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The purpose of this paper is to estimate and compare the efficiency of several water utilities using three frontier techniques. Moreover, this study estimates the impact of several qualities of service variables on water utilities’ performance.

The paper utilizes three frontier techniques such as data envelopment analysis (DEA), stochastic frontier analysis (SFA) and stochastic non-parametric envelopment of data (StoNED) to estimate efficiency scores.

Efficiency scores for each methodological approach were different being on average, 0.745, 0.857 and 0.933 for SFA, DEA and StoNED methods, respectively. Moreover, it was evidenced that water leakage had a statistically significant impact on water utilities’ costs.

The choice of an adequate and robust method for benchmarking the efficiency of water utilities is very relevant for water regulators because it affects decision making process such as water tariffs and design incentives to improve the performance and quality of service of water utilities.

This paper evaluates and compares the performance of a sample of water utilities using three different frontier methods. It has been revealed that the choice of the efficiency assessment method matters. Unlike SFA and DEA, a lower variability was shown in the efficiency scores obtained from the StoNED method.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

By utilizing the two most commonly used approaches to generate “best practice frontier” to estimate efficiency of observed units, the purpose of this research paper is to estimate technical efficiency for total population of 200 Slovenian municipalities for the 2011 fiscal year.

Stochastic frontier analysis (SFA) and data envelopment analysis (DEA) methods are used to estimate technical efficiency levels. Namely, the majority of studies have utilized these two “traditional” approaches. Since the advantages of one method often represent the disadvantages of the other method, the two methods have been selected to compare the results obtained on the technical efficiency levels.

The results suggest that mean technical inefficiency should be approximately 22-25 percent (SFA method), whereas DEA method suggests the inefficiency in the range 12-18 percent. The DEA approach also suggests that the paper has many more technically efficient units compared to the SFA estimates. Nevertheless, the SFA assessment has revealed that, although on average the inefficiency should be larger compared to the DEA assessment, more than one-third of municipalities should exhibit relatively low levels of inefficiency (less than 5 percent).

This study utilizes both parametric as well as non-parametric approaches to assess the technical efficiency, which is not very common in the empirical literature. Besides, it focusses on the local government efficiency in a post-socialist country.

Outlines previous research on the efficiency of the Italian banking system, describes the structure of Italian banking groups and uses parametric (stochastic cost frontier) and non‐parametric (data envelopment analysis) approaches to assess the efficiency of Italian bank conglomerates in 1995 compared with the parent companies and subsidiearies. Explains the methodology and presents the results, which suggest that parent companies and subsidiaries are more efficient than groups and that efficiency is not related to size. Analyses efficiencies of scale and scope to show that bank groups gain more economies of scope than parents or subsidiaries; but finds mixed results for economies of scale.

The purpose of this paper is to study the production and efficiency of rice growers in drought prone areas with special attention given to economic and financial factors.

The authors use a parametric stochastic frontier approach and a non-parametric data envelopment analysis.

The study found that financial and liquidity constraints negatively influence production efficiency while off-farm work positively influences efficiency in drought prone areas.

Many biotic and abiotic factors affect the production efficiency of rice growers. Among abiotic stress, drought is the strongest constraint affecting nearly one third of the total rice area in Asia and causing significant economic losses. Farmers’ economic conditions and financial constraints further exacerbate the situation. However, very few studies have analyzed the efficiency in drought prone areas and the influence of economic and financial factors. This study contributes to in this regard by augmenting economic and financial factors in the efficiency estimation of drought prone areas using parametric and non-parametric approach.

This paper aims to evaluate the technical efficiency of the health-care systems in 21 selected middle-income countries during the period (2000–2017) and determine the source of inefficiency whether it is transient (short run) or persistent (long run).

The study uses the stochastic frontier analysis technique through employing the generalized true random effects model which overcomes the drawbacks of the previously introduced stochastic frontier models and allows for the separation between unobserved heterogeneity, persistent inefficiency and transient inefficiency.

Persistent efficiency is lower than the transient efficiency; hence, there are more efficiency gains that can be made by the selected countries by adopting long-term policies that aim at reforming the structure of the health-care system in the less efficient countries such as South Africa and Russia. The most efficient countries are Vietnam, Mexico and China which adopted a social health insurance that covers almost the whole population with the aim of increasing access to health-care services. Also, decentralization in health-care has assisted in adopting health-care policies that are suitable for both the rural and urban areas based on their specific conditions and health-care needs. A key success in the implementation of the adopted long-term policies by those countries is the continuous monitoring and evaluation of their outcomes and comparing them with the predefined targets and conducting any necessary modifications to ensure their movement in the right path to achieve their goals.

Although several studies have evaluated the technical efficiency both across and within countries using non-parametric (data envelopment analysis) and parametric (stochastic frontier analysis) approaches, to the best of the authors’ knowledge, this is the first attempt to evaluate the technical efficiency of selected middle-income countries during the period (2000–2017) using the generalized true random effects stochastic frontier analysis model.

The purpose of this paper is to estimate technical efficiency obtained from both data envelopment analysis (DEA) and stochastic frontier approaches using household survey data for rice farming households in Vietnam.

A bootstrap method is used to provide statistical precision of the DEA estimator. Technical efficiency is modeled as a function of household and production factors.

The results from the deterministic, semi‐parametric and parametric approaches indicate that among other things, technical efficiency is significantly influenced by primary education and regional factors. In addition, scale efficiency analysis shows that many farms in Vietnam are operating with less than optimal scale of operation.

The study is among the first that employ a bootstrap method and compare estimates from both Data Envelopment Analysis (DEA) and stochastic frontier approaches.

Testing the efficiency in the economy has been highly pronounced since the financial crisis in 2008, as many countries have started to deregulate their economic sectors. The potential impact of testing efficiency is thus the key driver of world output and welfare. For this purpose, the main objective of the Capital Market Authority consists of more regulation of securities trading to boost economic efficiency. In particular, the purpose of this paper, is to examine the efficiency of 40 investment companies in Kuwait. In this study, the authors investigate the efficiency in the investment sector in Kuwait. Studying such a case is important for several reasons. First, the investment sector in Kuwait is affected by the World Trade Organization (WTO) conditions and regulations for more market liberalization. Second, most studies on efficiency have focussed on developed countries, such as those of Europe and the USA, with very few studies examining developing countries, such as Kuwait. Third, the study efficiency features is important in helping policy makers evaluate how the investment sector will be affected by increasing competition and then formulate policies that affect that sector and the economy as a whole.

In this study, we use non-parametric data envelopment analysis (DEA) to estimate investment companies’ efficiency in Kuwait. The authors test predictions of the model using yearly data for 2006-2010. In the analysis, the authors follow the two-stage approach suggested by Coelli et al. (1998). In the literature on DEA efficiency score measurement, this two-stage approach is the most prominent. This approach uses the efficiency score, measured by the DEA model, as the dependent variable in a regression model with explanatory variables that are supposed to capture the impact of external factors (Hahn, 2007). In the second stage, the authors used a Tobit model to investigate factors affecting the efficiency in the Kuwaiti investment sector.

The findings of the second stage suggest that 2008-2010 had a negative impact on firms’ efficiency in Kuwait. The results confirm the substantial influence of the 2008 global financial crisis on the investment sector in Kuwait. In addition, the results show that factors affecting production efficiency in the investment sector in Kuwait include the total revenues, total assets, government participation, and Islamic firm dummy. These second-stage results are confirmed using different specifications of a fixed effect model, a random effects model, and a logit model.

The results may be utilized by both monetary authorities and policy makers in establishing the general economic policy in the country. A number of policy implications may be derived from the estimates obtained in the current paper. First, the results show that the investment sector in Kuwait faced a sharp drop in its efficiency in 2008 due to the global financial crisis. This result tells us that there was a spillover effect of the global financial crisis in the Kuwaiti investment market, as companies in this market are highly vulnerable to global shocks. As a result, the investment sector needs to be regulated by, for example, encouraging more company mergers and acquisitions. Second, to meet the appropriate regulations in the investment sector in Kuwait, monetary authority in Kuwait should take into consideration the WTO conditions for more openness in the economic sector. Therefore, companies in the investment sector should be more efficient to compete with foreign investment companies that decide to enter into Kuwaiti market. Therefore, the need for regulations in the Kuwaiti investment sector is more necessary than before. Third, the study of efficiency features is important to help policy makers evaluate how the investment sector will be affected by increasing competition and then formulate policies that affect that sector and the economy as a whole. Furthermore, monetary policy can play an important role in influencing the efficiency in the investment sector. Therefore, the Central Bank of Kuwait should take a leading role in regulating abnormal financial activity in the Kuwaiti market.

The aim of this paper is to investigate technical, scale, allocative and economic efficiencies by data envelopment analysis (DEA) and stochastic frontier methods to provide a decision‐making tool and managerial implications in the measurement of farm business performance and efficiency.

Technical, scale, allocative and economic efficiencies are analyzed with the Farm Accountancy Data Network (FADN) sample for 13 farm business branches in Slovenia in the period 1994‐2003. DEA models are used with an output‐orientation, three outputs and four inputs. The non‐parametric DEA estimations are compared with a parametric stochastic frontier approach. The cluster analysis is used to identify three different farm business groups according to their performance.

The average technical, scale, allocative and economic efficiencies for the whole FADN sample over the analyzed period are relatively high (around or over 0.90), suggesting that, although the FADN sample contains very different farms, the latter have similar management practices, and are similarly able to make the best use of the existing technology. Five farm branches (crop, dairy, livestock using own feed, fruit, and forestry) are fully efficient with respect to all four analyzed efficiency measures, suggesting that these specializations have the best chance to compete on the European and world markets.

Studies of technical, scale, allocative and economic efficiencies are rare for transitional farm businesses, especially in Slovenia. The research contributes to the crucial issue of whether small family farm businesses might be able to compete on international markets, as Slovenian agriculture is characterized by such structures.

Data envelopment analysis (DEA) and window analysis are used to follow the changes in Australian trading banks' pure technical efficiency, scale efficiency, and the nature of returns to scale. The main findings indicate declining average efficiency scores until 1991, followed by a steady rise thereafter. Pure technical inefficiency emerges as a greater source of inefficiency than scale inefficiency. Overall, regional banks exhibit increasing returns to scale and major trading banks exhibit decreasing returns to scale. Also worthy of note is the mixed size of banks operating at optimal returns to scale.