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Global climate change is a serious threat to the survival and development of mankind. Reducing carbon emissions and achieving carbon neutrality are the keys to reducing greenhouse gas emissions and promoting sustainable human development. For many countries, taking China as an example, the electric power sector is the main contributor to the country’s carbon emissions, as well as a key sector for reducing carbon emissions and achieving carbon neutrality. The low-carbon transition of the power sector is of great significance to the long-term low-carbon development of the economy. Therefore, on the one hand, it is necessary to improve the energy supply structure on the supply side and increase the proportion of new energy in the total power supply. On the other hand, it is necessary to improve energy utilization efficiency on the demand side and control the total primary energy consumption by improving energy efficiency, which is the most direct and effective way to reduce emissions. Improving the utilization efficiency of electric energy and realizing the low-carbon transition of the electric power industry requires synergies between the government and the market. The purpose of this study is to investigate the individual and synergistic effects of China’s low-carbon policy and the opening of urban high-speed railways (HSRs) on the urban electricity consumption efficiency, measured as electricity consumption per unit of gross domestic product (GDP).

This study uses a panel of 289 Chinese prefecture-level cities from the years 1999–2019 as the sample and uses the time-varying difference-in-difference method to test the relationship between HSR, low-carbon pilot cities and urban electricity consumption efficiency. In addition, the instrumental variable method is adopted to make a robustness check.

Empirical results show that the low-carbon pilot policy and the HSR operation in cities would reduce the energy consumption per unit of GDP, and synergies occur in both HSR operated and low-carbon pilot cities.

This study has limitations that would provide possible starting points for future studies. The first limitation is the choice of the proxy variable of government and market factors. The second limitation is that the existing data is only about whether the high-speed rail is opened or not and whether it is a low-carbon pilot city, and there is no more informative data to combine the two aspects.

The findings of this study can inform policymakers and regulators about the effects of low-carbon pilot city policies. In addition, the government should consider market-level factors in addition to policy factors. Only by combining various influencing factors can the efficient use of energy be more effectively achieved so as to achieve the goal of carbon neutrality.

From the social perspective, the findings indicate that improving energy utilization is dependent on the joint efforts of the government and market.

The study provides quantitative evidence to assess the synergic effect between government and the market in the low-carbon transition of the electric power industry. Particularly, to the best of the authors’ knowledge, it is the first to comprehend the role of the city low-carbon pilot policy and the construction of HSR in improving electricity efficiency.

In the early 1990s, the Thai government initiated a process of reform of the electricity industry with the argument that such reform would improve the performance of the industry and contribute to enhancing the overall economic prosperity. The purpose of this paper is to examine the veracity of this argument by analysing both the technical and environmental performance of the Thai electricity industry.

A data envelopment analysis‐based methodology is employed in this study to measure the productivity of the Thai electricity industry, for the period 1980‐2006. This method enables the decomposition of productivity changes into technical and efficiency changes, and hence enables one to determine if changes in productivity are due to electricity reform (efficiency gains) or due to autonomous technological improvements.

The study reveals that the increase in the productivity of the Thai electricity industry over the period 1980‐2006 was mainly driven by technological improvements and that industry reform has had insignificant impact on productivity. Further, the impacts of electricity reform on the environment appear to be relatively modest – this too was driven by government regulation that supports the use of less environmentally detrimental fuels for electricity generation by the private producers, rather than electricity reform.

The analysis in this paper contributes to the literature on productivity and efficiency, by applying the DEA method to a time series data for a single industry. Additionally, the analysis of environmental performance of the Thai electricity industry – to the best of knowledge of the authors – is the first of its kind for the Thai electricity industry.

The purpose of this paper is to demonstrate that overcapacity and tariff deficit (external constraints) negatively affect the efficiency of distribution firms in the Spanish electricity sector. To do this, the paper is based on the theory of constraints and theory of economic regulation.

Data envelopment analysis (DEA) window methodology is carried out on the constant scales (I-C) with a sample consisting of five main distribution firms during the period from 2006 to 2015. In turn, an analysis of the Malmquist index is carried out to assess whether it has had a displacement with respect to the efficiency frontier.

The results show that the overcapacity and the tariff deficit negatively affect the efficiency of the distribution firms of the Spanish electricity sector. In addition, there is an existence of external constraints that affect the activities of regulated organisations and the importance of adequate legislation in regulated sectors.

This study defines a model that shows how the efficiency problems associated with electricity distribution companies such as productive overcapacity or tariff deficit can be measured based on the theory of constraints and theory of economic regulation.

The objective of the present study is to evaluate and analyse the performance of Indian electricity distribution utilities post the implementation of landmark Electricity Act 2003.

Stochastic frontier analysis (SFA) that incorporates exogenous influences on operational efficiency is adopted in the present study. Specifically, a stochastic frontier production function model with a technical inefficiency effects model (Battese and Coelli, 1995) is chosen as a preferred model. In this model, the function that explains the inefficiency scores is estimated in a single stage with the production technology. This avoids the problem of inconsistency which is possible in the two-stage approach.

The sample involved 52 Indian electricity distribution utilities for seven-year period from 2006 to 2013. Major findings of SFA show that Indian electricity distribution utilities post the implementation of Electricity Act (2003) had, on average, experienced efficiency improvement during the observed period. The overall mean technical effciency score is estimated as 78.5% which indicates that there exist wide scope for effciency improvement in the sector. Further, the empirical findings also indicate that publicly owned distribution utilities obtain average technical efficiencies of 71.3%, which is lower than privately owned distribution utilities, which achieve average technical efficiencies of 85.7%.

Power supply quality indicators such as SAIFI, SAIDI, CAIFI, etc. and unobserved heterogeneity also influence the efficiency analysis of electricity distribution utilities. Hence, these parameters as explanatory variables can be incorporated in the future work.

The results obtained from this empirical study would likely be helpful for utility managers and policymakers to know how well they are performing, and how a better corporate strategy a particular utility can formulate to improve its operational efficiency and also its position in the marketplace.

This paper is amongst the first significant attempts that implement SFA approach to the panel dataset over a longer period of time – 2006 to 2013, so, as to evaluate and analyse the operational efficiency of Indian electricity distribution utilities in a single framework after the enactment of Electricity Act (2003). Unlike previous studies, this study investigates the degree to which various exogenous (or environmental) factors influence efficiency levels in these utilities.

The Indian power sector is dominated by coal. Environmental awareness and advances in techno-economic front have led to a slow but steady shift towards greener alternatives. The distributions of both fossil fuel resources and renewable energy potential are not uniform across the states. Paper attempts to answer how the states are performing in the sector and how the renewable energy and conventional resources are affecting the dynamics.

The authors employ a two-stage data envelopment analysis (DEA) to rank the performance of Indian states in the power sector. Multi-stage analysis opens up the DEA black-box through disaggregating power sector in two logical sub-sectors. The performance is evaluated from the point-of-view of policy formulating and implementing agencies. Further, an econometric analysis using seemingly unrelated regression equations (SURE) is conducted to estimate the determinants of total and industrial per-capita electricity consumption.

Efficiency scores obtained from the first phase of analysis happens to be a significant explanatory variable for power consumption. The growth in electricity consumption, which is necessary for economic wellbeing, is positively affected by both renewable and non-renewable sources; but conventional sources have a larger impact on per-capita consumption. Yet, the share of renewables in the energy mix has positive elasticity. Hence, the findings are encouraging, because development in storage technologies, falling costs and policy interventions are poised to give further impetus to renewable sources.

The study is one of the very few where entire spectrum of the Indian power sector is evaluated from efficiency perspective. Further, the second phase analysis gives additional relevant insights on the sector.

This study evaluates the efficiency and productivity change of 39 electricity distribution companies in Iran over the period 2005-2014. For purposes of electricity management and utilization of scarce resources, Iran’s 33 provinces have been classified into five regions by the Ministry of the Interior. Analyzing the efficiency of distribution companies across these regions yields significant understanding of these resources and helps policymakers to generate more informed decisions.

The proposed method of this study develops nonparametric data envelopment analysis (DEA) with the consideration of geographic classification, size and type of company. At the first stage, a DEA model is used to estimate the relative technical efficiency and productivity change of these companies. At the second stage, distributions of efficiency improvements are examined based on geographic classification, size and type of the company type. A stability test is also conducted to verify the proposed model’s robustness.

The results demonstrate that the average technical efficiency of the companies increased during the years 2006-2009, but decreased during 2010-2014. The productivity measurement reveals that low efficiency change was the largest contributor to the small increase in productivity change rather than technology change. In addition, testing the hypothesis that the large and small companies have statistically the same efficiency scores revealed no statistical difference among them. Moreover, another test did not detect a difference among companies at the urban and provincial levels.

By applying this approach, policymakers and practitioners in the power industry at the country and corporate level can effectively compare the efficiency and productivity changes among electricity distribution companies, and therefore generate more informed decisions.

The paper’s novel concept applies DEA to Iran’s electricity distribution companies and analyzes them by examining geographic classification, size and the type of the companies. In addition, a stability test is conducted and productivity changes are estimated.

The purpose of this paper is to determine the level of efficiency in the Mexico electricity industry during the 2008-2015 period.

A data envelopment analysis (DEA) network model is proposed, where technical efficiency is calculated. A factorial analysis using the principal components method was carried out first. Later, latent dimensions were calculated through the variance criterion and sedimentation graph, where four components were presented. After performing factor rotation, the nodes were grouped: generation, transmission, distribution and sales. It proceeded later to structure a DEA network model.

From the calculations made, the most efficient node was the transmission, while the North Gulf and East Center divisions were the only efficient.

The limitations presented in this study were data collection.

The implications that were observed were that through the results obtained, proposals can be made to the Mexican electricity sector to improve each of the nodes, and have a better operation and reduce energy losses.

The social impact of this type of study is that based on the results obtained, they present the basis for improving energy policy and users can have a better service that has better quality and coverage.

The originality of this study consists in the use of two methodologies, factor analysis methodology and DEA network model.

The paper seeks to evaluate the changes in efficiency and productivity of coal‐fired electricity generation of 30 Chinese administrative regions from 1999 to 2007.

The paper incorporates data envelopment analysis with the Malmquist index to study the progress made in this sector. The model considers both economic and environmental factors by including the variables fuel consumption, labor, capital, sulfur dioxide emissions and electricity generated. A second model is constructed without the variable sulfur dioxide emissions to evaluate economic performances without taking environmental measures into consideration.

By comparing the two models, the paper identified provinces that favored economic performance over environmental performance, or vice versa. Also, it showed that the more efficient provinces tend to manage both economic and environmental efficiencies equally well, while the reverse is true for the least efficient provinces. The average total factor productivity growth in coal‐fired electricity generation of all provinces was 3.96 per cent for 1999‐2007, and this growth is mainly attributed to technological change. In addition, it found that the Eastern provinces are the most efficient and productive of the group.

In the absence of provincial coal quality data, a key efficiency factor is missing from the analysis.

Efficiency improvement efforts in the Chinese generation sector should target the least efficient provinces identified in this paper. Practices in the most efficient provinces should be further investigated to be replicated when possible.

The paper provides a contemporary overview of Chinese provincial efficiency and productivity measures for policy makers and investors to improve China's coal‐fired electricity generation sector.

The purpose of this paper is to investigate relationships between five energy efficiency programs and electricity intensities in the US commercial buildings sector.

Regression methods analyze state-level secondary data from 2006 through 2009 to identify significant energy program drivers of electricity efficiency.

Combined, the five programs studied account for approximately nine percent reduction in commercial electricity intensity.

Outcomes will inform stakeholders’ decision-making regarding adoption or continuation of energy programs.

Electricity efficiency gains will help reduce negative environmental aspects and the present dependence on foreign oil.

Very little research has considered the impact of multiple programs on commercial electricity efficiency within their complex implementation environment.

The purpose of this paper is to evaluate the utility-level productivity changes in Indian electricity sector during a period that witnessed structural reforms through several landmark regulatory changes.

A transformed fixed-effect stochastic frontier panel approach accounting for time-invariant unobserved heterogeneity is employed to evaluate the productivity changes, and the inefficiency level in 98 utilities spanning over the years 2001–2010. A flexible translog production model is modeled and estimated, and decomposition of productivity into components of changes in efficiency, scale technology and price effect is computed.

The empirical findings obtained from the present study suggest that the utility-level productivity in Indian electricity sector has generally declined during the observed period of 2001–2010 specifically after the implementation of Electricity Act 2003. Also, it is estimated that the state-level un-bundling of the electricity sector is not significantly associated with utility-level efficiency change. Furthermore, efficiency improvements attributable to increased competition are observed only in the case of smaller gas-based generating utilities.

Earlier studies on the productivity evaluation of Indian electricity industry have applied the non-parametric data envelopment analysis approach, which has several limitations. The novelty of the paper lies in the fact that this paper is one of the first attempts that implement transformed fixed-effect stochastic frontier panel approach and thus disentangle unobserved heterogeneity from inefficiency. Furthermore, it is the only paper that analyzes 98 utilities (51 generating utilities, 38 transmission and distribution licensees and 9 vertically integrated utilities) in a single framework during the period 2001–2010.