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The purpose of this paper is to reveal the mechanism and process of the dynamic evolution of the economy-energy-environment (EEE) system and study the variables that determine the speed of system evolution and development. The innovation is to overcome the defect of single index by constructing a system evaluation index and reveal the regional EEE system's evolution mechanism based on Haken's synergetic theory to supplement a systematic perspective's empirical evidence. It selects 30 provinces, municipalities, and autonomous regions in China to empirically analyse the evolution mechanism of the EEE system from 2005 to 2019. The empirical results show that economic development is the order parameter of the evolution and development of the EEE system. In the process of system evolution, the economic development subsystem is the decisive factor in EEE system evolution. In terms of the positive feedback mechanism of order parameter combination, the EEE system forms a positive feedback mechanism for increasing economic development in the stage of evolution and development. The negative feedback mechanism of decreasing environmental pollution emissions is formed in the EEE system. The increase in pollutant emissions has a certain inhibitory effect on economic growth. The improvement in the economic development level has no promoting effect on pollutants, and economic development, in turn, reduces environmental pollution. [ABSTRACT FROM AUTHOR]

The empirical conclusions regarding the relationship between energy price and energy efficiency are relatively mixed. This paper systematically examines the influence of energy price on energy efficiency in China based on data from 30 provinces between 2003 and 2017, using linear and nonlinear effect analysis. We found that the impact of energy price on energy efficiency in China was positive in general. However, there existed heterogeneous effects of energy price on energy efficiency in various regions, and the effect differed with differences in energy efficiency levels based on the panel quantile regression analysis. Finally, the nonlinear effect analysis based on the panel threshold model indicated that the effect of energy price on energy efficiency increased with the rise of the environmental regulation level and economic growth rate, while it decreased with the ascent of the degree of energy price distortion and economic development level. In particular, when the value of a region's economic development level and economic growth rate was within a certain range, the impact was not statistically significant. Overall, these findings contribute to a deeper understanding regarding the effect of energy price on energy efficiency in China. [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]

The goal of this study is to develop a model based on panel data from 30 Chinese provinces to assess rebound and fixed effects, as well as policy implications, in order to provide a theoretical foundation for the rapid advancement of lowcarbon transformation, which is a necessary result of a new stage in environmental growth. The results of primary analysis are the CO2 emission intensity reached 15.72 kt/million yuan in 2019, which was an great decline of 21.86 kt/million yuan as compared with the intensity in 2001; the average value of technological progress reached 1.017, waved like a U shape. The findings of empirical study show that the amount of energy CO2 emission rebound ranged widely; the average value of the rebound impact was -0.449; a 1% rise of technological progress led a 0.442% CO2 emission decrease, notably in Central and Western China. The results lower the cost of drafting energy policies as well as the decision-making involved and increase the economic advantages and transformation rate of technical breakthroughs in practice. [ABSTRACT FROM AUTHOR]

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: 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]

In this article, the relationship between energy consumption and economic growth is examined from the viewpoint of China's industrial sectors. Panel data from 37 industrial sectors in China covering the period from 1998 to 2010 was used in this study. Not only first generation panel unit root tests and panel cointegration tests, but also second generation tests that account for dependence between cross-sectional units were employed. The empirical results reveal that both energy consumption and economic growth are integrated as order one, and they are cointegrated. Panel fully modified ordinary least squares estimators show that a 1% increase in energy consumption increases the real value added of industrial sectors by 0.871%, and a 1% increase in real value added of industrial sectors increases energy consumption by 1.103%. The panel vector error correction models for causality tests are estimated by a system generalized moment method. We find a unidirectional causal relation running from economic growth to energy consumption in the shortrun. In the long run, however, there is evidence of a unidirectional causality running from energy consumption to economic growth. [ABSTRACT FROM AUTHOR]