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1 – 10 of 492Zhichao Wang and Valentin Zelenyuk
Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were…
Abstract
Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.
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The consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the…
Abstract
Purpose
The consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.
Design/methodology/approach
Due to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.
Findings
The results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.
Originality/value
This research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.
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Maria Molinos-Senante, Alexandros Maziotis and Ramon Sala-Garrido
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Originality/value
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.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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).
Originality/value
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.
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Phong Hoang Nguyen and Duyen Thi Bich Pham
The paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when…
Abstract
Purpose
The paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when measuring cost efficiency. The purpose of the study is to assess the consistency in issuing policies to improve the cost efficiency of Vietnamese commercial banks.
Design/methodology/approach
The cost efficiency of banks is assessed through the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). Next, five tests are conducted in succession to analyze the differences in cost efficiency measured by these two methods, including the distribution, the rankings, the identification of the best and worst banks, the time consistency and the determinants of efficiency frontier. The data are collected from the annual financial statements of Vietnamese banks during 2005–2017.
Findings
The results show that the cost efficiency obtained under the SFA models is more consistent than under the DEA models. However, the DEA-based efficiency scores are more similar in ranking order and stability over time. The inconsistency in efficiency characteristics under two different methods reminds policy makers and bank administrators to compare and select the appropriate efficiency frontier measure for each stage and specific economic conditions.
Originality/value
This paper shows the need to control for heterogeneity over banking groups and time as well as for random noise and outliers when measuring the cost efficiency.
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Syed Manzur Quader and Michael Dietrich
Using a panel of 1,122 UK firms listed on the London Stock Exchange over the period of 1981-2009, corporate efficiencies are predicted in this paper as inverse proxies of agency…
Abstract
Purpose
Using a panel of 1,122 UK firms listed on the London Stock Exchange over the period of 1981-2009, corporate efficiencies are predicted in this paper as inverse proxies of agency cost and the agency cost hypotheses are tested. The paper aims to discuss this issue.
Design/methodology/approach
Stochastic frontier analysis is used to estimate corporate efficiency of firms, but from two different perspectives. The long-run and short-run corporate efficiencies are predicted focussing on modern approach of value maximization and traditional approach of profit maximization, respectively.
Findings
The estimation results reveal that, an average firm in the sample achieves 74.5 percent of its best performing peer's market value and 86.6 percent of its best performing peer's profit and both of them are highly significant in the analysis. The long-run market value efficiency supports the agency cost of outside equity and the short-run profit efficiency supports the agency cost of outside debt hypothesis. Also there is a positive rank correlation between these two efficiencies which confirms that an average firm in the UK suffers from inefficiency or agency conflicts to a certain extent, no matter whether the firm is driven by short-run or long-run growth perspectives.
Research limitations/implications
The predicted broad measures of agency costs in the paper have wider implications in enhancing the understanding of the UK firms’ corporate performance especially when they operate under a relatively free and market based governance and financial system.
Originality/value
The work is distinguished by the large panel of UK firms and a long period of time that is considered. Emphasizing on the empirical implications of the distinctions between short-run and long-run efficiency is also novel.
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Thanh Ngo and David Tripe
This paper aims to examine alternative methods for recording and treating costs in studies of bank efficiency.
Abstract
Purpose
This paper aims to examine alternative methods for recording and treating costs in studies of bank efficiency.
Design/methodology/approach
This study used stochastic frontier analysis (SFA) models with core costs and total costs to estimate the cost efficiency of banks in two different economies, Vietnam where the banking system is under-developed (and thus is dominated by traditional banking activities) and New Zealand where the banking system is well-developed (and thus non-traditional banking activities play an important role).
Findings
The authors found that models using total cost tend to underestimate the banks’ cost efficiency. This underestimation relates to the extent of modern activities in a banking system: it is larger in an advanced banking system (i.e. New Zealand) and smaller in a less-developed banking system (i.e. Vietnam).
Research limitations/implications
Research is limited to two countries, and it would be useful to apply the same technique to other data sets.
Practical implications
The paper suggests a new approach to cost SFA studies in banking.
Originality/value
The paper provides a much more searching analysis of costs in banking than has generally been seen in previous research.
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Jiao Yan, Chunlai Chen and Biliang Hu
The purpose of this paper is to analyze the relationship between farm size and agricultural production efficiency from the aspects of output and profit in order to find an optimal…
Abstract
Purpose
The purpose of this paper is to analyze the relationship between farm size and agricultural production efficiency from the aspects of output and profit in order to find an optimal farm size that achieves both output and profit efficiency in agricultural production in China.
Design/methodology/approach
This study uses the 2012 China Family Panel Studies survey data and employs the stochastic frontier analysis (SFA) models to investigate empirically the relationship between farm size and agricultural production efficiency.
Findings
The study finds that there is an inverted-U curve relationship between farm size and output efficiency and a U-shaped curve relationship between farm size and profit efficiency in agricultural production in China. Based on the empirical results, the study estimates that the appropriate farm size is around 10–40 mu and the optimal farm size is around 20–40 mu both in terms of output efficiency and profit efficiency in Chinese agricultural production under the current agricultural technology and land management system.
Practical implications
The findings of this study suggest that appropriate land consolidation will bring more benefits to farmer households and agricultural production efficiency. There are some policy implications. First, governments should give long term and more stable land using rights to farmers through extending the period of land contract and verifying land using rights. Second, governments should encourage transfers of land using rights and promote land consolidation. But the implementation of this policy should consider regional differences and not be used for blindly pursuing increasing land size. Third, land consolidation should be accompanied with the development of specialized agricultural services.
Originality/value
The paper makes two major contributions to the literature. First, the authors use the SFA model to investigate the relationship between land size and agricultural production efficiency. Second, the authors establish two SFA models – the stochastic frontier output analysis model and the stochastic frontier profit analysis model – to estimate the optimal land size to achieve both output and profit efficiency of agricultural production in China.
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Shrimal Perera and Michael Skully
Since there is no agreement on the consistency of their estimates, the purpose of this paper is to investigate whether parametric stochastic frontier analysis (SFA) and…
Abstract
Purpose
Since there is no agreement on the consistency of their estimates, the purpose of this paper is to investigate whether parametric stochastic frontier analysis (SFA) and nonparametric data envelopment analysis (DEA) generate consistent bank efficiency assessments.
Design/methodology/approach
The authors utilize four alternative efficiency computation models: two DEA technical efficiency models based on constant and variable returns to scale, and two SFA cost efficiency models employing Translog and Fourier functional specifications. An unbalanced panel of 59 Indian banks over 1990‐2007 is employed as a model, developing country, banking market.
Findings
The Translog and Fourier specifications in SFA and the constant and variable returns to scale assumptions in DEA are found to rank and identify “best‐practice” and “worst‐practice” approximately in the same order. The association between DEA efficiency estimates and non‐frontier standard performance measures, however, is mixed and inconclusive. Unlike DEA scores, SFA efficiency assessments were found to be consistent with cost and profit ratios and hence are “believable”.
Practical implications
For regulators and bankers alike, the authors' findings highlight the importance of investigating the consistency of efficiency scores across various research methods. They should ensure that frontier‐based efficiency assessments are not simply “artificial constructs” of models' assumptions/specifications.
Originality/value
This paper extends the existing literature by checking jointly the statistical consistency of both DEA technical efficiency scores and SFA cost efficiency scores. The prior studies focus either on technical efficiency or cost efficiency, but not both. Moreover, as far as the authors are aware, this is the first cross‐methodological validation study to focus on bank efficiency in the context of a developing country banking market.
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While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely…
Abstract
Purpose
While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions.
Design/methodology/approach
A literature survey.
Findings
While there are many useful applications of SFA to econometrics, there are also many important open problems.
Originality/value
This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.
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