Regional Total-factor Energy Efficiency Research Articles

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.

Is cleaner more efficient? Exploring nonlinear impacts of renewable energy deployment on regional total factor energy efficiency

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation.

Do the national industrial relocation demonstration zones have higher regional energy efficiency?

The National Industrial Relocation Demonstration Zones serve as an important platform for optimizing spatial layout of productivity and promoting coordinated regional development. The impact of the establishment of demonstration zones on regional total factor energy efficiency remains unclear. This paper used dynamic slacks-based measurement method to measure the total factor energy efficiency of prefecture-level cities from 2005 to 2017. A Difference-in-Differences method is used to examine the policy effect of demonostration zones on regional energy efficiency. The results indicate that the average energy efficiency of these regions shows a downward trend within the observation interval. The establishment of the National Industrial Relocation Demonstration Zones has reduced the energy efficiency of the demonstration zones and not promoted the advanced development of industrial structure. Foreign Direct Investment and government intervention are the main reasons for the decline of total factor energy efficiency in the region. These findings have significant implications for the design of future policy which can promote the high-quality development of the central and western regions through industry transfer.

Regional Total Factor Energy Efficiency Evaluation of China: The Perspective of Social Welfare

The energy resource is an essential input of economic growth, which has an important impact on the ecological environment and social welfare. From the perspective of social welfare, considering the radial and non-radial characteristics of different input and output indicators, and the inseparability of the energy input and undesirable output, this study employs the non-separable hybrid DEA (Data Envelopment Analysis) model to evaluate the total energy efficiency of Chinese provinces between 2012 and 2016. Furthermore, this study calculates the energy saving and emission reduction potentials of China. The results reveal that the average total factor energy efficiency in China from 2012 to 2016 is 0.694, which means that there are still 30.6% energy efficiency losses. There is great potential for China to save energy, reduce pollutant emissions, and increase the output of social welfare. There are great differences in the total factor energy efficiency among provinces. The average energy saving potential of the whole country is 60.5%. If the energy efficiency of all provinces can reach the frontier, the whole country can save more than half of the energy consumption. The highest national average emission reduction potential is SO2, followed by dust, CO2, and NOX. The implication of the conclusion is that in the development of regional economy, we cannot sacrifice the social welfare and sustainable development and take the growth rate of GDP as the only objective. Different energy saving and emission reduction policies should be put forward according to the characteristics of different provinces.

Correction: Huang, H., et al. The Total-Factor Energy Efficiency of Regions in China: Based on Three-Stage SBM Model. Sustainability 2017, 9, 1664

The authors did not realize the errors made in the affiliations and references in the proofreading phase. [...]

Does grid-connected clean power promote regional energy efficiency? An empirical analysis based on the upgrading grid infrastructure across China

Abstract On the basis of the fact that China is setting up world's largest electricity network with the extra high voltage (EHV) and ultra high voltage (UHV) as their backbones, creating the foundation for large-scale accession of clean power which may deeply affect regional energy efficiency across the country, this paper attempts to empirically study the joint effects of clean power accessing to power grids on regional total-factor energy efficiency. To complete this job, we first measured the total-factor energy efficiencies of 29 provinces in China over the period 1991–2013, based on one of the data envelopment analysis methods, then, the static panel model considering panel fixed effect with instrument variable (FE-IV), dynamic panel model of system generalized method of moments (SYS-GMM) and panel smooth transition regression (PSTR) were employed, respectively, to investigate separate and joint effect of clean power and its grid-connection with EHV and UHV electricity network. The results show that the joint effect of clean power accessing to EHV and UHV power grid is either not significant or even negative although clean power itself separately promote regional energy efficiency. Thus, while the investment in grid infrastructure continues to increase, the grid-connection mechanism of clean power needs to be optimized therewith.

Spatial econometric analysis of factors influencing regional energy efficiency in China.

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

The Total-Factor Energy Efficiency of Regions in China: Based on Three-Stage SBM Model

This paper constructs a three-stage Slacks-Based Measure (SBM) model to evaluate and analyze the total-factor energy efficiency (TFEE) of 276 cities in China during the period of 2000–2012 from the management and environment dual perspectives according to the principles of multi-stage Data Envelopment Analysis (DEA) model. In the first stage, a SBM-DEA model is applied to assess TFEE scores to illustrate the effects of the energy factors, while considering the undesirable output. In the second stage, we adjust the original data, and then in the third stage, we use SBM model again to get efficiency evaluation and obtain pure management efficiency of every decision unit. The results show that Chinese TFEE is still low and energy saving potential can be up to 34–46%, showing an inverted “U” shape tendency and characteristic of regional imbalance. Based on these findings, we further put forward some paths and strategies to improve Chinese energy efficiency.

The congestion total-factor energy efficiency of regions in Taiwan

This study applies the congestion total-factor energy efficiency model to analyze the energy efficiency of 20 administrative regions in Taiwan from 2004 to 2013, by studying four kinds of energies: amount of electricity for manufacturing industry use, amount of electricity consumed for lighting, amount of gasoline sales, and amount of diesel sales. The main findings are that: (i) in terms of these four energies, only Taipei City, Taitung County, and Penghu County among the 20 administrative regions exhibit no phenomenon of energy input congestion during the whole data period; (ii) more attention should be put on energy efficiency improvement in diesel use than on electricity for manufacturing industry use, electricity consumption for lighting, and gasoline usage; and (iii) the energy efficiency outcomes in Taiwan correlate to the country's regional development features such as its tourist regions, including Taitung County and Penghu County, which have nature, green, and environmental protection characteristics.

Analysis of regional total factor energy efficiency in China under environmental constraints: based on undesirable-minds and DEA window model

With China’s entrance into the new economy, the improvement of energy efficiency has become an important indicator to measure the quality of ecological civilization construction and economic development. According to the panel data of Chinese regions in 1996-2014, the nearest distance to the efficient frontier of Undesirable-MinDS Xeon model and DEA window model have been used to calculate the total factor energy efficiency of China’s regions. Study found that: Under environmental constraints, China’s total factor energy efficiency has increased after the first drop in the overall 1996-2014, and then increases again. And the difference between the regions is very large, showing a characteristic of “the east is the highest, the west is lower, and lowest is in the central”; finally, this paper puts forward relevant policy suggestions.

Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey

Regional energy and environmental efficiency measurement is a noteworthy research topic regarding regional development. Data Envelopment Analysis is a suitable technique in the studies of energy and environmental efficiency. This study investigates the efficiency and total-factor energy efficiency scores of the manufacturing industry in 26 regions of Turkey between the years 2003 and 2012, using four data envelopment analysis models supported by a total-factor framework. The first and the second models are based on absence and presence of undesirable outputs, respectively; the third model and the proposed new model aims to maximize energy saving potential considering undesirable outputs. The empirical results show that TR10-Istanbul region is the best performer and acts as a model for inefficient regions with its production composition. Total electricity saving potential is investigated per each region and for the manufacturing industry per each year between years 2003–2012. It is observed that Turkish manufacturing industry has an average electricity saving potential of 39.7%, which reaches its highest in 2004 and lowest in 2012. Another important finding of this study is the existence of a U-shaped relationship between gross value added per capita as regional development indicator and efficiency as well as total-factor energy efficiency index.

The impact and economic cost of environmental regulation on energy utilization in China

This article utilizes three data envelopment analysis-based models: a no environmental regulation model, a weak environmental regulation model and a strong environmental regulation model to reveal the impact of environmental regulation on China’s regional total-factor energy efficiency (TFEE) during the period of 2003–2010. To take a further step, these three models are adjusted for calculating the correspondingly macro-economic cost of environmental regulation. The estimation results show that at present, the level of China’s environmental regulation is relatively low, and an enhancing of environmental regulation would lead to a sufficient increase of China’s regional TFEE with an enormous economic cost as its price. That means in China, the nationwide environmental stress is high, and the regulation cost is very huge. Strengthening environmental regulation would inevitably have some negative influences on China’s economy in the short run. Based on our findings, some corresponding policies are also proposed in this article.

An Empirical Analysis of the Regional Influence of FDI on Energy Efficiency in China

Based the panel data of China from 1997 to 2008, this paper constructed the regional total-factor energy efficiency (TFEE) by using the method of the data envelopment analysis (DEA) and then discussed the regional influence of FDI on local energy efficiency. The empirical results show that, FDI improved Chinese average level of energy utilization efficiency; the FDI inflow in the eastern region and the central region improved local energy efficiency, however, western area FDI reduced the energy efficiency. Some policy suggestions are also put forward for energy-saving and emission reduction target.

The Influence of FDI on Energy Efficiency of China: An Empirical Analysis Based on DEA Method

Based the panel data of China from 1997 to 2008, this paper computes the regional total-factor energy efficiency (TFEE) in China by using the method of the data envelopment analysis (DEA) and then discusses the influence of regional FDI on local energy efficiency. The empirical results show that, FDI improved China's average level of energy utilization efficiency by technical and structural effect channels; the FDI in the eastern region and the central region improved local energy efficiency, however, western area FDI reduced the energy efficiency.

Ecological total-factor energy efficiency of regions in China

Most existing energy efficiency indices are computed without taking into account undesirable outputs such as CO2 and SO2 emissions. This paper computes the ecological total-factor energy efficiency (ETFEE) of 30 regions in China for the period 2005–2009 through the slack-based model (SBM) with undesirable outputs. We calculate the ETFEE index by comparing the target energy input obtained from SBM with undesirable outputs to the actual energy input. Findings show that China's regional ETFEE still remains a low level of around 0.600 and regional energy efficiency is overestimated by more than 0.100 when not looking at environmental impacts. China's regional energy efficiency is extremely unbalanced: the east area ranks first with the highest ETFEE of above 0.700, the northeast and central areas follow, and the west area has the lowest ETFEE of less than 0.500. A monotone increasing relation exists between the area's ETFEE and China's per capita GDP. The truncated regression model shows that the ratio of R&D expenditure to GDP and the degree of foreign dependence have positive impacts, whereas the ratio of the secondary industry to GDP and the ratio of government subsidies for industrial pollution treatment to GDP have negative effects, on the ETFEE.

Regional total factor energy efficiency: An empirical analysis of industrial sector in China

The rapid growth of the Chinese economy has resulted in great pressure on energy consumption, especially the energy intensive sector – the industrial sector. To achieve sustainable development, China has to consider how to promote energy efficiency to meet the demand of Chinese rapid economic growth, as the energy efficiency of China is relatively low. Meanwhile, the appeal of energy saving and emission reduction has been made by the Chinese central government. Therefore, it is important to evaluate the energy efficiency of industrial sector in China and to assess efficiency development probabilities. The framework of total factor energy efficiency index is adopted to determine the discrepancy of energy efficiency in Chinese industrial sector based on the provincial statistical data of industrial enterprises above designated size in 30 provinces from 2005 to 2009, with gross industrial output as the output value and energy consumption, average remaining balance of capital assets and average amount of working force as the input values. Besides, in considerate of the regional divide of China, namely eastern, central, and western, and economic development differences in each region, energy efficiency of each region is also analysed in this paper. The results show that there is room for China to improve its energy efficiency, especially western provinces which have large amount of energy input excess. Generally speaking, insufficient technological investment and fail of reaching best scale of manufacture are two factors preventing China from energy efficiency promotion. Based on our findings, some policy implications on the improvement of energy efficiency, particularly for economically underdeveloped regions in China, are also discussed.

Total-factor energy efficiency of regions in Japan

This study computes the regional total-factor energy efficiency (TFEE) in Japan by employing the data envelopment analysis (DEA). A dataset of 47 prefectures in Japan for the period 1993–2003 is constructed. There are 14 inputs, including three production factors (labor employment, private, and public capital stocks) and 11 energy sources (electric power for commercial and industrial use, electric power for residential use, gasoline, kerosene, heavy oil, light oil, city gas, butane gas, propane gas, coal, and coke). GDP is the sole output. Following Fukao and Yue [2000. Regional factor inputs and convergence in Japan—how much can we apply closed economy neoclassical growth models? Economic Review 51, 136–151 (in Japanese)], data on private and public capital stocks are extended. All the nominal variables are transformed into real variables, taking into consideration the 1995 price level. For kerosene, gas oil, heavy oil, butane gas, coal, and coke, there are a few prefectures with TFEEs less than 0.7. The five most inefficient prefectures are Niigata, Wakayama, Hyogo, Chiba, and Yamaguchi. Inland regions and most regions along the Sea of Japan are efficient in energy use. Most of the inefficient prefectures that are developing mainly upon energy-intensive industries are located along the Pacific Belt Zone. A U-shaped relation similar to the environmental Kuznets curve (EKC) is discovered between energy efficiency and per capita income for the regions in Japan.

Total-factor energy efficiency of regions in China

This paper analyzes energy efficiencies of 29 administrative regions in China for the period 1995–2002 with a newly introduced index. Most existing studies of regional productivity and efficiency neglect energy inputs. We use the data envelopment analysis (DEA) to find the target energy input of each region in China at each particular year. The index of total-factor energy efficiency (TFEE) then divides the target energy input by the actual energy input. In our DEA model, labor, capital stock, energy consumption, and total sown area of farm crops used as a proxy of biomass energy are the four inputs and real GDP is the single output. The conventional energy productivity ratio regarded as a partial-factor energy efficiency index is computed for comparison in contrast to TFEE; our index is found fitting better to the real case. According to the TFEE index rankings, the central area of China has the worst energy efficiency and its total adjustmentof energy consumption amount is over half of China's total. Regional TFEE in China generally improved during the research period except for the western area. A U-shape relation between the area's TFEE and per capita income in the areas of China is found, confirming the scenario that energy efficiency eventually improves with economic growth.