• Energy Research

The Chinese households that make up approximately a quarter of world households are facing a residential power tariff reform in which a rising block tariff structure will be implemented, and this tariff mechanism is widely used around the world. The basic principle of the structure is to assign a higher price for higher income consumers with low price elasticity of power demand. To capture the non-linear effects of price and income on elasticities, we set up a translog demand model. The empirical findings indicate that the higher income consumers are less sensitive than those with lower income to price changes. We further put forward three proposals of Chinese residential electricity tariffs. Compared to a flat tariff, the reasonable block tariff structure generates more efficient allocation of cross-subsidies, better incentives for raising the efficiency of electricity usage and reducing emissions from power generation, which also supports the living standards of low income households.

Abstract Analysis of CO2 emission has attracted more attention due to increasing environmental awareness. As a pillar of the national economy, the CO2 emissions of the metallurgical industry continually increased during 2000–2015 and reached around 3208.65 million tons in 2015. Thus, research on the CO2 emission performance of the metallurgical industry is significant for achieving binding emission reduction targets in China's 13th Five-Year Plan as well as constructing clean and low carbon energy system based on the directives of the 19th CPC National Congress. Taking regional heterogeneity into consideration, we construct a Metafrontier Malmquist CO2 Emissions Performance Index (MMCPI) to conducts a multi-dimensional analysis of the CO2 emissions performance in metallurgical industry of China, focusing on the CO2 emission efficiency, the main influencing factors of carbon performance and CO2 emission reduction potentials. Based on the aforementioned analysis, the paper finds that technological progress change was the main factor contributing to the improvement of the CO2 emissions efficiency of the metallurgical industry. Under the meta-frontier, Central and Western China still have a CO2 emissions reduction potential of 75.3% and 81.1% correspondingly. Under the group-frontier, the lowest reduction potential in Eastern, Central and Western China is in Jiangsu, Hubei and Chongqing respectively.

Abstract PM 2.5 emissions not only have serious adverse health effects, but also impede transportation activities, especially in air and highway transport. As a result, PM 2.5 emissions have become a public policy concern in China in recent years. Currently, the vast majority of existing researches on PM 2.5 are based on natural science perspective. Very few economic studies on the subject have been conducted with linear models. This paper adopts provincial panel data from 2001 to 2012, and uses the STIRPAT model and nonparametric additive regression models to examine the key driving forces of PM 2.5 emissions in China. The results show that the nonlinear effect of economic growth on PM 2.5 emissions is consistent with the Environmental Kuznets Curve (EKC) hypothesis. The nonlinear impact of urbanization exhibits an inverted “U-shaped” pattern due to the rapid development of urban real estate in the early stages and the strengthening of environmental protection measures in the latter stage. Coal consumption follows an inverted “U-shaped” relationship with PM 2.5 emissions owing to massive coal consumption at the beginning and efforts to optimize the energy structure as well as technological progress in clean energy in the latter stages. The nonlinear inverted “U-shaped” impact of private vehicles may be due to the different roles of scale, structural and technical effects at different stages. However, energy efficiency improvement follows a positive “U-shaped” pattern in relation to PM 2.5 emissions because of differences in the scale of the economy and the speed of technological progress at different times. As a result, the differential dynamic effects of the driving forces of PM 2.5 emissions at different times should be taken into consideration when initiating policies to reduce PM 2.5 emissions in China.

Abstract This study attempts to contribute to the literature on stock markets and energy prices by examining the dynamic volatility and volatility transmission between oil and Ghanaian stock market returns in a multivariate setting using the recently developed VAR–GARCH, VAR–AGARCH and DCC–GARCH frameworks. In turn, the models' results are used to compute and analyze the optimal weights and hedge ratios for oil-stock portfolio holdings. For comparison purposes and to put the paper more in the perspective of West Africa, the Nigerian stock market is also included in the analysis. Our findings point to the existence of significant volatility spillover and interdependence between oil and the two stock market returns. While spillover effects are stronger for Nigeria, the transmission of volatility is much more apparent from oil to stock than from stock to oil in the case of Ghana. Also, the study demonstrates evidence of short-term predictability in oil and stock price changes through time and reveals that conditional volatility changes more rapidly as result of substantial effects of past volatility rather than past news/shocks for all market returns. Moreover, we show that there is a slightly more effective hedge in the two stock markets under the DCC–GARCH framework (our preferred model) compared to the other two models, although hedging effectiveness is much greater for Ghana. On the whole, our findings for optimal hedge ratios are consistent with other studies and particularly the view that oil assets should be an integral part of a diversified portfolio of stocks and suggest that a better understanding of volatility links is crucial for portfolio management in the presence of oil price risk. Finally, the existence of multivariate asymmetric effects and dynamic conditional correlations as revealed by the VAR–AGARCH and DCC–GARCH models make it clear that the assumptions of symmetric effects and constant conditional correlations are not supported empirically.

Abstract Electricity plays an important role in economic and social development. China’s coal-based power generation structure emits a large quantity of greenhouse gases. Improving electricity consumption efficiency is an important measure for energy conservation and emission mitigation. With this in mind, this study analyzes the influencing factors of electricity consumption and estimates the electricity consumption efficiency by considering the role of structural changes in China’s 30 provinces over the period 2006–2015. The following findings are obtained: (1) Per capita income, urbanization, population, the proportion of secondary industry, and electricity price have significant impacts on electricity consumption. (2) The optimization of industrial structure is conducive for improving the electricity consumption efficiency and has a significant impact, while the improvement in electrification level will lead to a decrease in efficiency score during the study period. (3) There are significant differences in electricity consumption efficiency with a range from 0.372 to 1.000, depending on different model specifications, regions, and years. This paper sheds new light on the electricity demand and its efficiency. Based on these findings, this paper proposes some targeted policy recommendations.

Abstract Energy resource depletion and environmental degradation have become big challenges for China's sustainable development. Energy efficiency improvement is usually regarded as an major pathway for reducing the pressure on energy and the environment. However, this would be undermined by the rebound effect, because the rebound effect would partially or even totally offset the anticipated of efficiency improvement. Evidence of the rebound effect has important implications for the economic, resource and environmental consequences of improving energy efficiency, as well as enables policy makers to take informed decisions on energy and environmental issues. In this paper, we incorporate the endogenous energy efficiency into the model specification of rebound effect, and build a unified comprehensive framework for analyzing rebound effect and related issues. We applied this framework to conduct empirical analysis and comparison of heavy and light industries, considering heterogeneity across sub-industries. Furthermore, this paper goes beyond simple estimation of rebound effect, and takes additional effort to highlight the policy application via combining energy subsidies and technological progress with rebound effect.

Despite reforms, China still largely applies the cost plus pricing mechanism for the energy sector. Government administrative energy pricing leads to energy price distortions, which could result in not only the excessive and wasteful energy consumption, but also environmental deterioration, thereby undermining energy conservation and emission abatement. Using fossil-fuel subsidies as a proxy for the level of energy price distortions, this paper estimates the subsidy of 22 Chinese departments during the period 2006–2010, and adopts the price-gap approach to analyze the impacts of subsidy removal on energy consumption and CO2 emissions for the various sectors and energy types. The results demonstrate that removing energy subsidies would reduce energy consumption and emissions by 3.77% and 2.85%, respectively, but the effects vary across sectors. The transport, storage and post sector and the electricity, gas and water supply sector are much more affected by energy subsidies removal than other sectors. With respect to energy types, fuel oil and natural gas are sensitive to subsidies, indicating the magnitude of their consumption. This suggests that removing subsidies on these fuel types could significantly reduce CO2 emissions. Finally, we comprehensively discuss relevant policy issues on energy price formation reform.

China has committed to achieving carbon neutrality by 2060, primarily focusing on reducing carbon intensity. Understanding the regional embodied carbon emissions is critical for managing carbon efficiency and carbon equity in this process. Using the input-output and SBM-DEA models, this article first calculates China's regional embodied carbon emissions. The results reveal substantial carbon transfers between China's different regions. Therefore, designing reduction pathways solely based on production-based carbon emissions raises fairness concerns. To address this, this article employs the SBM-DEA model to calculate the regional reduction potential and marginal abatement costs using the regional embodied carbon emissions and optimize China's pathways of regional carbon emission reduction. The new pathways consider consumption-based reduction potential, marginal abatement cost, and reduction equity, and are all in line with China's carbon reduction target. These schemes are of practical significance for China to develop a more efficient and equitable regional emission reduction plan.