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Expanding the supplies of new energy can not only reduce CO2 emissions, but also alleviate energy shortage. This paper applies the quantile regression to investigate the new energy industry in China. The results show that economic growth exerts the greatest effect on the new energy industry in the lower 10th quantile province. This is because these provinces have the developed economies, demand for a higher ecological environment and new energy resources. Foreign energy dependence has a minimal impact on the new energy industry in the 25th-50th quantile province, due to their minimal oil importation. The contribution of technological progress to the upper 90th quantile province is the lowest, because their R&D capabilities are the weakest. The impact of energy consumption structure decreases in steps from the lower 10th quantile provinces to the upper 90th quantile provinces. The agricultural sector promotes the new energy industry in most provinces. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the determinants of decline in energy intensity in four Chinese industries—pulp and paper, cement, iron and steel, and aluminum. This paper attempts to answer the following key question: For the purpose of promoting energy efficiency, do prices, technology, enterprise restructuring and other policy-related instruments affect various sectors uniformly so as to justify uniform industrial energy conservation policies, or do different industries respond significantly differently so as to require policies that are tailored to each sector separately? In this paper, we examine this question using data for China's most energy-intensive large and medium-size enterprises over the period 1999-2004. Our results suggest that in all four industries rising energy costs are a significant contributor to the decline in energy intensity over our period of study. China's industrial policies encouraging consolidations and scale economies also seem to have contributed to reductions in energy intensity in these four industries. [ABSTRACT FROM AUTHOR]

Global climate change has caused governments worldwide to take actions to improve their energy efficiency. This paper investigates how China's Top-1000 program, a command-and-control type of energy-saving mandate, has affected the operational choices of firms, and in turn, their profitability. We apply the propensity score matching method to find "identical twins" for the participants in the Top- 1000 program, then conduct a difference-in-differences analysis on the matched sample. Our findings suggest that the profitability of the enterprises targeted for energy savings decreased by one-third, mainly due to increased production costs. The targeted enterprises tended to increase their fixed assets per capita, which was associated with improvements in energy efficiency. Furthermore, compared to similar untargeted enterprises, there was a significant slowdown in the production growths of the targeted enterprises, raising concerns about carbon leakage due to increased production by less efficient producers. [ABSTRACT FROM AUTHOR]

This paper proposes an extended Solow decomposition framework with a finite mixture model, which is incorporated to account for heterogeneous regimes. The model decomposes green economy into two different components, namely, green total factor productivity and factor endowment. Then, we reestimate the growth sources of green economy and especially the importance of energy consumption in China's provincial industries over 2000-2015. The empirical results suggest that there are three green growth regimes across Chinese provinces for overall economy and different industries. Specifically, some provinces switch regime over time, while the others maintain the same regime. Furthermore, when controlling for regime heterogeneity, the contribution of factor endowment decreases and that of green total factor productivity increases. With respect to energy consumption, traditional methods overestimate its importance in the primary and tertiary industries and underestimate that in the secondary industry. In addition, the reliance of China's overall economy and the secondary and tertiary industries on energy consumption decreases as economy develops. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an important policy in the current global response to climate change and has been widely recognized by various industries. In the process of promoting carbon neutrality, new energy plays a pivotal role. In this study, the definition and connotation of new energy and its role and specific operation in the energy transition of carbon neutrality are firstly explained. Promoting new energy development requires significant green and low-carbon investments. Taking China as an example, this paper analyzes the opportunities brought by the carbon neutral process to the field of green finance and analyzes the main features and development trends of green finance in China at present. Then this paper proposes policy recommendations to strengthen the development of green finance in China in terms of improving the green financial policy system, enhancing the supply capacity of green financial services, and optimizing the supporting environment for green financial development. Finally, this paper analyzes the measures and experiences of the United States in promoting low-carbon development and proposes countermeasures for China's low-carbon development on the basis of the five major relationships that need attention in China's carbon-neutral process. That is, strengthen the top-level design and improve the regulatory policy system; optimize the energy structure and increase the proportion of clean energy; optimize the industrial structure and reduce energy consumption in key industries; build a complete low-carbon technology system and promote low-carbon technology research and development and demonstration applications, and encourage local conditions to explore low-carbon development paths. The development of green finance can contribute to the advancement of new energy technologies, thus contributing to the achievement of carbon neutrality goals. [ABSTRACT FROM AUTHOR]

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China's urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 2001-2014, for the first time, we investigate the degrees and determinants of China's urban residential energy demand and energy rebound effect. The results show that residents' income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents' income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China. [ABSTRACT FROM AUTHOR]

Understanding the rapidly rising demand for energy in China is essential to efforts to reduce the country's energy use and environmental damage. In response to rising incomes and changing prices and demographics, household use of various fuels, electricity and gasoline has changed dramatically in China. In this paper, we estimate both income and price elasticities for various energy types using Chinese urban household micro-data collected by National bureau of Statistics, by applying a two-stage budgeting AIDS model. We find that total energy is price and income inelastic for all income groups after accounting for demographic and regional effects. Our estimated electricity price elasticity ranges from -0.49 to -0.57, gas price elasticity ranges from -0.46 to -0.94, and gasoline price elasticity ranges from -0.85 to -0.94. Income elasticity for various energy types range from 0.57 to 0.94. Demand for coal is most price and income elastic among the poor, whereas gasoline demand is elastic for the rich. [ABSTRACT FROM AUTHOR]

To analyze the operational efficiency of Chinese power sector at the provincial level, this paper studies the convergence of technical efficiency and productivity growth of electricity across 29 Chinese provinces during the period 1996-2008 using several convergence models. Depending on the model being employed, we find evidence of convergence of operational efficiency towards either a national steady state or towards their own steady states, with the latter process occurring more rapidly. In essence, our study provides evidence of negative effects of government intervention. Additionally, we use the nonparametric distribution dynamics approach to analyze intra-distributional dynamics of technical efficiency and productivity. We find some support for productivity convergence while technical efficiency does not converge for provinces with relatively low levels. We discuss policy implementations based on our model results and highlight several aspects for policy making in the power sector reforms currently being undertaken. [ABSTRACT FROM AUTHOR]

As part of the country's efforts to achieve green development, China implemented a mandatory energy intensity reduction target in its 11th "Five-Year Plan (FYP)" in 2006, and then began to roll out a series of relevant measures. However, existing studies have paid little attention to the actual effects of China's energy intensity constraint policy (EICP). In this paper, using panel data from China's 36 industrial sub-sectors covering the years from 2001 to 2014, we adopt the difference-in-differences (DID) method to investigate for the first time the EICP's (marginal) effect on total factor energy efficiency growth (TFEEG). We also estimate the superposition effect caused by the introduction of a carbon intensity constraint policy (CICP) on TFEEG, through the difference-in-difference-in-differences (DDD) strategy. Finally, using counterfactual, re-grouping and quasi-DID analyses, we conduct a series of robustness tests of the empirical results. The results show that the TFEEG in China's industrial sector experienced an overall declining trend between 2001 and 2014. The implementation of the EICP has had a significantly negative effect on the improvement of the TFEEG of sub-sectors with higher levels of energy intensity. After the implementation of the EICP, the TFEEG rate of these sub-sectors declined by 4.31%, compared to the rate of the other sub-sectors. The results of a series of robustness tests indicate that such a negative effect is credible. The marginal effect in the first two years after the implementation of the EICP was significantly negative, while the superposition effect of the introduction of a CICP on industrial TFEEG remained negative. Thus, the Chinese government should reinforce the implementation of energy-saving policies by introducing additional market-oriented auxiliary policies to propel the green development transformation of China's industrial sector. [ABSTRACT FROM AUTHOR]

In the 2009 Copenhagen Accord, China agreed to slash its carbon intensity (carbon dioxide emissions/GDP) by 40% to 45% from the 2005 level by 2020. We assess whether China can achieve the target under the business-as-usual scenario by forecasting its emissions from energy consumption. Our preferred model shows that China's carbon intensity is projected to decline by only 33%. The results imply that China needs additional mitigation effort to comply with the Copenhagen commitment. The emission growth is more than triple the emission reductions that the European Union and the United States have committed to in the same period. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports published within the issue which include the development of energy economics in China, the status of carbon and renewable energy in the country, and the demand for household energy.

Extending existing studies based on constant structure, we adopt a time-varying approach to study energy consumption and GDP causality for China in a context of industrialization and urbanization. We find that in light of structural change, China's energy consumption is trend-stationary and thus forms no cointegration with GDP. Further, the relationship between energy consumption and GDP is two-way causal and has been decreasing in strength over time. Finally, industrialization and urbanization, especially the former, have limited effects on energy consumption, suggesting the decreasing energy intensities in individual sectors, instead of structure shift between sectors, as the main reason for China's decreasing energy intensity over the years. [ABSTRACT FROM AUTHOR]

We study firm responses to a large-scale energy efficiency program in China, focusing on the quality of reporting and compliance outcomes. Using statistical methods to detect data manipulation in compliance reports, we find evidence that firms deliberately exaggerated performance during the first phase of the program (2006-2010), suggesting the high compliance rate was overstated. In its second phase (2011-2015), the number of firms in the program expanded by an order of magnitude, and the compliance rate decreased. We develop a simple model to show how the observed increase in non-compliance is consistent with reduced misreporting. Statistical tests find no evidence of manipulation in the second phase. Larger firms, especially those not controlled by the state, and firms in cities with relatively low growth were more likely to report non-compliance, which suggests a role for state control and local protectionism in shaping compliance decisions. Based on our findings, we offer several lessons for future program design. [ABSTRACT FROM AUTHOR]

China has set a goal of 20% non-fossil energy in total primary energy consumption by 2030. The decision of where to invest in renewable energy, and to what extent, needs to be considered from a forward-looking perspective. This article presents a power sector optimization model that integrates unit commitment with long-term generation expansion planning framework. Power dispatches at an hourly level are combined with yearly investment decisions. Based on the model, this article analyzes the optimal spatial deployment of renewable energy. The results show that regional differences in non-hydro renewable energy are significant. Approximately 75% should be deployed in the north of China. With the increase of combined heat and power, more renewable energy facilities, especially solar photovoltaic, should be located in the south of China. Inter-regional power transmission is beneficial to onshore wind in resource-rich areas, and could mitigate the conflict between coal-heavy generation mix and renewable energy. [ABSTRACT FROM AUTHOR]

This study examines the energy efficiency transitions in China using provincial data covering the period 2003-2015. Sustainable progress in energy efficiency achievement is beneficial to energy security and the achievement of the Paris Agreement. This article combines the stochastic frontier method with the panel Markov-switching regression to model energy efficiency transitions. The estimated energy efficiency scores show significant regional and provincial heterogeneity. Also, while human capital development, urbanization, and foreign direct investment promote energy efficiency, price and income per capita reduce it. The transition probabilities indicate that the high energy-efficient state is less sustainable, and the movement towards the frontier seems less persistent than movement from the frontier. Thus, it appears that China is not making sustainable progress in energy efficiency. The unsustainable nature of the high energy-efficient state suggests that in China, there are weak energy efficiency efforts and energy efficiency policies lack robustness. [ABSTRACT FROM AUTHOR]

Analyzes the energy consumption behavior in China. Use of a cointegration and vector error-correction model; Methodology and model estimation; Evaluation of forecasts; Four major energy inputs.

Explores the relationship between energy consumption and economic activity in China. Use of province-level cross-section data; Income elasticity of energy consumption; Impact of exporting energy and heavy industry.