An analysis of cost efficiency in Swiss multi-utilities

This study presents an empirical analysis of the cost efficiency of a sample of Swiss multi-utilities operating in the distribution of electricity, natural gas and water. The multi-utilities that operate in different sectors are characterized by a strong unobserved heterogeneity. Therefore the measurement of their performance poses an important challenge for the regulators. The purpose of this paper is to study the potential advantages of recently developed panel data stochastic frontier models in the measurement of the level of efficiency for multi-utility companies. These models are estimated for a sample of 34 multi-output utilities operating from 1997 to 2005. The alternative models are compared regarding the cost function slopes and inefficiency estimates. For the inefficiency estimates, the correlation between different models and the effect of econometric specification have been analyzed. The results suggest that the inefficiency estimates are substantially lower when the unobserved firm-specific effects are taken into account.     

基于随机前沿分析的配电网服务质量效率研究

为了解地理和气候因子对配电网的服务质量及效率的影响程度,采用基于Battese和Coelli(BC)模型的随机前沿分析(SFA)法,以我国2007~2010年117个配电网的平衡面板数据为例,分析了地理和气候因子对配电网服务质量效率的影响程度。为避免出现复共线性问题,运用因子分析法减少变量,使其转变为较少数量的复合因子,分别在有无复合因子的情况下评估了BC模型和固定效应模型,从而确定了可观测和不可观测的异质性对效率评估的影响效果。     

Efficiency and environmental factors in the US electricity transmission industry

The electricity industry in most developed countries has been restructured over recent decades with the aim of improving both service quality and firm performance. Regulated segments (e.g. transmission) still provide the infrastructure for the competitive segments and represent a significant share of the total price paid by final customers. However there is a lack of empirical studies that analyse firms' performance in the electricity transmission sector. In this paper an empirical analysis of US electricity transmission companies is conducted for the period 2001–2009. We use alternative stochastic frontier models that allow us to identify the determinants of firms' inefficiency. These models also permit us to control for weather conditions, potentially one of the most decisive uncontrollable factors in electricity transmission. Our results suggest that weather conditions clearly have an influence on transmission costs and that there is room for improvement in the management of US electricity transmission systems. Regulators should also be aware that more adverse conditions generate higher levels of inefficiency, and that achieving long-term efficiency improvements tends to worsen firms' short-term relative performance.     

Does environmental heterogeneity affect the productive efficiency of grid utilities in China?

China's electric power industry has experienced a reform whereby the generation sector is being opened up to competition but the transmission and distribution sectors are still under regulation. Efficiency and benchmarking analyses are widely used for improving the performance of regulated segments. The impact of observable environmental factors, together with unobservable characteristics, on efficiency has gained increasing attention in recent years. This study uses alternative stochastic frontier models combined with input distance functions to measure the productive efficiency of 29 grid firms of China over the period of 1993–2014 and investigates whether the observed environmental and unobserved heterogeneity factors affect the productive efficiency. The results indicate that adverse environmental conditions may bring negative influence to the production of grid utilities while the number of customers and the network length have positive impacts on the utilities' efficiency; Besides, the efficiency is sensitive to the model specification, which illustrates the presence of observed and unobserved heterogeneity; Moreover, there is no significant efficiency improvement in the grid utilities after the unbundling reform of 2002; Finally, the regional grids differ significantly in efficiency, and there is room for improvement, which could be achieved by incentive regulation taking due account of environmental heterogeneity.     

Generators' bidding behavior in the NYISO day-ahead wholesale electricity market

This paper proposes a statistical and econometric model to analyze the generators' bidding behavior in the NYISO day-ahead wholesale electricity market. The generator level bidding data show very strong persistence in generators' grouping choices over time. Using dynamic random effect ordered probit model, we find that persistence is characterized by positive state dependence and unobserved heterogeneity and state dependence is more important than unobserved heterogeneity. The finding of true state dependence suggests a scope for economic policy intervention. If NYISO can implement an effective policy to switch generators from higher price groups to lower price groups, the effect is likely to be lasting. As a result, the market price can be lowered in the long-run. Generators' offered capacity is estimated by a two-stage sample selection model. The estimated results show that generators in higher-priced groups tend to withhold their capacity strategically to push up market prices. It further confirms the importance of an effective policy to turn generators into lower price groups in order to mitigate unexpected price spikes. The simulated market prices based on our estimated aggregate supply curve can replicate most volatility of actual DA market prices. Applying our models to different demand assumptions, we find that demand conditions can affect market prices significantly. It validates the importance of introducing demand side management during the restructure of electricity industry.     

Estimating the potential for electricity savings in households

Improving efficiency in the use of energy is an important goal for many nations since end-use energy efficiency can help to reduce CO₂ emissions. Furthermore, since the residential sector in industrialised countries requires around one third of the end-use electricity, it is important for policy makers to estimate the scope for electricity saving in households to reduce electricity consumption by using appropriate steering mechanisms. We estimate the level of technical efficiency in the use of electricity using data from a Swiss household survey. We find an average inefficiency in electricity use by Swiss households of around 20 to 25%. Bottom-up economic-engineering models estimate the potential in Switzerland to be around 15%. In this paper we use a sub-vector input distance frontier function based on economic foundations. Our estimates lie at the upper end of the electricity saving potential estimated by the afore-mentioned economic-engineering approach.     

An incentive mechanism for electricity transmission expansion in Mexico

This study proposes an incentive regulatory framework for expanding electricity transmission in Mexico. A two-part pricing model is implemented within a combined merchant-regulatory structure. Three cases are considered. In the first, a monopolist with “postage stamp tariffs” serves the whole country using uniform prices. In the second case, one firm holds a regional monopoly in each of the five electricity areas. In the third, a monopolist operates in all areas of the national electricity system and discriminates in the prices it charges in each of the regions. This approach is described and then applied to the Mexican electricity transmission network. Using real data, the study compares all three cases in terms of profits, capacity increases, and network expansion. The results are found to depend on two effects: the “economies-of-scale effect”, in which the maximum level is reached with a single network; and the “discriminatory effect” that results when a firm can discriminate among types of consumers. The economies-of-scale effect produces greater capacity and network expansion, whereas the discriminatory effect increases profits.     

Identifying electricity-saving potential in rural China: Empirical evidence from a household survey

In recent years, there has been a fast-growing body of literature examining energy-saving potential in relation to electricity. However, empirical studies focusing on non-Western nations are limited. To fill this gap, this study intends to examine the electricity-saving potential of rural households in China using a unique data set from the China Residential Electricity Consumption Survey (CRECS) in collaboration with the China General Social Survey (CGSS), conducted nationwide at the household level in rural China. We use a stochastic frontier model, which allows us to decompose residential electricity consumption into the minimum necessary amount of consumption based on physical characteristics (e.g. house size, house age, number of televisions or refrigerators) and estimate the consumption slack (i.e. the amount of electricity consumption that could be saved), which depends on various factors. We find that rural households in China are generally efficient in electricity saving and the saving potential is affected by (fast) information feedback and social-demographic characteristics, instead of by the (averaged) electricity price, or energy efficiency labelling signals. In addition, we find no evidence of regional heterogeneity on electricity saving potential for rural households. Policy implications are derived.     

International benchmarking of electricity transmission by regulators: A contrast between theory and practice?

Benchmarking of electricity networks has a key role in sharing the benefits of efficiency improvements with consumers and ensuring regulated companies earn a fair return on their investments. This paper analyses and contrasts the theory and practice of international benchmarking of electricity transmission by regulators. We examine the literature relevant to electricity transmission benchmarking and discuss the results of a survey of 25 national electricity regulators. While new panel data techniques aimed at dealing with unobserved heterogeneity and the validity of the comparator group look intellectually promising, our survey suggests that they are in their infancy for regulatory purposes. In electricity transmission, relative to electricity distribution, choosing variables is particularly difficult, because of the large number of potential variables to choose from. Failure to apply benchmarking appropriately may negatively affect investors’ willingness to invest in the future. While few of our surveyed regulators acknowledge that regulatory risk is currently an issue in transmission benchmarking, many more concede it might be. In the meantime new regulatory approaches – such as those based on tendering, negotiated settlements, a wider range of outputs or longer term grid planning – are emerging and will necessarily involve a reduced role for benchmarking.     

Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach

Evaluating economy-wide energy performance is an integral part of assessing the effectiveness of a country's energy efficiency policy. Non-parametric frontier approach has been widely used by researchers for such a purpose. This paper proposes an extended non-parametric frontier approach to studying economy-wide energy efficiency and productivity performances by accounting for sectoral heterogeneity. Relevant techniques in index number theory are incorporated to quantify the driving forces behind changes in the economy-wide energy productivity index. The proposed approach facilitates flexible modelling of different sectors' production processes, and helps to examine sectors' impact on the aggregate energy performance. A case study of China's economy-wide energy efficiency and productivity performances in its 11th five-year plan period (2006–2010) is presented. It is found that sectoral heterogeneities in terms of energy performance are significant in China. Meanwhile, China's economy-wide energy productivity increased slightly during the study period, mainly driven by the technical efficiency improvement. A number of other findings have also been reported.     

Modelling of heterogeneities inside polymer electrolyte fuel cells due to oxidants

In present study, the influences of oxidants (concentration and stoichiometry factor) on the heterogeneities inside the polymer electrolyte fuel cells (PEFC) are analysed and modelled. In situ current density mapping technique is adopted to evaluate the heterogeneities. Heterogeneity factor is being introduced in present study to investigate the effects of the oxidants on the local performances. Local and mean performances of the fuel cells are analysed and modelled as a function of the air stoichiometry factor. It is observed that the minimum values of stoichiometry factors required for maintaining heterogeneities inside the fuel cells at the minimum level increase with the mean current density. Based on the experimental results, a model is being developed for determining the optimum values of air stoichiometry factor to maintain the heterogeneity inside the fuel cell at minimum level. The local performances of the fuel cells are investigated as a function of oxygen concentration at the cathode inlet. It is observed that the heterogeneities inside the fuel cell do not always increase with the decrease in the oxygen concentration at the cathode inlets. However, the heterogeneity factor always increases with the decrease in oxygen concentration.     

Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices

Non-linear autoregressive Markov regime-switching models are intuitive. Time-series approaches for the modelling of electricity spot prices are frequently proposed. In this paper, such models are compared with an ordinary linear autoregressive model with regard to their forecast performances. The study is carried out using German daily spot-prices from the European Energy Exchange in Leipzig. Four non-linear models are used for the forecast study. The results of the study suggest that Markov regime-switching models provide better forecasts than linear models.     

Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis

This study analyzes the electric and fuel energy efficiency for five different metal-based durable manufacturing industries in the United States over the time period 1987–2012, at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days HDD and cooling degree days CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. Own energy price elasticities range from −0.7 to −1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100% = best practice level) range from a low of 33% (fuel, NAICS 334 - Computer and Electronic Products) to 86% (electricity, NAICS 332 - Fabricated Metal Products). Electric efficiency is consistently better than fuel efficiency for all NAICS. Assuming that all plants in the least efficient quartile of the efficiency distribution achieve a median level of performance, we compute the decline in total energy use to be 21%. A Malmquist index is used to decompose the aggregate change in energy performance into indices of efficiency and frontier (best practice) change. Modest improvements in aggregate energy performance are mostly change in best practice, but failure to keep up with the frontier retards aggregate improvement. Given that the best practice frontier has shifted, we also find that firms entering the industry are statistically more efficient, i.e. closer to the frontier; about 0.6% for electricity and 1.7% for fuels on average.     

Cost of power outages for manufacturing firms in Ethiopia: A stated preference study

A reliable supply of electricity is essential for an operation of a firm. Nevertheless, in most developing countries electricity supply is highly unreliable. In this study, we estimate the cost of power outages for micro, small, and medium-sized enterprises in Addis Ababa, Ethiopia, using a stated preference survey. We find that the willingness to pay, and thus the cost of power outages, is substantial. The estimated willingness to pay for a reduction of one power outage corresponds to a tariff increase of 16 %. The willingness to pay for reducing the average length of a power outage by 1 h corresponds to a 33% increase. The compensating variation for a zero-outage situation corresponds to about three times the current electricity cost. There is, however, considerable heterogeneity in costs across sectors, firm sizes, and levels of electricity consumption. Policy makers could consider this observed heterogeneity when it comes to aspects such as where to invest to improve reliability, and introduce differentiated electricity contracts.     

Financial optimization in the Turkish electricity market: Markowitz's mean-variance approach

Electricity constitutes the input into many products that produced by industry and used by people. Hence, it can be considered as a product or service that has vital importance in human life and economy. Since it has such special properties of instantaneous production and consumption obligation and unfeasible storage, electricity market is not like other markets. In a competitive electricity market, generation company faces price risks and delivery risks. So that risk management is an important part of a generation company and can deeply effect companies’ profitability. This paper focuses on electricity generation asset allocation between bilateral contracts, such as forward contracts, and daily spot market, considering constraints of generating units and spot price risks. The problem is to find the optimal portfolio based on known electricity generation total costs, bilateral contract prices, it employed Turkish historical balanced market hourly system marginal and day-ahead hourly market prices between of 2006 and 2011. There are limited studies about portfolio optimization in electricity markets in literature and this paper should be considered frontier study taking spot market's hourly prices separately as risky assets. Markowitz mean-variance optimization which is claimed to be the beginning of modern portfolio theory in financial sector is used to demonstrate this approach. Mean-variance optimization has been successfully applied to all cases that modeled for electricity market. Some suggestions for future work are also listed in this paper.     

Manufacturing productivity and energy efficiency: a stochastic efficiency frontier analysis

This paper presents a mathematical model to estimate both production frontier and energy demand frontier, and evaluate the energy efficiency in the automotive manufacturing sector using plant‐level production and utility consumption data. By using the stochastic frontier analysis, two models—an output efficiency model (production frontier) and an input efficiency model (energy demand frontier)—are developed to analyze the plant's energy efficiency performance relative to the ‘best practice’ among peers. Both the structure and parameters of two stochastic frontier functions are identified to understand the relationship between production inputs (e.g., utilities and plant‐specific variables) and the overall productivity. A case study of a set of automotive engine manufacturing plants is conducted and shows that electricity has higher efficiency than other forms of utility in those production‐related activities, and the regional and climate factors have significant impacts on energy efficiency. The models provide a way to measure how far from the production frontier as well as how far from the energy demand frontier the plant is. The results also provide useful information about the inefficient energy components in manufacturing facilities. The opportunities of improving plant‐level efficiency in automotive manufacturing plants can be revealed by the results. Copyright © 2015 John Wiley & Sons, Ltd.     

Technology invention and adoption in residential energy consumption: A stochastic frontier approach

In this paper we analyse the electricity consumption of a set of four traditional ‘white goods’ in a panel of ten EU countries observed over the period 1995–2013 with the aim of disentangling the amount of technical efficiency from overall energy saving using a stochastic frontier approach. The efficiency trend is modelled as a function of energy efficiency policies and innovation dynamics that combines invention and adoption processes using specific patents weighted by granular production data and worldwide bilateral import flows. Our model also accounts for potential endogeneity arising when innovation processes and economic growth are considered. With this replicable approach, the stochastic frontier framework allows for explicit modelling of innovation processes. Our results show that the efficiency component is related to changes in the energy efficient technological content of appliances. The ‘international’ component represents a predominant share of technological advancement and exerts a significant influence on the transient efficiency. Our evidence calls for an active role to be played by policy makers in focusing on innovation and trade policies in order to achieve more ambitious energy efficiency targets.     

One price doesn't fit all: An examination of heterogeneity in price elasticity of residential electricity in India

Although well-designed consumer electricity pricing can improve access, contribute to higher metering, increase penetration of energy efficient technologies, limit extent of the rebound effect, and influence viability of electricity distribution utilities in India, there has been no comprehensive, policy-relevant assessment of price elasticities of electricity demand in the country. The objective of this study is to estimate price elasticity of residential electricity consumption and disaggregate it by state, rural and urban residence, and income categories to provide evidence for electricity tariff setting in India. We combine survey data from five rounds of nationally-representative household consumption expenditure surveys covering the period 2005–2012 with administrative data on electricity deficit and improve on methods applied in previous studies by estimating price elasticities using a quadratic form to account for constraints in electricity supply. We find that while the average price elasticity at the national level is −0.39 (95% confidence interval: −0.46, −0.31), it varies significantly by state, rural and urban residence, and income categories. Our results indicate that a “one ‘price’ fits all” policy may not be an effective approach to electricity tariff setting in India and a data-driven understanding of heterogeneities in price elasticities can better inform residential electricity tariff design in the country.     

Malmquist index measurement for sustainability enhancement in Chinese municipalities and provinces

This study discusses a use of DEA environmental assessment in a time horizon. We use a radial approach to examine a dynamic change of index measures related to China's regional development and industrial pollution prevention. In applying the proposed assessment to a time-series data, we need to examine components that produce a shift of an efficiency frontier in a time horizon. A unique feature of the proposed assessment is that it incorporates a framework of Malmquist index to examine the frontier shift among multiple periods. Here, the frontier shift indicates a progress potential on technology development and/or managerial improvement among observed periods. Thus, it is not an efficiency measure. Rather, the measurement eliminates inefficiency by shifting an organization to an efficiency frontier. In this study, the index is conceptually separated into 6 subcomponents, which are further disaggregated into 12 different elements (6 subcomponents × 2 disposability concepts) under natural and managerial disposability concepts. The proposed index measurement needs to consider a possible occurrence of a frontier crossover among different periods because technology diffusion on production activities usually has a time lag until it becomes really effective. Methodologically, this study conveys the message that DEA is an approximation method, so being not perfect. Therefore, it is necessary for us to use several different approaches (e.g., potential improvement by measuring a frontier shift and efficiency analysis) to obtain reliable empirical evidence. As an application, this study examines the level of sustainability related to 30 municipalities and provinces in China from 2003 to 2014. The following six policy implications are obtained in this study. First, all municipalities and provinces have made a considerable progress on their economies and pollution prevention efforts. Second, the effect of the frontier crossover is limited in China because they attain a high level of their potentials on economic development and pollution prevention. Of course, this effort is within the Chinese boundary, not international, because this study does not compare them with other industrial nations. Third, China needs to allocate its resources to western provinces at a level that it has used for coastal developments. Fourth, the government should reinforce efforts on environmental protection in central and southern regions. Fifth, the government has focused on the sustainability development in urban municipalities and provinces and then has gradually shifted the policy influence toward rural areas. Finally, different empirical results are confirmed by the potential analysis which consists of the Malmquist index measurement and the efficiency analysis. Both approaches need to be examined for future planning on Chinese regional development.     

Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model

This paper evaluates the operational activities of Chinese hydroelectric power companies over the period 2000–2010 using a finite mixture model that controls for unobserved heterogeneity. In so doing, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups among the hydro-power companies analysed, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with different technologies, suggesting that distinct business strategies need to be adapted to the characteristics of China's hydro-power companies. Some managerial implications are developed.