Total-factor Energy Efficiency Research Articles

Can Environmental Information Disclosure Improve Energy Efficiency in Manufacturing? Evidence from Chinese Enterprises

Improving the energy efficiency of enterprises is one of the key means to solve the problem of energy shortage. It is of great significance to investigate how environmental information disclosure (EDI) promotes the green total factor energy efficiency (GTFEE) of enterprises. Based on this, this study calculates the GTFEE of enterprises by combining the database of Chinese manufacturing and the pollutant emission of industrial enterprises and investigates the impact of EDI on the GTFEE of manufacturing industries by using a difference-in-difference model. The following is found: (1) EDI can significantly promote the manufacturing enterprises’ GTFEE, and the results are still valid after a series of robustness tests; (2) Mechanism analysis shows that EDI can improve the GTFEE of manufacturing enterprises by promoting technological innovation and optimizing energy structure; (3) The heterogeneity analysis shows that EID is more positive on firms’ GTFEE in the eastern than western regions. The positive impact is greater for non-state-owned, low-energy consumption, export, and polluting enterprises. The findings of this paper provide a theoretical basis and practical enlightenment for the government to promote the green development transformation of enterprises.

Catalyst or Obstacle? Green innovation and total factor energy efficiency

Green innovation possesses dual externalities of “innovation” and “environmental protection”, and enhancing energy efficiency serves as a crucial means to promote high-quality economic development. Building upon the energy rebound effect, we use the balanced panel data of cities at prefecture level and above in China from 2008 to 2018 to explore the impact of urban green innovation on total factor energy efficiency (TFEE). The findings of this study indicate that, firstly, the impact of green innovation on TFEE exhibits a positive U-shaped pattern, characterized by initial suppression followed by subsequent promotion. This conclusion remains robust after undergoing a series of rigorous robustness tests. Second, high-quality green innovation is found to reach the turning point more quickly, implying that substantial green innovation can cross the turning point in smaller quantities. Thirdly, on the whole, in comparison to non-resource-based cities, resource-based cities are capable of reaching the turning point at an earlier stage. Finally, the new energy demonstration cities have not yet reached the turning point, while the non-new energy demonstration cities have crossed the turning point. This study contributes novel insights into the relationship between green innovation and TFEE, which holds significant implications for the formulation and implementation of sustainable development policies.

Government digital transformation, resource curse and green total factor energy efficiency in Chinese cities

In the age of digitalization, Government Digital Transformation (GDD) stands out as a critical gauge of a nation's modernization drive. It reflects the extent of modernization within the governance framework and acts as a central catalyst for improving governance efficiency and the overall modernity of the system. Against this backdrop, this study empirically investigates the impact of GDD on green total factor energy efficiency (GTFEE) from 2011 to 2020, focusing on prefecture-level cities in China. Using a two-way fixed-effects model, we analyze how GDD influences GTFEE. Additionally, we explore the mediating effect and threshold models to elucidate the mechanisms underlying the resource curse (RC). The findings of the study are as follows: first, GDD has a promoting effect on GTFEE; second, the promoting effect of GDD on GTFEE is more obvious in southern cities and fourth-tier cities; third, the RC plays a mediating effect in the relationship between GDD and GTFEE, specifically, GDD promotes GTFEE by suppressing the RC effect and then promotes GTFEE; fourth, the present study also identifies a RC threshold effect; when RC < 0.5127, the energy efficiency promotion effect of GDD is relatively limited, while when RC ≥ 0.5127, the promotion effect of GDD on GTFEE is significantly enhanced. These findings are of great value for understanding and optimizing the strategic significance of GDD in enhancing GTFEE. They provide a scientific basis and directional guidance for formulating and implementing related policies.

Does Korea's carbon emissions trading scheme enhance efficiency for sustainable energy and utilities?

A carbon emissions trading scheme (ETS) should theoretically increase investment in sustainable energy and utilities, promoting energy efficiency in line with sustainable development and energy transition goals. However, whether Korea's ETS improves or impairs energy efficiency for sustainable energy and utilities is disputed. This study addresses this debate, using panel data from 16 sectors in Korea from 2011 to 2020 and employing a dynamic difference-in-differences (DID) method to estimate the effect of Korea's ETS on total factor energy efficiency and its influencing mechanisms. The main findings are as follows. First, while the effect appeared statistically insignificant in the analyses of the industry as a whole, improving energy efficiency demonstrated a moderate effect for the agriculture industry in terms of research and development investment, fixed assets, and operating income when performing heterogeneity and moderation effect analyses. Second, a company's production dependence on labour is unfavourable to improving energy efficiency through ETS. Lastly, the adverse impact of labour dependence is more prominently observed in light industries, particularly in durable goods and agricultural sub-sectors. Therefore, this reaffirms that the key to increasing energy efficiency is to adjust Korea's ETS flexibly, considering the characteristics of each industry.

Research on total factor energy efficiency in western China based on the three-stage DEA-Tobit model.

As an essential material basis and power source for economic and social development, Western China's low energy use efficiency has hindered its sustainable economic development. This study aims to evaluate the total factor energy efficiency of the region and identify its influencing factors. A three-stage DEA model was used to measure the efficiency of 11 provinces from 2006 to 2021, and the Tobit model was employed to investigate internal factors. The findings show that (i) external environmental factors and stochastic perturbations have a significant impact on TFEE in the western region, overestimating integrated efficiency and scale efficiency and underestimating pure technical efficiency. (ii) the study of external influencing factors finds that the level of economic development increases input redundancy; the industrial structure increases capital input and labor input redundancy while decreasing energy input redundancy; and the energy consumption structure increases capital input and energy input redundancy while decreasing labor input redundancy. (iii) the study of internal influencing factors finds that the level of scientific and technological innovation, the level of openness to the outside world, and the TFEE have a positive correlation. In contrast, the intensity of environmental regulation has a negative correlation.

Assessing the impact of prefabricated buildings on urban green total factor energy efficiency

Prefabricated buildings (PB) are assembled using prefabricated components, known for their cost-effectiveness and high efficiency. They are seen as an effective means to achieving sustainable development goals and mitigating climate change. This paper examines the impact of prefabricated buildings on urban green total factor energy efficiency (GTFEE) using panel data from 278 cities in China. The analysis is conducted through the application of a super-efficiency slack-based measure (SBM) model and a difference-in-differences model. The results of the study indicate that the promotion of PB can significantly improve urban GTFEE; there is heterogeneity in the improvement of urban GTFEE by PB; the innovation effect, industrial effect and marketization effect of PB are the main ways to improve urban GTFEE. Specifically, PB exerts an innovation effect by promoting technological innovation. It influences consumer and investor demand, leading to increased activity in the secondary industry, thereby creating an industrial effect. Moreover, PB facilitates the marketization effect by phasing out outdated industries, encouraging autonomous enterprise innovation, and fostering the growth of new advanced enterprises. This study reveals the critical role of PB in urban GTFEE improvement. It clarifies its mechanism of action, which provides a reference for urban sustainable development strategies and energy efficiency.

Can low-carbon city pilot policies improve urban energy efficiency? evidence from a quasi-natural experiment in China

In the context of global efforts to alleviate climate change, this study focuses on investigating the significance and impact of low-carbon city pilot policies (LCCPP), a key strategy in the reduction of greenhouse gas emissions. Drawing on data from prefecture-level cities spanning 2004 to 2019, the study explores the potential of LCCPP in enhancing green total factor energy efficiency (GTFEE) employing a multitemporal Difference-in-Differences (DID) model and examines its transmission mechanisms. First, LCCPP is shown to be effective in enhancing GTFEE. Second, heterogeneity testing indicates that the impact of LCCPP on GTFEE is more pronounced in “two control zones”, namely, in developing and mature resource cities. Third, industrial restructuring is identified as the key mechanism through which LCCPP influences GTFEE.

Spatiotemporal effect and influencing factors of the total factor energy efficiency: Evidence from the urban agglomerations in China

Amidst the ongoing global energy quandary, the imperative to augment energy efficiency emerges as a strategic response to counteract energy profligacy and propel sustainable development initiatives. This study aims to assist policymakers in gaining a more accurate understanding of the temporal and spatial complexity and dominant variables of total factor energy efficiency at the urban agglomeration level, thereby providing empirical insights for promoting a comprehensive improvement of the existing energy development framework. Based on the dynamic DEA model, this article utilizes an improved common frontier dynamic super-efficiency SBM model to conduct a quantitative analysis of total factor energy efficiency across 19 urban agglomerations in China. The influence factors of total factor energy efficiency are analyzed using spatial kernel density and geographical detectors at both temporal and factor levels. The research findings indicate that: (1) Total factor energy efficiency primarily fluctuates at a mid to low level, with a general decline to below 0.5 after 2018; (2) Significant regional heterogeneity is evident among Chinese urban agglomerations, displaying a “high in the northwest, low in the southeast” regional characteristic; (3) With time lag, the negative spatial spillover effect among regions further intensifies, becoming heterogeneous when the total factor energy efficiency of local urban agglomerations reaches 1.5 or above; (4) The singular and interactive effects of research funding become the main influencing factors of regional differentiation, and the integration of multiple factors is a key driver for enhancing total factor energy efficiency in the new era.

Mapping the Evolution of Green Finance Research and Development in Emerging Green Economies

Research on green and sustainable finance is increasing, crucial for advancing a green financial system and economic growth. Utilizing a Scopus database, this paper collects data and, through bibliometric analysis in R studio, visually explores research trends, hotspots, and fronts in green finance and sustainable development across top emerging green economies. From 2001 to 2022, publications in this field have grown annually, with China leading globally. Significant hotspots include urban total factor energy efficiency, reducing carbon emissions, regional economic development, climate adaptation, technological progress, green innovation, and transitioning from linear to circular economy models. The study anticipates future research to focus on refining industrial and financial structures that align sustainable, green development with superior ecological environment protection, highlighting the evolving nature of green finance research and its impact on promoting sustainable economic practices.

Sustainable energy efficiency in China from the perspective of environmental development: A comprehensive analysis of regional disparities and policy implications

Global agreements have emerged in order to achieve carbon neutrality as the needs for renewable energy sources and carbon reduction continue to grow. To achieve the global carbon neutrality goals, China, one of the largest carbon emitters, must improve urban energy efficiency. Using a three-stage slacks-based measure (SBM) technique, this study analyses the total factor energy efficiency of 270 prefecture-level cities from 2011 through 2020. It tries to monitor and evaluate energy efficiency without taking into account variations in the outside environment. China's total factor energy efficiency shows an overall rising trend, despite significant regional variations. Improved energy efficiency levels can be attributed to technical advancements, while limitations in technology contribute to lower energy efficiency in certain areas. The study highlights the importance of considering external environmental factors in evaluating energy efficiency, able to avoid an overestimation of China's overall energy efficiency. It is noteworthy that the eastern region consistently outperforms the national average in terms of energy use efficiency. Even after taking environmental factors out of the equation, the central, west, and northeast regions still have worse energy efficiency and slower rates of growth. On this basis, from strengthening energy management and planning; facilitating cross-regional sharing of expertise; take targeted policy measures to adapt to the characteristics of the western and northeastern regions and put forward policy suggestions. These guidelines contribute to international energy cooperation and carbon reduction initiatives, while promoting sustainable energy development in China.

Is the Green Total Factor of Energy Efficiency Rising or Falling? Evidence from the Belt and Road Initiative Countries

“The Belt and Road Initiative” (BRI) seeks to attain high‐quality development and sustainability. This study examines the green total factor energy efficiency (GTFEE) of 58 BRI countries from 2005 to 2019 and its influence factors using the Super slacked‐based measurement and Tobit models. The findings indicate that: 1) Singapore and the other seven countries have GTFEEs above 0.9, which is better than other countries; seven out of 58 countries have GTFEEs below 0.5. 2) Due to regional disparities, Southeast Asia, Central, and Eastern Europe have the greatest GTFEE, followed by South Asia, West Asia, and the Commonwealth of Independent States, and the lowest is in Central Asia, China, and Mongolia. 3) Compared to developing economies, developed economies have a higher GTFEE. 4) Between 2005 and 2019, the overall BRI energy efficiency dropped from 0.75 to 0.56. 5) According to Tobit results, for every 1% increase in economic development and energy structure, GTFEE increases by 0.08% and 0.31% points, respectively, and for every 1% increase in trade and land area, GTFEE decreases by 0.04 and 0.05, respectively. Therefore, BRI countries should strengthen international cooperation, develop advanced technologies, and increase the proportion of renewable energy utilization.

Can digital technology innovation promote total factor energy efficiency? Firm-level evidence from China

The study is based on panel data of listed manufacturing companies from 2010 to 2022, identifies digital technology innovation (DGTI) by using patent data, uses two-step stochastic frontier with Shepard energy distance function to measure total factor energy efficiency (TFE), and analyzes the impact of DGTI on TFE. Research has found that the larger the scale of DGTI, the more conducive it is to TFE. DGTI can also promote TFE by improving environmental responsibility fulfillment and internal control quality, while, DGTI may hinder TFE by increasing operating costs. In the heterogeneity, DGTI has a stronger promoting effect on the TFE of large-scale firms and state-owned firms. In the central and western regions, DGTI has a U-shaped effect that first inhibits and then promotes TFE. Moreover, intellectual property protection, information infrastructure, and digital industry agglomeration will all promote the positive impact of DGTI on TFE. This study aims to provide implications for improving energy efficiency and promoting digital technology research and development.

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.

The impact of market-based environmental regulation on corporate ESG performance: A quasi-natural experiment based on China's carbon emission trading scheme

At present, there are few studies exploring the impact of market-based environmental regulation on ESG performance based on the perspective of carbon emission trading scheme (CETS). This paper aims to supplement this research field through empirical analysis. Taking Shanghai-Shenzhen A-share listed companies from 2012 to 2022 as the research object, this paper studies the impact of CETS, a market-based environmental regulation tool, on the ESG performance of enterprises by constructing a time-varying DID model and examines the mediating roles of green technology innovation, agency cost and analyst attention. The results show that the implementation of CETS can significantly boost ESG performance, and green technology innovation, agency cost, and analyst attention play a partial intermediary role between the two, while the mediating effects of green total factor productivity and green total factor energy efficiency are not significant. In terms of heterogeneity analysis, the study shows that CETS implementation has a more substantial promotion effect on ESG performance in non-state-owned enterprises, non-politically connected enterprises and non-high-tech enterprises. In this paper, the robustness test was carried out through PSM-DID, placebo test and replacement of explained variables, and the test results further supported the hypothesis in this paper. This study enriched the research on the impact of market-based environmental regulation on ESG from the perspective of CETS. It provided enlightenment for enterprises to improve ESG performance to a strategic level, improve the level of green technology innovation, and the government to implement differentiated environmental governance policies.

Total-Factor Energy Efficiency (TFEE) and CO2 Emissions for GCC Countries

Recently, the potential role of energy efficiency in energy transformation on the path to sustainable development has become a crucial topic. Over the past three decades, energy consumption and CO2 emissions in the Gulf countries have increased dramatically. This paper assesses the energy efficiency of Gulf Cooperation Council countries during the period 2000–2019. Thus, the contribution of this study to the energy policy literature is to measure the total-factor energy efficiency, in order to explore the current energy efficiency situation in the Gulf countries. This is the first study of the Gulf countries in terms of estimating the total-factor energy efficiency using the DEA–Malmquist method. The analysis shows that the average total factor productivity change index value was 0.964, with a decline rate of 3.6%. This demonstrates that energy efficiency in those regions has experienced a relative decline. The results of Malmquist analysis show that the total factor productivity change index for the Gulf countries is less than 1, which means a regression in their efficiency (energy inefficiency) from 2000 to 2019. This means that the decline in total-factor energy efficiency in those regions was mainly due to the technical progress index. The results of the study can help policy makers understand the current level of energy efficiency, and identify the main drivers of total-factor energy efficiency. Based on the results, some policy implications related to energy efficiency and suggestions for the GCC region were formulated.

How Do Financial Development and Industrial Structure Affect Green Total Factor Energy Efficiency: Evidence from China

Improving energy efficiency is vital for addressing climate change and reducing carbon emissions in emerging economies. Financial development (FD) is crucial for economic growth, and its environmental impact and the adjustment of the industrial structure (IND) is a crucial lever in China’s economic transition period. This study explored the relationship between FD, IND, and China’s green total factor productivity (GTFEE) from 2000 to 2020 using the super-efficiency SBM-undesirable model, which estimates China’s GTFEE. The ARDL results suggest that FD and IND enhance GTFEE in the long term, with FD promoting GTFEE by facilitating industrial structure adjustments. The Dumitrescu–Hurlin panel causality tests supported this finding. The QRPD panel quantile regression and heterogeneity analysis revealed significant heterogeneity in the effects. With increasing GTFEE, FD exerts a restraining effect, gradually weakening and transitioning into a promoting effect, while the IND consistently plays a promoting role.

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.

How do the construction of urban high-speed railways influence green total factor energy efficiency?

As a typical measure for reducing carbon footprint, the opening of high-speed railways (HSRs) is a powerful lever for attaining the strategic purpose of carbon peak and carbon neutrality. Derived from the data of 265 prefecture-level cities in China from 2001 to 2018, this study adopts the Dynamic Network Slacks-Based Measure (DNSBM) model and introduces link variables and carry-over variables to conduct a dynamic assessment of green total factor energy efficiency (GTFEE). The study finds that the opening of HSRs significantly improved the GTFEE and this conclusion is robust under multiple conditions such as PSM-DID, counterfactual test and exclusion of other policy interference. Heterogeneity analysis indicates that the construction of HSRs has a more significant positive influence on GTFEE in smart city pilot cities, non-old industrial base cities middle and lower reaches of the Yangtze River Economic Belt (YREB). Mechanism testing indicates that economy concentration effect, structural optimization effect, and innovation driven effects are the transmission channels of HSRs in promoting low-carbon transition.

Measurement and influencing factors of TFEE, and potentials of energy conservation and emission reduction in china based on GW-SBM and bootstrap model

With the aggravation of energy shortage and ecological deterioration, it becomes more and more essential for China to improve energy efficiency and realize the targets of energy conservation and emission reduction. This paper focuses on the measurement of the total factor energy efficiency (TFEE), the potentials of energy conservation and emission reduction, and the influencing factors of TFEE in China. Firstly, the model of Gray Weight Slack-Based Measure (GW-SBM) is established, with the weights of the indicators obtained via the grey relational analysis method, to calculate the TFEE of thirty provinces and six regions in China from 2009 to 2019. Then, the potentials of energy conservation and emission reduction are analyzed on the basis of TFEE measurements. Finally, the influencing factors of TFEE are identified via the truncated bootstrap model. The findings show that the TFEE values of 30 provinces fluctuate in the range of 0.20 and 1.0, varying significantly among provinces. Energy conservation potential reached 8.7490 million tons of standard coal (potential 39.06%), which means that more than one-third of energy consumption is inefficient. The top two factors in the TFEE measurement identified by the truncated bootstrap model, are energy consumption structure and environmental protection expenditure. Based on the research conclusions, this paper puts forward some countermeasures and suggestions.

Do smart cities improve energy efficiency? A test of spatial effects and mechanisms

In recent years, a great deal of research has been done on how smart cities affect pollution. However, nothing is understood about how smart city affect energy efficiency. Based on China's 283 cities panel dataset from 2003-2019, the impact, spatial effects, and mechanisms of smart city projects (SCP) on green total factor energy efficiency (GTFEE) are empirically tested employing the multi-phase and spatial difference-in-difference (DID) method. The results indicate that (1) SCP significantly improves urban GTFEE, a finding that remains valid after the instrumental variables approach and robustness tests. (2) In east-central cities, economically developed cities, medium-sized cities, and non-resource-based cities, SCP significantly affects GTFEE. (3) The SCP considerably raises the local GTFEE but also the GTFEE of the 900-kilometer radius around cities. (4) SCP can improve GTFEE by clean energy development, optimizing industrial structure, promoting green innovation, and resource allocation. In addition, energy saving, emission reduction, and production increase are also important impact channels. Finally, based on its findings, the study offers a reference for decision-making to support SCP development and urban energy efficiency improvement.