Data Envelopment Analysis DEA

In general the undergraduate curriculum in statistics offers one semester basic course on linear programming (LP). The conventional course on LP includes simplex algorithm, duality theory, sensitivity analysis and some applications like the feedmix and transport problems. This outline seems to be distant from the mainstream curriculum in statistics. In order to partially overcome this shortcoming, we propose to introduce a technique based on linear programming called Data Envelopment Analysis (DEA) on the LP courses for students of statistics. DEA has gained momentum as a powerful complementary method for statistical tools in the research agenda as well as in practical activities of economic efficiency evaluation.

In general the undergraduate curriculum in statistics offers one semester basic course on linear programming (LP). The conventional course on LP includes simplex algorithm, duality theory, sensitivity analysis and some applications like the feedmix and transport problems. This outline seems to be distant from the mainstream curriculum in statistics. In order to partially overcome this shortcoming, we propose to introduce a technique based on linear programming called Data Envelopment Analysis (DEA) on the LP courses for students of statistics. DEA has gained momentum as a powerful complementary method for statistical tools in the research agenda as well as in practical activities of economic efficiency evaluation.

Banking system is one part of financial institution that plays an important role in economic growth and development of a country. The aim of this study was to assess the determinants of Ethiopian commercial banks efficiency. The study was based on secondary source of data. Quantitative data were obtained from published and audited financial statements of commercial banks in the period of 2003 –2012. To this end, measuring the efficiency of decision-making units (DMUs) has been growing in today’s banking system. The efficiency estimation of individual banks was evaluated using Data Envelopment Analysis (DEA). Likewise, to investigate the determinants of efficiency Tobit model was used. In Ethiopia banking industry embraces about nineteen commercial banks. Among which eight banks were selected as a sample size via purposive sampling techniques. The result of this study revealed deposit and liquidity has significant positive relationship with commercial banks efficiency.

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA (Data Envelopment Analysis) and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental aspect in incentive regulation schemes. In addition, this paper also addresses the problem of identifying outliers and influential observations in deterministic nonparametric DEA models.

In general the undergraduate curriculum in statistics offers one semester basic course on linear programming (LP). The conventional course on LP includes simplex algorithm, duality theory, sensitivity analysis and some applications like the feedmix and transport problems. This outline seems to be distant from the mainstream curriculum in statistics. In order to partially overcome this shortcoming, we propose to introduce a technique based on linear programming called Data Envelopment Analysis (DEA) on the LP courses for students of statistics. DEA has gained momentum as a powerful complementary method for statistical tools in the research agenda as well as in practical activities of economic efficiency evaluation.

The article presents a method for evaluating the efficiency of port container terminals. The research was conducted for nine European terminals which use different handling technologies. The terminals have been divided due to the level of automation of transport processes. In the efficiency research DEA (Data Envelopment Analysis) method is applied, that was previously used in studies of the relative productivity in the industry. This method allows you to multicriteria process analysis based on the properly selected production system model processing input parameters on output. Conclusions from analysis can be a ground for making a decision on organizational or investment issues.

The paper analyzes the allocation of health services to Brazilian states and regions. A relative service deficit indicator is constructed to achieve that goal, using equity-based criteria, which means equality of access for equal need. The Data Envelopment Analysis (DEA) is used to estimate the best service availabil ity frontier for equal need. The results show great differences in the availability of health services among Brazilian states and regions. In regional terms, the sit uation of the South is the best one, whereas the North experiences the worst deficit of health services. These disparities highlight the importance of deficit assessment as an instrument to guide public action, especially in the Brazilian context, where the coverage and availability of health services is a constitutional rule.

In this study, we use a three-stage analytical framework to analyse the productive efficiency of farms in the Batinah region. Data envelopment analysis (DEA) is employed to estimate the efficiency of the farms, together with a Tobit regression model and a production function to explain the variations in efficiency. The data used in this work are based on a survey of 60 randomly selected farm households. The results of the DEA stage showed an average technical efficiency of 0.42 for the sample farms, ranging from 0.12 to 1.00. At a subsequent stage, the efficiency scores were regressed on a set of selected contextual variables to identify possible sources of inefficiency. Tobit estimation failed to achieve statistical significance allowing a clear discrimination of the sources of inefficiency. A Cobb-Douglas production function was assumed, and analysis of the results helped to identify the specific operating factors affecting the variations in farming efficiency.

This paper analyses the efficiency and financial performance using CAMEL-type variables, three years before and after the consolidation programme for the domestic banking sector initiated by Bank Negara as a result of the 1997 financial crisis. The results suggest ...

In the Brazilian power sector, the transmission companies (TRANSCOS) receive revenues by the availability of their transmission facilities, regardless of the amount of the electric power transmitted. To promote their efficient operation the regulator periodically revises the revenue caps. The calculation of efficient operational costs is the first stage of the tariff revision process. Recently, the regulator agent published a resolution describing the methodology used to set the revenues of the Brazilian TRANSCOS. This algorithm includes a data envelopment model (DEA) which is described in this paper. In this work we propose an alternative DEA model and present a comparison of the results obtained by the two models.

Considering the fundamental role played by small and medium enterprises (SMEs) and especially from agricultural sector in the Greek economy and the considerable attention placed on factors associated with firms' effectiveness. The purpose of this study is to investigate the performance level of Greek agricultural firms during a period of economic turbulence on evidence from Greek agricultural firms and comparing with the period before the eruption of financial crisis. Little research has been carried out related to efficiency of agricultural firms especially for all regions (Floros et al., 2014). This empirical research using a sample data of 251 Greek agricultural SMEs, covering the time period of 2004-2011, measures the firm level technical efficiency of firms with the use of DEA analysis. The analysis classified firms according to their size into micro, small and medium. In addition, using DEA analysis it is attempted to rate the regions of Greece based on their firm efficiency. Further, financial ratios such as ROA, Market Share, Leverage, Liquidity, DEA scores, Fixed Assets/total Assets, Total sales/total assets, % Change in Sales are used in order to examine the financial performance of firms during pre-crisis period and post-crisis period. The results indicating that very small (micro) agricultural firms are more efficient during 2004-2011. In addition, it seems that Greek agricultural firms are less profitable and competitive in the post-crisis period, while they face lack of liquidity because of the economic turbulence of the country. Moreover, the eruption of financial crisis has impact on firm-level efficiency of Greek agricultural SMEs.

In general the undergraduate curriculum in statistics offers one semester basic course on linear programming (LP). The conventional course on LP includes simplex algorithm, duality theory, sensitivity analysis and some applications like the feedmix and transport problems. This outline seems to be distant from the mainstream curriculum in statistics. In order to partially overcome this shortcoming, we propose to introduce a technique based on linear programming called Data Envelopment Analysis (DEA) on the LP courses for students of statistics. DEA has gained momentum as a powerful complementary method for statistical tools in the research agenda as well as in practical activities of economic efficiency evaluation.

Data envelopment analysis (DEA) is a well-known technique for measuring the performance of homogeneous decision-making units (DMUs). Performances of DMUs can also be calculated by using some different techniques. Differential evolution (DE) is a versatile technique used for solving a wide range of problems occurring in various fields. In the present study, we propose a novel application of simple differential evolution (SDE) for solving data envelopment analysis-based models. The mathematical model of the problem is constrained in nature for which Pareto ranking method is embedded in SDE.

Abstract. In some data envelopment analysis (DEA) applications, some inputs of DMUs have negative values with positive cost. This paper generalizes the global cost Malmquist productivity index to compare the productivity of dierent DMUs with negative inputs in any two periods of times under variable returns to scale (VRS) technology, and then the generalized index is decomposed to several components. The obtained components are com-puted using the nonparametric linear programming models, known as DEA. To illustrate the generalized index and its components, a numerical example at three successive periods of time is given. c ⃝ 2014 IAUCTB. All rights reserved.

Evaluation of credit risk based on firm performance In this paper we investigate whether technical efficiency is an important ex-ante predictor of business failure. We use samples of French textiles, wood, and R&D companies to obtain efficiency estimates for individual firms in each industry. These efficiency measures are derived from a directional technology distance function constructed empirically using non-parametric Data Envelopment Analysis (DEA) methods. We summarize the effect of efficiency on the likelihood of default in terms of the franchise value hypothesis which states that more efficient firms will be less likely to fail. Estimating probit and logit regression models we find that efficiency has significant explanatory power in predicting the likelihood of default over and above the effect of standard financial indicators. Our empirical analysis also shows that caution needs to exercised when using the solvency ratio as an ex ante predictor of business failure.

This paper combines the CCR output-oriented model of data envelopment analysis (DEA) and Factor Analysis (FA) to evaluate the performance of academic units of a university's graduate programs relative to their counterparts nationally. We propose DEA/FA as a means of increasing the utility of DEA for policy decisions when there is uncertainty about the output constructs relevant to the programs. We discuss the concept that an academic program often maximizes the levels of some constructed outputs (CO), which may not themselves be directly observable. By means of FA, these COs can be deduced from the observable outputs, and can be expressed as a linear combination of observed and random components. Using the COs lessen the caveat of extreme specialization without the requirement for value judgements.

The purpose of this study is to examine the efficiency and its determinants of the Universities in Tanzania by means of deterministic frontier non-parametric approach. The analysis is based on a sample of 16 colleges and Universities 8 public, and 8 private across time period of 2008 - 2012 panel data. The data obtained from sampled universities, Tanzania Commission for Universities (TCU), Ministry of Education and Vocational Training (MoEVT) and the National Bureau of Statistics (NBS) are used. We include three inputs and three outputs in a two-stage data envelopment analysis (Wen-Bin-LIU et al (2013), first evaluating DEA scores and then regress them through Tobit regression model. The findings from the study suggest that there is variability of efficiency among Universities across years. It is revealed from the study that Universities are efficient in generating graduates through available human capital, whereas research publications and consultancy services are influential facto...

Supplying advanced technology defense systems and sustainability within the life cycle can be more costly and complex in terms of logistical processes day by day. Performance Based Logistics (PBL) is one of the new approaches to support and supply systems through supply chain and logistics. This approach focuses on importance to satisfying the needs of the end-user in terms of operational availability by taking into account the specific performance targets and with cost effectively. Many parametric and nonparametric methods are used for performance evaluation. The most preferred method of analysis among nonparametric methods is Data Envelopment Analysis (DEA). DEA is a linear programming-based method used to evaluate the performance and relative effectiveness of decision-making units. A real case study is carried out and the results are discussed.In the context of PDL strategy, a dynamic performance evaluation is performed by taking into consideration the data of the domestic batter...

A significant theme in data envelopment analysis (DEA) is the stability of returns to scale (RTS) classification of specific decision making unit (DMU) which is under observed production possibility set. In this study the observed DMUs are public postal operators (PPOs) in European Union member states and Serbia as a candidate country. We demonstrated a sensitivity analysis of the inefficient PPOs by DEA-based approach. The development of this analytical process is performed based on real world data set. The estimations and implications are derived from the empirical study by using the CCR RTS method and the most productive scale size concept (MPSS). First, we estimated the RTS classification of all observed PPOs. After that, we determined stability intervals for preserving the RTS classification for each CCR inefficient PPO under evaluation. Finally, scale efficient inputs and output targets for these PPOs are designated.

The occurrence of multiple optimal solutions is an important and interesting issue in data envelopment analysis (DEA), for it allows flexibility to estimate the optimal cross-efficiencies of all decision making units (DMUs). This paper uses the advantage of multiple optimal solutions, be in the cases of efficient and/or inefficient DMUs, to integrate both the first and second-order voices of all DMUs and proposes a most appreciative cross-efficiency DEA method. The paper deals with multiple optimal solution cases within the context of cross-efficiency models and suggest a model that is most appreciative for all DMUs being cross-evaluated by all others. The merits and appreciative superiority of the proposed method is proven theoretically; and illustrated practically through a ranking study chosen from the literature.

As transformações na economia internacional vêm atingindo em grande escala o setor bancário brasileiro. Para verificar o nível de competição no setor, e para investigar o desempenho comparativo entre os bancos brasileiros, aplicou-se o método da análise por envoltória de dados. Foram utilizados dados sobre o montante de capital dos proprietários, capital de terceiros, receita total e resultado do semestre de 144 instituições bancárias do país. Os bancos foram agrupados em três categorias: grande, médio e pequeno porte. Foi utilizada a abordagem da matriz BCG para enquadrar os diversos indicadores de eficiência operacional e de rentabilidade. Os resultados sugerem que os bancos de grande porte são os de melhor desempenho e os de pequeno porte os de pior desempenho.