examines its mediating effect between public environmental participation and pollution governance. Furthermore, a classifiable analysis of government environmental attention is carried out, and the effect of local governments' attention to the environment on pollution governance is studied. The results show that public environmental participation promotes pollution governance by increasing the governments' attention to the environment. Additionally, local governments' environmental attention also has a promotive effect on pollution governance, and the increase in environmental decision-makers' attention to environmental pollution and energy consumption is conducive to the improvement of environmental quality, but the effect of environmental protection and collaborative attention on environmental quality improvement still needs to be explored further. • Local governments' attention to the environment is estimated. • Public environmental participation promotes pollution governance. • Local Governments' Environmental Attention plays mediating role. • Local Governments' Environmental Attention has a promotive effect on environmental quality. • The effect of collaborative attention on environmental quality improvement still needs to be explored further. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2006 to 2016, the Gaussian kernel density estimation was initially used to describe the characteristics of the inter-provincial differences in household energy consumption (HEC), a dynamic panel data model was established secondly to study the main factors affecting HEC, and finally the counterfactual decomposition method was used to calculate the contribution of each factor to the inter-provincial differences in HEC. The research results are shown as follows: First, the inter-provincial HEC in China shows a phenomenon of agglomeration and growth, and the HEC level of different regions presents difference and imbalance. Second, the logarithms of consumption habits, total population and residents' income have significant effects on the logarithm of HEC, the influence coefficients are 0.191, 0.073 and 0.745, respectively; HEC not only has significant inertia characteristics, but also has certain population size effect and wealth effect. Third, the logarithms of technological progress, urbanization and household energy price have significant effects on the logarithm of HEC, the influence coefficients are 0.864, 0.195 and −0.346, respectively; the HEC saved by technological transformation is not sufficient to offset the increase in HEC demand, urbanization can improve HEC significantly, but the household energy price significantly inhibits HEC. Finally, from the perspective of contribution, the total population, residents' income and urbanization contribute a lot to the inter-provincial differences, totaling 73.02%. The possible innovations of this paper are as follows: First, the contribution of the influencing factors to the difference of inter-provincial HEC is studied, which is rarely seen in the previous literature. Second, compared with traditional decomposition method, counterfactual decomposition method is more convenient for economic interpretation. Third, the divergent conclusions of scholars are pointed out in this paper, and the actual impact of influencing factors on HEC are clarified. Image 10086681 • The level of inter-provincial HEC shows difference and imbalance. • HEC has significant inertia characteristics, population size effect and wealth effect. • HEC saved by technology is not sufficient to offset the increase in HEC demand. • Total population, residents' income and urbanization contribute 73.02%. • The statistical analysis tool used in this paper is Stata15. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 Chinese provinces in 2000–2018, this paper measures the green total factor energy efficiency (GTFEE) of China with the super-slack-based measure (Super-SBM) model. Then, the spatial correlation of provincial GTFEEs was analyzed, a spatial econometric model was established based on the panel data, and was used to empirically verify the effect of financial agglomeration, technological innovation, and financial agglomeration and technological innovation interaction on GTFEE. The results show that: in the sample period, most Chinese provinces had a low GTFEE, and the low-GTFEE provinces mainly belong to inland area; only a few eastern coastal provinces achieved a satisfactory GTFEE. China and its three regions exhibited similar trends of GTFEE. By mean GTFEE, eastern region ranked the highest, followed by central region; the western region came at the bottom. The Global Moran's I values show strong spatial correlations between provincial GTFEEs, that is, adjacent provinces often have similar GTFEEs, and the provinces tend to cluster in terms of GTFEE. According to the spatial econometric model, GTFEE is significantly inhibited by financial agglomeration, but significantly promoted by technological innovation. GTFEE is not clearly affected by financial agglomeration and technological innovation interaction. Opening up has a significant positive impact on GTFEE, while industrial structure, energy structure and environmental regulation have a significant negative impact on GTFEE. [ABSTRACT FROM AUTHOR]

One of the critical challenges facing China is environmental pollution caused by insufficient use of clean energy. This paper empirically investigates the impact of rural labor mobility on household clean energy use using data from the China Family Panel Studies (CFPS). The results indicate that labor mobility significantly promotes the adoption of clean energy by rural households, with income effects and information channel effects serving as the underlying mechanisms. The study also finds that health risks, as an important consideration for household energy use choices, enhance this positive effect. Furthermore, heterogeneity analysis reveals that labor mobility has a greater impact on households with lower levels of education, lack of social security, and those located in central and western regions. Therefore, the government should take measures to increase the income of the rural migrant population and continuously widen the information channels for rural households to promote clean energy use. The findings of this study provide a new perspective and evidence for understanding household energy use behavior in China, offering valuable insights for policymakers aiming to expand the use of clean energy. • Labour mobility significantly contributes to clean energy use in rural households. • Income effects and information channel effects are the main mechanisms of action. • Health risks faced by households play a moderating role. • Heterogeneity in region, educational attainment, social security status will influence the effect of labour mobility. [ABSTRACT FROM AUTHOR]

Human activities are closely related to energy consumption and carbon emissions. Nevertheless, in the context of energy transition and carbon emission reduction policies, the impact of population migration on energy consumption and carbon emissions is still unclear. Based on the panel data of 30 provincial regions in China from 2000 to 2019, this paper uses the spatial Durbin model to perform a spatial econometric investigation on this issue. In particular, this study innovatively embeds two spatial weight matrices, an economic gravity weight matrix and a population migration weight matrix, into the spatial Durbin model to capture the spatial spillover effects of population migration. The results show that population migration has obvious adverse impacts on the provinces with net outward population migration. Specifically, on the one hand, population migration increases energy consumption and energy poverty, but energy poverty is more severe in provinces with net outward population migration. On the other hand, population migration increases the carbon emissions and carbon reduction barriers of the provinces with net outward population migration and has no significant impact on the carbon emissions and carbon reduction barriers of the provinces with net inward population migration. Besides, the results of heterogeneity analysis show that population migration causes gaps in the energy structure among regions and even triggers the carbon transfer to provinces with net outward population migration. On the whole, the research results of this paper all prove that population migration increases the carbon reduction barriers in the provinces with net outward population migration. These empirical insights enrich the relevant theoretical achievements of the impact of population migration on energy consumption and carbon emissions and have a high reference value for formulating more reasonable regional energy transition and carbon emission reduction policies. • The spatial spillover effects of population migration on energy consumption and carbon emissions are explored. • The spatial Durbin model is used in this paper. • The spatial Durbin model is embedded with the economic gravity weight matrix and the population migration weight matrix. • Population migration has obvious adverse impacts on the provinces with net outward population migration [ABSTRACT FROM AUTHOR]

• The impact of economic growth pressure on energy efficiency improvement is discussed. • Economic growth pressure has hindered the improvement of energy efficiency. • Heterogeneity effects exist in individual dimension and temporal dimension. Economic growth target management has been a typical feature of Chinese governments at all levels for a long time in the past decades. Based on a panel data of 188 Chinese cities, this paper examines the impact of pressure brought by economic growth target on energy efficiency improvement. The results suggest that economic growth pressure has hindered the improvement of energy efficiency. For every unit of increase in economic growth pressure, the improvement indicator of energy efficiency will decrease by 3.3%. This finding is robust, after replacing explained variables and core explanatory variables, no substantial changes are found. Sub-sample regression confirms the existence of heterogeneity effects in individual dimension and temporal dimension. Finally, by summarizing existing studies, this paper finds that the investment imbalance effect, the hindrance effect on industrial structure upgrading, and the crowding-out effect on innovation are three important ways for economic growth pressure to restrain the improvement of energy efficiency. Our findings are helpful to understand the role of the government's economic growth target management in resource allocation and energy utilization and provide a certain practical reference for China to promote high-quality economic development. [ABSTRACT FROM AUTHOR]

Abstract: Recently, energy production in China fell behind energy consumption. This poses important challenges for the rapidly growing Chinese economy. As a consequence, the causal relationship between energy consumption and GDP is an important empirical issue. This paper examines Granger causality between energy consumption and GDP in China using province-level data. The current paper extends the Granger causality analysis employed in previous studies by taking into account panel heterogeneity. Specifically, four different causal relationships are examined: homogeneous non-causality (HNC), homogeneous causality (HC), heterogeneous non-causality (HENC), and heterogeneous causality (HEC). HC and HNC hypotheses are rejected for causality in either direction, from GDP to energy or from energy to GDP, which implies that the panel made up of Chinese provinces is not homogeneous. Then, heterogeneous causality tests (HEC ad HENC) are conducted for each province. For the causality running from GDP to energy, 19 provinces exhibit HEC and 11 provinces exhibit HENC. For the causality running from energy to GDP, 14 provinces exhibit HEC and 16 provinces exhibit HENC. The results suggest that the Chinese government should incorporate a regional perspective while formulating and implementing energy policies. [Copyright &y& Elsevier]

This paper investigates the impact of urbanization on provincial energy efficiency in China. Using panel data of 30 Chinese provinces between 2003 and 2014, we adopt a stochastic frontier model to estimate energy efficiency in China, and apply a series of spatial panel data models to tackle spatial dependence of energy efficiency between provinces. Our results show that the overall impact of urbanization on energy efficiency is negative in China. These results are established after controlling for spatial correlation and other confounding factors, and are also robust to various model specifications. We also document that the impact of urbanization on provincial energy efficiency manifests through both a direct negative impact induced by the focal province's urbanization process, and an indirect positive spillover effect caused by urbanization in adjacent areas. [ABSTRACT FROM AUTHOR]

For economic activities, energy is a necessary component of production. As the world's largest energy consumer and carbon emitter, China faces greater resource constraints and environmental pressure in the background of global climate change, improving energy efficiency is the inevitable path for long-term development. However, the energy efficiency in China at this stage is relatively low, thus improving energy efficiency is urgent. Based on the panel data from the database of Chinese industrial enterprises and the database of Chinese industrial enterprises' pollutant emissions between 2003 and 2012, this paper empirically conducts a thorough investigation on the nonlinear impact of spatial agglomeration and enterprises' energy efficiency, and further examine its heterogeneity and mechanisms. The results show that: (1) There is a significant U-shaped link between spatial agglomeration and enterprises' energy efficiency. (2) Based on agglomeration externalities, scale effect, learning effect, competition effect, and policy effect are the internal mechanisms through which spatial agglomeration impacts on enterprises' energy efficiency. (3) The effects of spatial agglomeration on enterprises' energy efficiency are influenced by technology level, energy consumption level, agglomeration patterns, and enterprise characteristics. Based on the empirical findings, we suggest that enterprises take full advantage of the benefits brought by spatial agglomeration, and that the government encourage the growth period of spatial agglomeration to become more profound, more synergetic, and more diverse. [ABSTRACT FROM AUTHOR]

Abstract: Recently, environmental pollution has attracted a lot of attention domestically and internationally. It is known that energy utilization is a major source of China’s environmental pollution. Measuring environmental efficiency of energy utilization in Chinese provinces first, the paper then offers decision supports for relevant departments in order to achieve sustainable development of energy and environment in China. This research chooses CO2 emission as a substitute variable for environmental effects of energy utilization and puts it into the study framework based on total-factor production theory to measure the environmental efficiency of energy utilization of each province and three major regions. On the basis of the above results this research further measures the cost of environmental regulation for each province. Provincial panel data during the period of 2000–2007 are used to carry out empirical study. The analysis indicates that the environmental efficiency of energy utilization in Chinese provinces varies greatly from each other, meaning that both economic output and CO2 emissions need considerable improvement. In addition, the results of empirical study also show that the environmental efficiency of energy utilization in China is quite low. Therefore, to ensure sustainable development of China’s energy, economy and environment, we should resort to advanced technology as the support to promote the efficient and clean utilization of energy resources. Besides, most Chinese provinces have spent quite a lot on environmental regulation, implying that in these provinces development of the economy and the environment are not in harmony. The contributions of this research are as follows: it constructs the models for measuring environmental efficiency of energy utilization in Chinese provinces; it introduces the idea of “environmental regulation” into research system and measures the environmental regulation cost of each Chinese province. [Copyright &y& Elsevier]

Abstract: This paper uses nonparametric efficiency analysis technique to estimate the energy efficiency, potential emission reductions and marginal abatement costs of energy-related CO2 emissions in China. We employ a non-radial slacks-based data envelopment analysis (DEA) model for estimating the potential reductions and efficiency of CO2 emissions for China. The dual model of the slacks-based DEA model is then used to estimate the marginal abatement costs of CO2 emissions. An empirical study based on China’s panel data (2001–2010) is carried out and some policy implications are also discussed. [Copyright &y& Elsevier]

Abstract: The negative effects of energy consumption and pollution have restrained the Chinese economy from further rapid growth. Therefore to clarify their relationship with economic growth can lay a solid foundation for the decision-making of energy conservation and pollution reduction and ensure the sustainable development of the Chinese economy. Using panel data on the 30 Chinese provinces from 2001 to 2008, this paper builds a 3E model of pollution, energy and production and conducts an empirical study on the interaction between pollutant emission, energy consumption and average GDP. [Copyright &y& Elsevier]

Abstract: Based on the panel data of three industries in China, this paper calculates the energy rebound effect arising from energy efficiency improvement, by stripping the rebound of energy usage caused by industrial restructuring from model. Results indicate: the similarity between them demonstrating energy efficiency rebound effect as the main component of energy rebound effect; the delayed rebound peak of the secondary industry reflects its lagged respond to changes in energy efficiency; with regard to the peak value in 2009 when calculating the whole nation, author concerns it with the intensification in investment on basic industries and relaxation of restriction over high energy consumption enterprises; the relatively larger value of energy efficiency rebound in China can not be ignored by policy-makers [Copyright &y& Elsevier]

Abstract: With the growing impact of global climate changes, carbon emissions reduction is becoming an international theme. There are significant differences among China''s economic development regions, regional energy consumption and carbon emissions in those regions are quite different. In the paper, 14 representative regions are selected from most developed regions, more developed regions, and less developed regions in China, based on the regional 2001-2008 panel data to make the econometric analysis and comparative analysis, and the regional carbon emissions reduction investigations to different development stages are given according to the results of analysis different development stages. [Copyright &y& Elsevier]

Abstract: The global energy issues have stimulated increasing research interest in the linkages between the energy consumption and economic growth. As the biggest developing country, China has surpassed United States to be the world''s largest energy consumption country. This paper examines the casuality between GDP and energy consumption by using updated China provincial panel data for the period 1985–2007 within a multivariate framework by adopting Pedroni''s panel methodology. The results show that cointegration is present between real GDP, energy consumption, the labor force, and real gross fixed capital. The results of Granger-causality test indicate the presence of Bi-directional causality between energy consumption and economic growth which supports the feed back hypothesis.Economic interpretations of the empirical results are also presented. [Copyright &y& Elsevier]

• We estimate the energy efficiency and direct rebound effect of residential electricity consumption by using the stochastic energy demand frontier model. • The average value of efficiency is 0.491, and the average rebound effect is 48%. • We find that electricity price and household size have a negative impact on the rebound effect, while the impact of income is inverted U-shaped. • The rebound effect varies across before and after the implementation of the increasing block pricing policy, considering rural and urban residents and different regions. The rebound effect is a potential threat to energy efficiency related policies to save energy. Based on data from China family panel studies over the period 2010–2018, this paper measures the energy efficiency and direct rebound effect of residential electricity consumption by using the stochastic energy demand frontier model. The result shows that the average value of efficiency is 0.491, and the average rebound effect is 48%. It means that there is still room for improvement in China's household electricity consumption efficiency. But the expected electricity- saving after improving efficiency can only achieve 52%. Besides, we find that electricity price and household size have a negative impact on the rebound effect, while the impact of income is inverted U-shaped. Finally, the rebound effect varies between before and after the implementation of the increasing block pricing policy, considering rural and urban residents and different regions. These findings provide some policy implications for the residential electricity pricing system under the background of energy conservation and climate change. [ABSTRACT FROM AUTHOR]

• Assessing the Environmental Performance of china's Three Urban Agglomerations. • Using the dynamic DEA model based on the input–output perspective. • The total environmental efficiency exhibits a wave-like development trend. • PM2.5 is the best unexpected output after strict prevention from 2013 to 2017. • Industrial smoke and dust emissions need to strengthen management in the future. As a special form of a cluster city, urban agglomeration has become an important platform to support national economic growth and to participate in international competition and cooperation, but it faces severe environmental problems. This research thus selects panel data of 60 cities in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2013 to 2017. Based on the input–output perspective, labor and energy consumption per GDP are selected as input indicators, GDP, PM2.5, SO 2 , industrial smoke and dust emissions, and wastewater discharged as output indicators, and fixed assets as a carry-over variable in the dynamic DEA model to evaluate and analyze the environmental efficiencies of these three urban agglomerations. Findings show that their total environmental efficiency exhibits a wave-like development trend, and that the total efficiency score of BTH is better than that of PRD and YRD. From the viewpoint of a sub-efficiency index, PM2.5 is the lowest in unexpected output, where its average five-year efficiency score is 0.9847, while the average score of industrial smoke and dust emissions efficiency is the lowest at 0.6199. Finally, this paper offers suggestions for different problems facing the three urban agglomerations. [ABSTRACT FROM AUTHOR]

As an important part of urban carbon emissions, the carbon emissions from household energy consumption are increasing with the continuous improvement of Chinese urbanization. This study divides family population into 4 groups: adolescents (aged 0–17), young people (aged 18–44), middle-aged people (aged 45–59), and elderly people (aged 60 and older) and develops a calculation model for carbon emissions of household energy consumption in accordance with the latest standards of the World Health Organization based on Chinese Family Panel Studies in 2016. Results showed that the marginal and intergenerational effects coexist in various types of household energy consumption: Families with 3–5 people have the most economical consumption scale and the largest marginal sharing effect; multigenerational families or families with a large proportion of middle-aged and older people are beneficial in reducing household energy consumption. This paper suggests it is important to fully consider the impact of the intergenerational effect, marginal effect, and cultural shock caused by the electronic information age on household energy consumption when formulating standards of household energy consumption. [ABSTRACT FROM AUTHOR]

Whether embedding in global value chain(GVC)can promote China's manufacturing industry green growth is of great importance for China to accelerate the realization of green economy transformation and building of China's high-quality modern ecological economic system. This paper analyzes the impact of embedding in GVC on China's manufacturing industry green growth from perspectives of embedding position and embedding degree, using panel data from 17 manufacturing industries from 2000 to 2014. The study finds that during the inspection period, GVC embedding position and embedding degree of China's manufacturing industry have a fluctuation and there is a large difference between industries, most industries are still in the downstream of GVC, and low-tech industries embedding in GVC to a deeper degree. In the meantime, China's manufacturing industry green growth level has declined, and green growth situation is not optimistic. Dynamic panel results show that raising the GVC embedding position can significantly promote China's manufacturing industry green growth. Further, threshold regression is used to find that when the embedding position crosses a certain threshold, the effect of increasing the GVC embedding degree on green growth changes from inhibition to promotion. And the effect of GVC embedding position and degree on China's manufacturing industry green growth has significant industry heterogeneity. Finally, based on the research conclusions, concrete implications for promoting China's manufacturing industry green growth are put forward: First, China should improve the GVC embedding position of manufacturing industry and enhance the value-added and control capabilities of the value chain. Second, China should increase the GVC high-end links embedding degree of manufacturing industry. While realizing value chain functional upgrading and chain upgrading, increase GVC embedding degree. Third, China should accelerate energy technology innovation, promote the development of new energy, and accelerate the transformation of energy consumption structure. Last of all, China should implement industry differentiation policies, enhance the overall competitiveness of the high-tech industry, and achieve the "essential" improvement of the GVC position of the low-tech industry. At the same time, for all industries, China must improve the level of environmental regulation, increase R&D investment, and reduce the proportion of coal consumption and the proportion of state-owned enterprises. [ABSTRACT FROM AUTHOR]

China's transportation industry, with its typical characteristics of "high energy consumption and high emissions", is a key point for China's CO 2 emission reduction. An investigation of the driving factors of China's transport energy-related CO 2 emissions has great importance for clarifying the "gains" and "losses" as well as the future focuses of CO 2 emissions emission reduction in this sector. Existing studies on the driving factors of transport CO 2 emissions in China fail to incorporate effects of technology and efficiency into decomposition analysis framework. Based on the provincial panel data of China's transportation industry for the period of 2004–2016, this paper uses a comprehensive decomposition framework, which combines the logarithmic mean Divisia index method (LMDI) and production-theoretical decomposition analysis (PDA), to decompose China's transport CO 2 emissions into nine components: emission factor effect, energy structure effect, scale effect, regional structure effect, energy-saving technology effect, production technology effect, energy efficiency effect, production efficiency effect, and potential energy intensity effect. The main results indicate that: (1) during the sample period, China's transport industry witnessed 498.998 million tons (Mt) CO 2 emissions growth. Scale effect was the largest contributor, followed by production technology, energy-saving technology, and energy structure; (2) the improvement of energy efficiency and production efficiency, the decline of electricity's emission factor, and regional structure adjustment played active roles in the CO 2 emission reduction of transportation industry; (3) the performance of various driving factors varies greatly in different provinces. Local governments should establish and implement policies tailored to their characteristics. • A production-theoretical approach was used for China's transport CO 2 emissions. • It can decompose CO 2 emissions from technology and efficiency perspectives. • Results show that during 2004–2016, China's transport CO 2 emissions increased by 498.998 Mt. • Output effect was the largest contributor to this remarkable increase of transport CO 2 emissions. • Technology and efficiency factors cumulatively reduced 242.1 Mt transport CO 2 emissions. [ABSTRACT FROM AUTHOR]

Environmental regulation is of great concern to international academics and policy makers. Previous studies often regarded environmental regulation as an influencing factor when calculating eco-efficiency or energy efficiency. More attention should be given to the efficiency of environmental regulation, especially in industrial field. According to exiting studies, industrial environmental regulation efficiency (IERE) may be influenced by external environmental factors, to explore the influence and obtain an actual efficiency, this paper calculated IERE in China by using the panel data of 30 regions from 2011 to 2015 (the 12th Five-Year Plan period) through the three-stage data envelopment analysis approach. Firstly, the Undesirable-slacks-based model method was used to calculate the original IERE. Secondly, the economic base, industrial structure, urbanization level, and education level were taken as external environmental variables, and the effect of external environmental factors and stochastic disturbance were excluded. Thirdly, the actual IERE can be calculated after adjusting input values. The results showed that China's IERE was underestimated due to the impact from external environmental factors. Moreover, the IERE was more influenced by pure technical efficiency than scale efficiency. The IERE of each region varied, thus, targeted policies should be formulated according to local conditions. This research provided a new analytical method for calculating environmental regulation efficiency. The method can be applied either in other countries or in other sectors. • The environmental regulation efficiency in the industrial field of China was evaluated. • The three-stage DEA method was utilized, the role of environmental variables could be considered. • Industrial environmental regulation efficiency was more influenced by pure technical efficiency. • Three kinds of efficiencies were all underestimated due to the influence of external environmental factors. [ABSTRACT FROM AUTHOR]