Total-factor Energy Efficiency Research Articles

Unleashing the power of green fiscal policies: Driving energy efficiency in China

This study examines the impact of such policies on energy efficiency by focusing on the “National Comprehensive Demonstration of Energy Saving and Emission Reduction Fiscal Policy” (ESER fiscal policy). Using a difference-in-difference method with multiple time points, the study finds that the ESER fiscal policy has significantly closed the total factor energy efficiency (TFEE) gap. The results are robust, supported by sensitivity analyses such as variable substitutions, dynamic effect tests, exclusion of potential intervening variables, placebo tests, and propensity score matching. Mechanism analysis shows that the pilot program closes the energy efficiency gap by increasing expenditure on environmental protection, improving agglomeration of productive services, and promoting of green technological innovation. Furthermore, the impact of green fiscal policies on TFEE is more pronounced in cities within two-control areas, non-old industrial base cities, large-scale cities, and resource-depleted cities. The analysis of the energy rebound effect found that green fiscal policies can effectively close the energy efficiency gap without generating energy rebound. These findings provide valuable insights and empirical evidence on the effectiveness of China's green fiscal policies in achieving green development, improving quality and efficiency.

The Impact of Industrial Robots on Green Total Factor Energy Efficiency: Empirical Evidence from Chinese Cities

Improving energy utilization efficiency is a crucial means to achieve energy conservation, emission reduction, and green development. At present, to establish a high-quality development framework and satisfy the growing need for a better life among all its people, China must steadfastly pursue the path of green development. Although China’s substantial economic scale and achievements in ecological civilization construction provide favorable conditions for green transformation, there remains a significant gap compared to developed countries in the application of green and clean technologies. Confronted with technological bottlenecks, leveraging emerging technologies such as industrial robots from the new round of scientific and technological revolutions to improve the green total factor energy efficiency (GTFEE) is of critical importance to China’s green development. This study explores the potential impact of industrial robots on enhancing China’s GTFEE. It begins by reviewing the current research landscape in this field, highlighting its shortcomings, and theorizing potential impact pathways of industrial robots. Subsequently, the paper analyzes data from 2010 to 2019 on the usage of industrial robots and GTFEE across 276 cities at the prefectural level or above in China. Through empirical regression models that incorporate control variables and interaction terms, the study investigates the specific impacts of industrial robots on energy efficiency and their mechanisms of action. The results indicate that industrial robots significantly enhance the GTFEE of Chinese cities, especially in the Northeastern region. Industrial robots notably improve the GTFEE in resource-based cities, old industrial bases, and low-carbon pilot cities. Additionally, robots indirectly boost GTFEE by increasing labor productivity. Enhanced levels of green innovation and environmental regulations also positively moderate the effectiveness of industrial robots in improving energy efficiency. The findings of this research can assist local government agencies in coordinating and implementing policies that are conducive to green development, making better use of industrial robots to serve the people, and are of significant importance for promoting the transformation of China’s economy and society towards high-quality development.

Research on energy saving effect of spatial correlation network of digital infrastructure: based on the analysis of network centrality.

Accurately portraying the spatially linked network characteristics of digital infrastructure and exploring its energy-saving effects are highly valuable for enhancing the synergy in digital infrastructure development and expanding its network spillover effects on energy conservation. This paper uses panel data at the city level in China and employs a modified gravity model to calculate the centrality of digital infrastructure spatial correlation network nodes. Based on this, an econometric model is constructed, incorporating variables such as digital infrastructure spatial correlation network node centrality and urban green total factor energy efficiency. The model is used to analyze the effects and transmission paths of digital infrastructure network node centrality on urban green total factor energy efficiency. The analysis yields the following conclusions: (1) Digital infrastructure spatial correlation network node centrality significantly improves urban green total factor energy efficiency, with considerable variability due to city geographic location, city scale, and city attributes. (2) Nonlinear testing results indicate that as digital infrastructure construction advances, its impact on urban green total factor energy efficiency shifts from inhibitory to promotional. (3) The impact mechanism shows that digital infrastructure node centrality enhances urban green total factor energy efficiency through green technology innovation. Additionally, it promotes advanced industrial structures and reduces capital mismatch, further influencing energy efficiency. (4) Digital infrastructure node centrality not only boosts urban green total factor energy efficiency but also facilitates regional convergence, increasing the convergence rate from 0.094 to 0.170%. The findings of the research offer policy guidance for the government on advancing digital transformation initiatives and enhancing energy efficiency.

The haze reduction effect in china under the digital economy

Haze pollution is becoming increasingly serious as it endangers human health and pressurizes economic development. This study incorporates the digital economy and haze pollution management into a unified research framework, and uses the panel data of 285 cities in China from 2011 to 2020 to precisely identify the haze reduction effect of the digital economy, governance mechanisms, and the non-linear and spatial spillover characteristics of the haze reduction effect in China. The findings demonstrate that: First, the digital economy can significantly reduce haze pollution, and this conclusion still holds after considering endogeneity and other robustness tests. Second, the digital economy can inhibit haze pollution by promoting industrial upgrading and improving total factor energy efficiency, and there is a chain mechanism of “industrial green transformation → total factor energy efficiency” and “factor market distortion → total factor energy efficiency.” However, the haze reduction mechanism of digital economy is heterogeneous to cities with different levels of economic development. Independent transmission mechanism plays a complete intermediary role in cities with low level of economic development, while it plays a partial intermediary role in cities with high level of economic development. Chain transmission mechanism only has an impact on cities with high level of economic development. Third, there is an evident threshold effect on the digital economy, and its haze reduction effect has N-type non-linear characteristics. Meanwhile, Digital economy has threshold effect on the mechanism of restraining haze pollution through total factor energy efficiency, industrial green transformation and factor market distortion. With the development of total factor energy efficiency, industrial green transformation and the reduction of factor market distortion, the haze reduction effect of digital economy can produce a qualitative leap. Fourth, Haze pollution in the spatial, temporal, and spatial dimensions has spillover and warning effects, and the haze reduction effect of digital economy shows strong positive externalities. Therefore, the digital economy should be actively developed, and industrial green transformation and factor market reform should be promoted to curb haze pollution by promoting industrial upgrading, improving energy efficiency and strengthening regional joint prevention and control mechanisms.

Ultra-High-Voltage Construction Projects and Total Factor Energy Efficiency: Empirical Evidence on Cross-Regional Power Dispatch in China

Optimizing cross-regional energy dispatch is crucial for addressing regional energy resource imbalances and significantly enhancing energy utilization efficiency. This study aims to analyze the potential impact of China’s ultra-high-voltage (UHV) construction on firms’ total factor energy efficiency and provide empirical evidence supporting the role of cross-regional energy dispatch in improving firms’ energy efficiency. The construction of UHV infrastructure has become a vital part of China’s “New Infrastructure” projects, presenting a “Chinese solution” to the global challenge of regional energy resource mismatches. This study employs an enhanced two-step stochastic frontier method to quantify firms’ total factor energy efficiency and utilizes a difference-in-differences model to evaluate the impact of inter-regional electricity dispatch on this efficiency. The empirical analysis results indicate that UHV construction projects increase the total factor energy efficiency of regional firms by an average of 0.45%, which significantly contributes to firms’ total factor productivity. This conclusion remains valid after a series of robustness tests. Furthermore, the heterogeneity analysis results indicate that the UHV construction project increases the total factor energy efficiency of non-energy-intensive industries by 0.49%, and significantly enhances the total factor energy efficiency of the manufacturing industry by 0.94%. However, it has no significant effect on energy-intensive industries or non-manufacturing enterprises. Additionally, the mechanism analysis shows that UHV construction projects affect total factor energy efficiency through three pathways: industrial structure adjustment, urban innovation, and clean energy transition. This study offers insights for addressing regional energy spatial mismatches and provides policy recommendations for developing a new energy system aligned with regional needs.

Green growth governance and total factor energy efficiency: Economic growth constraint and policy implementation in OECD countries

This study aims to examine the nature and governance of green growth strategy in OECD countries. As the strategy implies a sustainable relationship between economic growth and energy efficiency, we considered economic, environmental, and policy factors to empirically analyze green total factor energy efficiency (GTFEE) performances for 2001–2020 period. For this purpose, we employed a two-step methodology. In the first step, we estimated GTFEE scores from an undesirable output model by using robust order-m frontier efficiency method. In the second step, we used GTFEE estimates and built a panel data model to investigate the impact of governance and environmental policy factors. The panel data regression results point to several implications. Firstly, market-based environmental stringency policies are found to be effective. Also, economic globalization is found to be effective only in market-based and mix policy cases. The findings indicate the key roles of market-based pricing mechanisms and economic actors for the inclusive governance of green growth. Secondly, economic growth is found to be negatively related with GTFEE which shows the trade-off between economic growth and energy efficiency. Lastly, the analysis by commitment periods of the Kyoto Protocol points to the importance of global consensus on the implementation of green growth strategy.

Factor market distortion, total factor energy efficiency and energy shadow price: A case of Chinese manufacturing industry

The manufacturing industry is responsible for the highest share of energy consumption in China and improving its energy efficiency is important for reducing the dependence of economic growth on the growth of fossil energy consumption and carbon emissions. However, factor market distortion (FMD) has substantially inhibited effective resource allocation. This study proposes a metafrontier parametric linear programming method based on the Shephard energy distance function to measure the total factor energy efficiency (TFEE) of Chinese manufacturing industry. Then, we derive the energy shadow price by cost minimization. Finally, we compare and analyze the impact of different levels of FMD on TFEE and energy shadow price. The results showed that regions with lower FMD had higher TFEE from 2000 to 2021. FMD hindered TFEE mainly by affecting technical efficiency and scale efficiency. The energy shadow price within China's manufacturing industry exhibited a downward trend and regions with low FMD had a higher energy shadow price. This implies that the manufacturing industry in China is progressively diminishing its reliance on fossil fuels for production activities. The efficient distribution of production factors may enhance the actual marginal value of energy inputs.

Spatial conditional convergence analysis of total factor energy efficiency based on industry transfer and technology diffusion

Measuring energy efficiency is important to achieve the goal of sustainable economic development. This paper adopts the Malmquist index to measure the trend of regional total factor energy efficiency. This paper analyses the spatial aggregation characteristics of TFEE and the impact mechanism of industrial transfer and technology diffusion on TFEE convergence from a dynamic perspective. The results of the study show that there is a large gap in TFEE between regions in China, with a spatial characteristic of “high in the south and low in the north”. In 2006–2021, the convergence rate of TFEE shows a slowing down trend. Industrial transfer has a negative effect on TFEE. The impact of technology diffusion on TFEE is different in different periods. The impact of researchers, technology market, technology introduction, and import-export on TFEE have significant differences. The convergence rate of the south is higher than that of the north. The impact of industrial transfer and technology diffusion on TFEE in the two parts is different. Policymakers should implement differentiated energy policies based on the characteristics of the industrial structure and technological development of each region. They should actively guide technological innovation, promote industrial diversification, and build a clean and efficient energy system.

Retraction notice: Spatial spillover effects of technological innovation on total factor energy efficiency: taking government environment regulations into account for three continents

Retraction notice: Spatial spillover effects of technological innovation on total factor energy efficiency: taking government environment regulations into account for three continents

Urban green total factor energy efficiency and its decomposition under a multidimensional heterogeneity framework: a case study of the Yellow River Basin, China.

Assessing and monitoring the green total factor energy efficiency (GTFEE) of cities while considering technology heterogeneity is crucial for the development of energy-conservation and emission-reduction policies. Considering that the heterogeneity of production technologies encompasses several dimensions, this paper proposes a 3E3S (Economy-Environment-Energy-Society-Science-Space) heterogeneity framework and integrates it with the improved meta-frontier global SBM-undesirable to analyze GTFEE and its decomposition. Empirical analysis of cities in the Yellow River Basin of China (YRBC) highlights the following: (1) The 3E3S heterogeneity framework facilitates the classification of all cities into three distinct groups, a finding that contrasts significantly with previous outcomes documented in the literature that relied solely on criteria such as geographic location. (2) The three groups identified under the meta-frontier exhibit substantial energy-saving potentials of 24.49%, 35.17%, and 52.46%, respectively. Additionally, there are spatiotemporal variations in GTFEE, with cities located in the central part of YRBC, particularly those in Shanxi province, demonstrating poor GTFEE performance. (3) The decomposition analysis of GTFEE indicates that technological progress plays a pivotal role in enhancing GTFEE on the whole, albeit with varying approaches for improving GTFEE depending on individual cities.

The Impact of Coal-Fired, Soot on China's Industrial Production and Total Factor Energy Efficiency

The Impact of Coal-Fired, Soot on China's Industrial Production and Total Factor Energy Efficiency

Does Air Quality Ecological Compensation Improve Total Factor Energy Efficiency?—A Quasi-Natural Experiment from 282 Cities in China

The impact of air-quality ecological compensation on total factor energy efficiency can help a country to achieve high-quality economic development with the goals of peak carbon emissions and carbon neutrality, and to explore a win–win path for the economy and the environment. This study investigates the impact of air-quality ecological compensation (AQEC) on total factor energy efficiency using the time-varying difference-in-difference model with a sample of 282 Chinese cities from 2004 to 2022. The results show AQEC significantly increases total factor energy efficiency by 1.71% in the pilot areas. This result remains robust after undergoing PSM-DID, considering only the first three pilot batches, an instrumental variable approach, the exclusion of other policies interference, and dual machine learning. The mechanisms analysis indicates that AQEC enhances total factor energy efficiency by promoting industrial structure advancement and green technology innovation. Furthermore, it is noteworthy that heterogeneity exists in the effect of AQEC on total factor energy efficiency, particularly in cities with an old industrial base and small cities. Overall, this study refines the causal relationship between air-quality ecological compensation and total factor energy efficiency, providing empirical evidence and policy insights for China and other countries to enhance energy efficiency and promote urban ecological civilization.

Towards China's dual-carbon target: Energy efficiency analysis of cities in the Yellow River Basin based on a “geography and high-quality development” heterogeneity framework

The Yellow River Basin (YRB) serves as a critical energy hub in China. Enhancing energy efficiency in cities across the YRB is pivotal for achieving high-quality development and meeting carbon peaking and neutrality targets. This paper proposes a multidimensional technology heterogeneity assessment framework to refine the classification of production technologies. It leverages this framework to develop a data envelopment analysis model for evaluating green total factor energy efficiency (GTFEE) in 78 cities within the YRB from 2006 to 2022. The key findings are as follows: (1) Grouping outcomes from the multidimensional heterogeneity framework significantly differ from existing literature. (2) GTFEE shows notable spatiotemporal variations within the YRB, with a substantial overall increase since 2011. However, cities in the central YRB exhibit lower GTFEE performance. (3) Energy inefficiency in groups 1, 2, and 3 is attributed to developmental inefficiency, management inefficiency, and practical inefficiency, respectively. (4) Evaluation of energy-saving potential reveals an average annual potential of around 8 million tce per city during 2006–2022. The study concludes with strategies for enhancing GTFEE based on dynamic GTFEE decomposition outcomes, supporting policy design for achieving dual-carbon goals through improved energy efficiency in the YRB region.

Does carbon pricing policy improve energy efficiency? New evidence from Canadian provinces

ABSTRACT Given the increasing damage effect of climate change, the Canadian government has taken a further step to ensure that carbon pricing is implemented in all provinces to reduce its GHGs emissions as a means of addressing climate change. Thus, this paper examines the effect of carbon pricing on energy consumption which is the main source of CO2 emission to enhance our understanding beyond carbon-pricing effects on households and revenue recycling in the prior research. Our study analyzes the energy efficiency of Canada using the province-level data between 2000 and 2021, by developing an SFA production model to understand the drivers of energy consumption and then compute the total factor energy efficiency index while controlling for the role of carbon pricing. Our empirical results reveal that increased labor input, as well as output, mitigate the rising capital-induced energy consumption, while carbon pricing policy plays no significant role in influencing energy consumption. However, the effectiveness of carbon pricing is found in reducing province-level energy efficiency. This striking evidence suggests that policymakers should consider a labor-oriented energy saving scheme and conduct a comprehensive review of the current carbon pricing policy in order to align with energy efficiency interventions toward the achievement of Canada’s Paris Agreement targets.

Energy quota trading policy and energy efficiency: The role of government supervision and public participation

Unlike carbon emissions trading based on end-of-pipe regulation, the Energy Quota Trading (EQT) policy represents a market-oriented environmental regulation rooted in source control. However, its effectiveness on energy efficiency remains to be scrutinized. Using the panel data of 269 cities in China from 2011 to 2021, we employ the difference-in-differences method to examine whether and how the EQT policy impacts energy efficiency. Our results reveal that the EQT policy can significantly enhance green total factor energy efficiency. Mechanism analysis indicates that this promotion is primarily achieved by fostering green technology innovation and facilitating industrial structure upgrading. Further investigations explore the moderating role of external supervision, demonstrating that government supervision and public participation can amplify the EQT policy's efficacy in promoting energy efficiency. This underscores the complementary role of governmental and public in bolstering the utility of market-oriented incentives. Additionally, we identify significant heterogeneity in EQT policy effects across cities with varying geographical locations and development strategies. Our research offers critical insights into the adoption of source-control environmental regulations for developing countries.

Energy rights trading policy, spatial spillovers, and energy utilization performance: Evidence from Chinese cities

China initiated its first energy rights trading (ERT) pilot in 2016 and had plans to assess the policy's replicability in 2020. However, there is limited literature available that examines its influence on energy utilization performance (EUP). To complement this knowledge gap, the study investigates the impacts and mechanisms of ERT on EUP employing a spatial difference-in-difference (SDID) model. The findings reveal that: (1) ERT reduces local energy consumption significantly, increases green total factor energy efficiency, and enhances the EUP of neighboring cities within an 1100 km radius. (2) ERT indirectly enhances the EUP of local and neighboring cities through green innovation, transformation towards cleaner energy structures, and energy allocation. Notably, ERT boosts the local EUP via industrial structure upgrading but reduces the positive spillover effects on nearby cities due to the siphoning effect. (3) ERT exhibits more pronounced impacts and spillover effects on cities that are not resource-dependent and have higher levels of marketization. Interestingly, the central and western regions benefit more from the spillover effects of ERT. The findings of this study will serve as a valuable resource for advancing the implementation of ERT and offer critical insights for decision-makers focused on sustainable urban development.

Spatial–temporal evaluation of total-factor energy efficiency in Chinese construction industry based on three-stage super-efficiency SBM-DEA model

PurposeThe study aims to enhance energy efficiency within the high-energy consuming construction industry. It explores the spatial-temporal dynamics and distribution patterns of total factor energy efficiency (TFEE) across China’s construction industry, aiming to inform targeted emission reduction policies at provincial and city levels.Design/methodology/approachUtilizing a three-stage super-efficiency SBM-DEA model that integrates carbon emissions, the TFEE in 30 Chinese provinces and cities from 2004 to 2019 is assessed. Through kernel density estimation and exploratory spatial data analysis, the dynamic evolution and spatial patterns of TFEE are examined.FindingsAnalysis reveals that environmental investments positively impact TFEE, whereas Gross Regional Product (GRP) exerts a negative influence. R&D expenditure intensity and marketization show mixed effects. Excluding environmental and random factors, TFEE averages declined, aligning more closely with actual development trends, showing a gradual decrease from east to west. TFEE exhibited fluctuating growth with a trend moving from inefficient clusters to a more even distribution. Spatially, TFEE demonstrated aggregation effects and characteristics of space-time transition.Originality/valueThis research employs the three-stage super-efficiency SBM-DEA model to measure the total factor energy efficiency of the construction industry, taking into account external environment, random disturbances, and multiple effective decision-making units. It also evaluates energy efficiency changes before and after removing disturbances and comprehensively examines regional and temporal differences from static and dynamic, overall and phased perspectives. Additionally, Moran scatter plots and LISA cluster maps are used to objectively analyze the spatial agglomeration and factors influencing energy efficiency.

Unlocking a greener future: The role of digital finance in enhancing green total factor energy efficiency

The development of digital finance provides new opportunities for improving energy efficiency and promoting green development. This paper calculates green total factor energy efficiency (GTFEE) using the super-efficiency SBM model and examines the impact of digital finance on GTFEE. Digital finance has a significant positive impact on GTFEE. Under a bank-dominated financial structure, the positive impact of digital finance on GTFEE is quite significant. In regions with intense banking competition, a large amount of green credit, and lower resource dependence, digital finance is conducive to enhancing GTFEE. Optimizing the allocation efficiency of production factors is an essential mechanism for digital finance to encourage improvements in GTFEE. Digital finance alleviates distortions in factor markets and enhances the matching of the marginal output and the price of capital, labor, and energy factors, thereby facilitating improvements in GTFEE. Further analysis indicates that digital finance has a significant, positive spatial spillover effect on GTFEE, enhancing GTFEE levels in both local and neighboring regions. This study enriches the research on the relationship between digital finance and energy efficiency and provides theoretical foundations and policy references for how digital finance can better serve the green transition of the economy.

Improve energy use efficiency through free trade policy: evidence from the establishment of free trade zones in China.

In the context of increasing global resource and environmental problems, it is of great practical significance to accurately test the impact of various factors on energy use efficiency for maintaining national energy security and formulating relevant policies. This paper measures firms' total factor energy efficiency (TFEE) using the two-stage stochastic frontier method within the data envelopment analysis (DEA) framework, leveraging data from listed firms in China spanning 2010 to 2022. Employing the establishment of free trade zones (FTZs) as a quasi-natural experiment, we apply the staggered differences-in-differences (DID) and stacked DID methods and analyze the impact of FTZs on firms' TFEE. The results show that the establishment of FTZs significantly promotes the improvement of firms' TFEE, and it has a greater promotion effect on heavily polluting, non-manufacturing, state-owned, private, and small-scale firms. The results of the mechanistic analysis showed that the promotion effect of FTZs on firms' TFEE is mainly realized through three channels: increasing government subsidies, reducing the financing constraint effect, and encouraging the technology innovation effect. Furthermore, industry-level decomposition results indicate that the surge in industry energy efficiency primarily results from improvements within firms rather than inter-industry variations. This paper's results propose that countries can enhance energy efficiency by progressively endorsing the implementation of FTZs.

The Spatial Spillover Effect of OFDI on Energy Efficiency

The article uses the spatial Durbin model to examine the spatial spillover effect and mechanism of outward foreign direct investment (OFDI) on China’s green total factor energy efficiency. The study found that, from an overall perspective, outward direct investment negatively impacts local green total factor energy efficiency and has a negative spatial spillover effect on green total factor energy efficiency in geographically related regions. From a regional perspective, the impact of outward direct investment on regional green total factor energy efficiency shows significant regional heterogeneity. In contrast, outward direct investment in the eastern region only promotes improving local green total factor energy efficiency. Mechanism analysis found that outward direct investment negatively impacts the region’s green total factor energy efficiency by inhibiting green technology innovation and industrial structure upgrading. These research conclusions can provide important references for other countries to optimize their foreign investment policies and achieve sustainable development.