Energy Efficiency In China Research Articles

Assessing energy efficiency, regional disparities in production technology, and factors influencing total factor energy productivity change in the agricultural sector of China

Efficiently utilizing the energy resources in the agriculture sector to produce more agricultural output with minimum environmental degradation is a shared global challenge. The Chinese government has introduced various policies aimed at enhancing energy efficiency (EE) and total factor energy productivity (TFEP) while addressing regional technological disparities in the agricultural sector. This study utilized DEA Super-SBM, Meta frontier Analysis, and the Malmquist–Luenberger index to assess energy efficiency, changes in total factor energy productivity, and the regional technology gap ratio (TGR) across 30 provinces in mainland China and three distinct regions during the period from 2000 to 2020. The findings reveal that the average EE in China's agricultural sector is 0.8492, indicating that, on average, there is a 15.08 % potential for improvement in EE growth within the sector. Qinghai (1.5828), Shanghai (1.3716), and Hainan (1.3582) are found to be the top 3 performers with the highest EE levels. The Eastern region demonstrates high excellence in EE, with a value of 1.0532. The TGR value of Zhejiang indicates the superior production technology utilized in the agriculture sector to utilize energy resources efficiently. Except for Zhejiang, the TGR of Liaoning, Jiangsu, Shanghai, Guangdong, Ningxia, and Hainan is above 0.96 and near 1, indicating superior production technology in the agriculture sector of China. The Technology Gap Ratio (TGR) of China's eastern region is superior to that of the central and western regions, consistently approaching 1. This suggests that the eastern provinces possess more advanced agricultural technologies, allowing them to optimize resource utilization for maximum output. The Malmquist–Luenberger index (MLI) score of 1.103 indicates a 10.3 % growth in the total factor energy productivity of China's agricultural sector. Further analysis reveals that this growth is primarily driven by technological change (TC), with a TC value of 1.080 surpassing the efficiency change (EC) value of 1.028. Among the three agricultural regions, the eastern region exhibits the highest total factor energy productivity. Specifically, Zhejiang (1.23), Shanghai (1.197), Liaoning (1.184), and Hebei (1.147) are identified as the top performers in total factor energy productivity growth in China's agricultural sector. Additionally, the Kruskal-Wallis test confirmed statistically significant differences in EE and TGR among the three regions.

The convergence of total-factor energy efficiency across Chinese cities: A distribution dynamics approach

Improving energy efficiency is considered the most direct route to reducing carbon emissions on a massive scale. To examine the long-run trend of China's energy efficiency, this paper employs a distribution dynamics approach to analyze the convergence of total-factor energy efficiency (TFEE) across 286 Chinese cities between 2002 and 2014. The result suggests the existence of convergence, which comes more from the efficiency declines in the high TFEE cities rather than the efficiency gains in the low TFEE cities. Despite the fact that a few cities have performed well in energy efficiency, the majority of cities have converged to a low-efficiency point. Further analyses show that the inefficiency was attributed to inefficient energy use in small- and medium-sized cities. Our analysis provides strong scientific support for China's ongoing energy conservation and environmental protection policies.

Practical effects of carbon emissions trading system on energy efficiency

The carbon emissions trading system (CETS) is a helpful policy instrument for separating carbon emissions from economic expansion, and it significantly impacts energy efficiency (EE). This study uses 30 Chinese provinces from 2007 to 2020 as its research samples, and classifies energy efficiency into single-factor energy efficiency (SFE) and total-factor energy efficiency (TFE), using the difference-in-differences model to examine the effect and mechanism of the CETS on EE. As an additional tool to assess the efficacy of the CETS, the corresponding evolution of the rebound effect of energy-related carbon emissions (RECE) is also calculated. This study shows that the CETS can significantly improve EE in China's pilot provinces. The influence mechanism indicates that the effect of the CETS on EE is influenced by the level of government governance, green innovation, and industrial structure optimization. Further study finds that after the CETS was carried out, the RECE in pilot provinces was higher than that in non-pilot provinces, and 31.4% of carbon emissions reduced by EE improvement rebounded. Therefore, the CETS has yet to realize its full carbon reduction potential. The study offers specific policy proposals for the enhancement of China's CETS in light of the aforementioned findings.

Modelling the role of industrial structure adjustment on China's energy efficiency: Insights from technology innovation

Due to uncoordinated economic progress, China's regional gap concerning energy efficiency (EE) is noticeable. However, industrial structure adjustments can be reorganized as a promising way to prioritize the green and low-carbon transition. Aiming to understand how regional EE can be achieved through industrial structure adjustment, this study empirically investigates the role of industrial structure adjustment in increasing interprovincial EE from a technology innovation perspective. Unlike previous studies, the primary analytical framework is anchored on a spatio-temporal domain. Specifically, we observe that industrial structure rationalization and industrial structure adjustment not only directly influence local EE but also indirectly exert a positive effect on EE improvements in adjacent provinces. The same implications are also valid when addressing the EE-ICT nexus. Further mechanism analysis shows that technology innovation positively moderates industrial structure adjustment to EE enhancements, with regional heterogeneity being all-important. We find that the non-linear effect of industrial structure adjustment on EE is conditioned by technology innovation. Increasing R&D input intensity could significantly change the impacts of industrial structure adjustments on EE efficiency.

Exploring resource endowment and human capital impact on regional energy efficiency in China in the context of COP26

The 26th Conference of the Parties (COP26) noted that one of the most effective and a rapid pathway to carbon reduction is to improve energy efficiency (EF). Therefore, the improvement of energy efficiency has become the focus of attention of many countries. This study measured China's regional EF by selecting data from 30 regions (excluding Hong Kong, Macau, Taiwan and Tibet) in China from 2008 to 2021 and explored human capital and resource endowment's impact on EF. The study fount that (1) the average value of national EF was 0.773 and the EF showed an upward trend over the study period; its value was the highest in eastern and lowest in western regions; (2) resource endowment can inhibit EF in three major regions and across the whole country, which verifies the existence of the resource curse hypothesis (with the exception of the for the eastern region); human capital has a positive effect on EF, and it is most significant in the eastern region, while the central and western regions have a smaller impact on EF; (3) the relationship between environmental regulations and EF shows a ‘U’ shape in all regions; foreign direct investment can significantly improve EF in all regions and it is most significant in the central region; the industrial structure can promote EF, with the exception of the eastern region. Urbanization can improve EF in the national and eastern regions, but it inhibits EF in the central and western regions. The study provides valuable implications for the promotion of EF in China.

Analysis on the Influence of Industrial Structure on Energy Efficiency in China: Based on the Spatial Econometric Model.

Compared with other developed countries, China's energy efficiency level is not optimal, but it has indeed made remarkable achievements in its long-term development, mainly due to efforts targeting the adjustment of industrial structure. This research, therefore, uses a spatial econometric model to study the energy efficiency of 30 provinces in China with data from the panel from 2004 to 2019, and studies the impact of industrial structure on energy efficiency from the overall sample, for different time periods and across the three regional scales of eastern, central and western regions. The following conclusions are drawn from the empirical analysis. (1) China's energy efficiency indicators have significant geographic spatial correlation and regional spatial structure differences. (2) In the full sample condition, the industrial structure has a positive impact on the energy efficiency of China's provinces, but it also shows a significant negative spatial spillover effect. (3) Industrial structure was positively correlated with energy efficiency from 2004 to 2011. (4) The industrial structure in the east promotes energy efficiency, while the industrial structure in the central and western regions inhibits energy efficiency improvement. (5) Government intervention and scientific and technological innovation have had a spatial impact on energy efficiency in China's provinces, while marketization and the average income of residents have had no significant impact.

The influence of sustainable energy demands on energy efficiency: Evidence from China

Recently, there has been a high level of energy demand worldwide, which has piqued regulators and researchers’ interest in producing efficient energy. Therefore, this research investigates the impact of multiple energy demands on China's energy efficiency (renewable energy production). The researchers use secondary data extracted from World Development Indicators for the period 1986 to 2019. They use time series analysis techniques, such as the ADF test for stationarity, the ARDL model to evaluate the association between the variables, and the Granger causality test to evaluate the directional nexus amongst the variables. The findings show that multiple energy demands have a positive association with energy efficiency in China. Several implications and recommendations are made by the study to facilitate future research and regulation.

The role of different paths of technological progress in improving China's energy efficiency

Improving energy efficiency is one of the most effective ways to address environmental constraints and achieve high-quality economic development. The existing literature suggests that technological progress has an important impact on energy efficiency, but ignores the role of different paths of technological progress. Herein, the impact of different technological progress paths on energy efficiency was analyzed using the dynamic panel data model and the threshold model based on the energy efficiency measurement using the Meta-frontier and Nonradial Directional Distance Function model. The findings of this study were as follows: (1) During the study sample period, a fluctuating upward trend was observed in China's energy efficiency, and there were significant differences in energy efficiency in different regions of China. (2) The energy efficiency in China could be significantly improved by domestic innovation and regional technology diffusion. Even though the imported technologies do not play a significant role in promoting energy efficiency and have no positive effect on the improvement of energy efficiency from the perspective of domestic technology absorption or foreign technology absorption. (3) The eastern and central regions of China improve their energy efficiency through domestic innovation. However, none of the technological progress paths in the western and low-energy-efficiency regions have played a positive role in promoting energy efficiency. (4) The effect of promoting domestic innovation and regional technology diffusion on energy efficiency is gradually increasing with human capital improvement, and the restriction of foreign technology import on energy efficiency has obviously decreased. In a nutshell, different paths of technological progress have differential effects on energy efficiency improvements. Based on the above results, this paper makes some targeted policy recommendations on the choice of technological progress paths to improve energy efficiency in different regions of China.

Influence of air quality ranking on China's energy efficiency: spatial difference-in-differences model with multiple time periods.

Exploring the impact of air quality ranking on energy efficiency and its spatial spillovers will help improve the pollution and carbon reduction effects of environmental governance policies. Based on the panel data of 285 cities at or above prefecture level in China during 2009-2019, this study pioneers in adopting difference-in-differences (DID) model with multiple time periods, spatial DID (SDID) model with multiple time periods, and mediating effect to explore the direct influence of ranking on China's energy efficiency, as well as its spatial effect and influence mechanism. Results show that air quality ranking is of significant positive impact on energy efficiency, proved by parallel trend hypothesis, placebo control, and policy heterogeneity. With spatial effect considered, such impact still exists, and ranking of the experimental group has significant positive spatial spillover effect on efficiency of the control group, meaning the ranking also promotes the efficiency of nearby cities in control groups via spatial spillover effect. In addition, air quality ranking greatly elevates energy efficiency via industrial structure and technological innovation, the mechanism of which is of significant positive spatial spillover effect. Based on the above results, some policy recommendations on environmental competition policy, industrial structure adjustment, and low-carbon applicable technology promotion were proposed to promote the energy efficiency of China.

Measuring China’s energy efficiency by considering forest carbon sequestration and applying a meta dynamic non-radial directional distance function

China is the world's largest consumer of fossil energy and CO2 emitter, as well as the country with the fastest growth of forest cover. While the China government regards forest carbon sequestration as one of the paths to achieve carbon neutrality, the existing research on energy efficiency measurement in China rarely takes it into account. Thus, this research introduces forest carbon sequestration as a new desirable output variable and applies a meta dynamic non-radial directional distance function to measure China's energy efficiency from 2010 to 2019, which effectively improves the accuracy of the assessment while providing dynamic comparison results. Different from previous studies, findings shows that, with the improvement of forest carbon sequestration, the technology gap ratio between the central and western regions and the eastern region has narrowed from 0.4 to 0.23 and 0.36 to 0.2 on average in 2015–2019. In addition, this study obtains the room for improvement of China's provinces in forest carbon sequestration and puts forward policy suggestions for its long-term sustainable development of forest carbon sequestration, including establishing responsibility objectives of annual minimum growth of forest carbon sequestration by provinces, accelerating the construction of forest carbon sequestration trading system, and developing urban green space carbon sequestration.

The impact of the anti-corruption campaign on energy efficiency: Evidence from prefecture-level cities in China

China’s development has been accompanied by serious corruption and environmental pollution. Corruption is particularly prevalent in the energy sector, where it can bring very substantial benefits. However, corruption in the energy sector can lead to serious misallocation of energy, resulting in wasteful and inefficient use of energy. With the rise of the anti-corruption campaign, there is an urgent need to explore the impact of the anti-corruption campaign (ACC) on energy efficiency (EE). This paper investigates whether and how the ACC affects EE in China. Leveraging a staggered difference-in-differences (DID) model, we estimate the causal effect of the ACC in China on EE. Our results indicate that the ACC significantly improves EE, which is robust to a battery of robustness tests, such as parallel trend test, placebo test, excluding other policies, and substituting the explained variable. The positive relationship is correlated to reducing rent-seeking behavior, promoting innovation capacities, and upgrading industrial structure within a city. The heterogeneous results suggest that the effect of the ACC on EE improvement is more pronounced in big cities, cities located in the central, cities with high fiscal expenditures and low R&D expenditures. The results of this paper show that we must be tenacious in the anti-corruption campaign to establish a clean government and increase energy efficiency in order to achieve sustainable development.

The underlying drivers of energy efficiency: a spatial econometric analysis.

It is theoretical and practical to investigate the causes and effects of energy efficiency. However, few empirical studies have been conducted to examine the potential underlying drivers of energy efficiency from a spatial perspective. In light of this, we combined the data envelopment analysis and spatial econometric analysis to explore the driving factors of energy efficiency. The results show that China's energy efficiency shows significant characteristics of regional disparity and spatial agglomeration; that is, high energy efficiency has presented a benefit agglomeration, while low energy efficiency has presented a disadvantage agglomeration. The empirical results indicate that technological progress, trade openness, and foreign direct investment have effectively improved energy efficiency, while energy structure and industrial structure adversely affect energy efficiency. Furthermore, technological progress, trade openness, energy structure, foreign direct investment, and industrial structure exert different influences on energy efficiency, but their potential underlying mechanisms vary essentially across regions. Thus, using a spatial econometric model allowing for spatial dependence in analyzing drivers of energy efficiency is urgent and necessary for promulgating energy policies.

A step towards green economic policy framework: role of renewable energy and climate risk for green economic recovery

According to the World Bank, energy efficiency is a critical facilitator of most Sustainable Development Goals. Its contribution to CO2 emission reduction is astounding. Environmentalists have recently emphasized the essential need to determine energy efficiency causes. This research broadens the debate's horizons by proposing additional possible energy efficiency factors using data from the Chinese economy. From 1990 to 2020, we examined the influence of investment in renewable energy resources, financial inclusion, industrial production, and trade openness on China's energy efficiency and climate risk. Additionally, this study is added to the literature by examining the causal relationships between variables while considering the temporal dimension. The findings indicate that industrial production, financial inclusion, public R&D on renewable energy, and trade openness contribute significantly to China's energy efficiency and climate risk. All other factors, except industrial production, are positively associated with energy efficiency. The path of causality is established from energy efficiency and climate risk to financial inclusion, industrial production, renewable energy, public research and development budgets, and trade openness. According to the findings, changes in energy performance have frequency-changing impacts on all variables. Policymakers believe that the financial system must be strengthened since this will significantly influence renewable energy.

China's energy efficiency improvement on account of the development of wind and solar power: Applying a dynamic non-radial directional distance function

China is developing wind energy and solar power as the main channels to deal with climate warming and has put forward the goal of achieving peak carbon emissions by 2030 and carbon neutralization by 2060. Previous studies evaluating the nation energy efficiency rarely consider the impact of wind and solar power. Thus, different from past literature, this research introduces Carbon Emission Reduction Capacity (CERC) by wind and solar power as a new output variable and applies a dynamic non-radial directional distance function to evaluate China's energy efficiency from 2011 to 2019. The empirical results show that northwest provinces with their high proportion of wind and solar power present better energy performance, while some eastern and central provinces with high efficiency as seen in previous study have greater room for improvement of wind and solar power. It is suggested that the China government formulate more flexible policies to support the sustainable development of wind and solar power, so as to reduce the consumption of fossil energy and cope with climate warming.

Revisiting the nexus between financial agglomeration and energy efficiency: A spatial spillover approach

ABSTRACT Financial agglomeration (FA) may play an essential role in enhancing energy efficiency (EE) and, thus, is important from both theoretical and empirical viewpoints. However, few studies have investigated the causal nonlinear relationship between FA and EE. Hence, we first extend the novel ray slacks-based measure with global technology to evaluate the urban EE in China during 2003–2018. Next, we reexamine the nonlinear causality of FA on EE and then explore the underlying impact mechanism. The empirical results show that China’s urban EE is generally relatively low with distinct patterns of regional differences. Moreover, we find that the causal relationship between FA and EE follows an inverted U-shaped function rather than a linear one. FA promotes the improvement of EE only up to a certain threshold point, after which it reverses into an inhibitory effect. A further analysis based on the two-regime spatial Durbin panel model suggests that FA can indeed improve the EE of surrounding cities through positive externalities when the degree of FA in focal cities is not substantially greater than that in surrounding cities. However, when financial resources absorbed in certain focal cities become increasingly higher than that in most surrounding cities, the positive spillover effect would gradually disappear and even reverse into an undesirable siphon, thereby inhibiting the improvement of overall EE. These findings provide new insights for understanding the role of FA in sustainable development.

Fiscal decentralisation in China: Is the guarantee of improving energy efficiency?

China's fiscal decentralisation system has led to the increase of local governments' independent decision-making power, which promotes to the optimisation of industrial structure and has an impact on energy efficiency. This study analyzes the social network of energy efficiency based on gravity model, and uses dynamic SAR (Spatial Auto-Regressive) model to test the impact path of Fiscal Decentralisation (FD) on China's Energy Efficiency (EE). Firstly, the results show that China's energy efficiency decreases from Eastern to Western regions, but the energy gap between the three areas has gradually narrowed in recent years, and there are great differences in the distribution and trend of energy efficiency between the secondary and tertiary industries. Secondly, social network analysis highlights that the energy efficiency of each province presents a complex and multi-threaded spatial spillover relationship. It slowly radiates from the economically developed Eastern coastal provinces to the surrounding areas, driving underdeveloped regions. Then, fiscal decentralisation positively impacts energy efficiency by upgrading industrial structure (IS), which has also been verified by the Eastern, Central and Western regions. The theoretical model supports the view that when environmental governance is included in the utility function of local government, officials may invest more financial funds in environmental improvement. Finally, the heterogeneity analysis shows that fiscal decentralisation in the Eastern region has the most significant effect on energy efficiency while the Western region has the least. Governments should plan differentiated green development policies to continuously strengthen the supervision and management of industrial energy consumption in the backward areas.

Analysis of China's energy efficiency and influencing factors under carbon peaking and carbon neutrality goals

Nowadays, China's economy and energy structure are deeply adjusting to the direction of low-carbonization and non-carbonization with unprecedented efforts. This paper considered carbon emissions and energy endowments, adopted SBM-Undesirable model and spatial Durbin model to calculate the energy efficiency of 30 provinces and municipalities in China from 2015 to 2019 and analyze the direct effect, indirect effect and total effect on energy efficiency of 7 variables. Empirical results show that: Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. The valuable conclusions obtained in this study deepens the insights about the influencing factors of China's energy efficiency under the constraints of carbon emission and energy endowment.

Quantifying the spatiotemporal characteristics of China's energy efficiency and its driving factors: A Super-RSBM and Geodetector analysis

Improving energy efficiency is a key component of ensuring energy security and realizing “dual carbon” goals for China. This study introduced a ray slack-based model (RSBM) and Super-RSBM, which may distinguish weak and strong disposability to provide a more comprehensive and reliable insight compared with traditional models, to measure China's energy efficiency during 2000–2017. Its spatiotemporal characteristics were outlined elaborately by spatial autocorrelation models and Theil index, and its driving factors were probed by Geodetector model instead of econometric models to minimize fitting bias. The results showed that China's energy efficiency remained a medium level over time, and experienced a slightly declining first and then fluctuating. Meanwhile, it maintained a distribution pattern of higher energy efficiency in the eastern region as well as Mongolian and Tibetan Plateau, while lower in the western region and most of North China Plain. It had great inequality across provinces and regions. Specifically, the number of LL-type provinces decreased while provinces of HH-type were always rare. The national inequality of energy efficiency was mainly derived from the intraregional difference. Furthermore, China's energy efficiency was tightly associated with the economic development and urbanization level. It showed a loose connection with environmental regulation and clean production proportion. All pairs of studied factors had mutually reinforcing effects on energy efficiency. These results could serve as strong scientific supports to formulate policies targeted towards energy conservation and emission reduction.

Energy-saving potential of deeply retrofitting building enclosures of traditional courtyard houses – A case study in the Chinese Hot-Summer-Cold-Winter zone

It is increasingly believed that energy retrofits are a protection tool to preserve cultural heritage for future generations. However, few studies are available regarding the deep retrofits of traditional courtyard houses in the Chinese Hot-Summer-Cold-Winter zone, although the winter conditions in these buildings are very uncomfortable based on existing studies. Besides, few studies analyzed the actual energy performance of still-occupied traditional buildings in this region. Therefore, this study investigated the energy-saving potential of deeply retrofitting the building enclosures of a traditional courtyard house in Tongren in southern China. The investigation was based on calibrated hygrothermal simulation with WUFI®Plus applying the multi-zone airflow modeling. For the calibration, short-term monitoring (two weeks) was conducted in winter and measured the air temperature, relative humidity, and heating energy consumption. The calibration showed satisfactory results by assessing the Normalized-Mean-Bias-Error, the Coefficient of Variation of Root-Mean-Square Error, and the Coefficient of determination. In contrast, the application of Goodness of Fit shows poorer performance and requires further discussion for short monitoring periods. According to this study, improving the U-values of building envelopes to meet at least the current Chinese energy-efficiency standard can reduce more than 56% energy demand for heating and cooling, with an estimated payback time of 2.5 years for the material cost. With growing expectations of building occupants on indoor thermal comfort, the improvement of the energy performance of traditional buildings will become more critical for their long-term preservation and should be implemented in China's energy efficiency policies and initiatives in the future.

Energy efficiency cycle and the export-oriented economic growth style in China

Few studies addressed the relationship between the energy efficiency cycle and the export-oriented economic growth style, and our work aimed to contribute this research in the literature using China's dataset during 1985–2018. Results of the autoregressive-distributed-lag model there were two cycles in China's energy efficiency, and the first ranged from 1989 to 2002 while the second was over the period 2003–2012. Meanwhile, the estimations suggested that a 1% export increase was linked to a 0.107% increase in energy efficiency in the long run. However, the export was significantly and negatively associated with the short-run fluctuation of energy efficiency. As a result, the statistical simulation confirmed that export would raise the fluctuation range of energy efficiency.