Chance-Constrained Efficiency Analysis

Data envelopment analysis (DEA) is extended to the case of stochastic inputs and outputs through the use of chance-constrained programming. The chance-constrained envelope envelops a given set of observations "most of the time." We show that the chance-constrained enveloping process leads to the definition of a conventional (certainty-equivalent) efficiency ratio (a ratio between weighted outputs and weighted inputs). Furthermore, extending the concept of Pareto and Koopmans efficiency to the case of chance-constrained dominance (to be defined), we establish the identity of the following two chance-constrained efficiency concepts: (i) the chance constrained DEA efficiency measure of a particular output-input point is unity, and all chance-constraints are binding; (ii) the point is efficient in the sense Pareto and Koopmans. Finally we discuss the implications of our approach for econometric frontier analysis.IC2 Institut

The assessment of dynamic efficiency of decision making units using data envelopment analysis

The concept of a "production function" as means to measuring efficiency began in 1928 with the seminal paper by Cobb and Douglas (1928). However, until the 1950s, production functions were largely used as a tool for studying the functional distribution of income between capital and labour. Farrell's argument (1957) provides an intellectual basis for redirecting attention from the production function specifically to the deviation from that function as a measure of efficiency. He developed a method so that we can measure efficiency in terms of distance to the "best DMU" on the frontier isoquant. Charnes, Cooper and Rhodes (1978) generalised Farrell's concept to multiple - input multiple - output situations and reformulated it using mathematical programming and thus derived an efficiency measurement known as Data Envelopment Analysis (DEA). Therefore DEA is a linear programming based method for comparing Decision Making Units (DMUs) such as schools, hospitals, etc. In the method originally proposed by Charnes, Cooper and Rhodes (1978) the efficiency of a DMU is defined as a ratio of the weighted sum of outputs to the weighted sum of inputs. Thus in the original DEA approach the notion of time dimension has been ignored. This thesis proposes a IDEA based method for assessing the comparative efficiencies of DMUs operating production processes where input - output levels are inter - temporally dependent. One cause of inter - temporal dependence between input and output levels is stock input which influences output levels over many production periods. Such DMUs cannot be assessed by traditional or 'static' DEA. The method developed in the study overcomes the problem of inter - temporal input - output dependence by using input - output 'paths' mapped out by operating DMUs over time as the basis of assessing them. The aim of this thesis is, therefore, firstly, to address that traditional or "static" IDEA fails to capture the efficiency of DMUs with inter - temporal input - output dependence. Secondly the thesis develops an approach for measuring efficiency under inter - temporal input - output dependence by defining an inter - temporal Production Possibility Set (PPS). The method developed uses path of input - output levels associated with DMUs rather than input - output DMUs observed at one point in time as static IDEA does. Using this PPS, an assessment framework is developed which parallels that of static DEA. The thesis develops mathematical programming models which use input - output paths to measure efficiency, identify peers and target of performance of DMUs. The approach is illustrated using simulated and real data

Data Envelopment Analysis and Commercial Bank Performance: A Primer with Applications to Missouri Banks

This paper describes a particular methodology called Data Envelopment Analysis (DEA), that has been used previously to analyze the relative efficiencies of industrial firms, universities, hospitals, military operations, baseball players and, more recently, commercial banks. The use of DEA is demonstrated by evaluating the management of 60 Missouri commercial banks for the period from 1984 to 1990.IC2 Institut

Azorean agriculture efficiency by PAR

The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimizing their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study, and, at the same time, to the need of timely and inexpensive information. The “Productivity Analysis with R” (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection and aggregation, and summarization and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez, 2008) and FEAR (Wilson, 2007). The DEA package performs some models of Data Envelopment Analysis presented in (Cooper et al., 2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in (Simar and Wilson, 2000). PAR is a software framework using a portfolio of models for efficiency estimation and providing also results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimization. PER framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self- explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al., 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of “good” practices and cluster of “less good” practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.N/

Efficiency frontier on Japanese banking system

Since the emergence of the efficiency frontier techniques, a series of comparisons between the methods that led to the resultant efficiency has been presented. In this paper, data from 99 Japanese banks are used in order to prove the applicability of efficiency frontier analysis on the East-Asian financial system and to reveal the differences between inter and intra-regional banks, showing the effect of the present financial crisis on the efficiency of the studied banks. DEA and FDH are used to determine the technical and scale efficiency of the analyzed banks and also it compares fully efficient banks by ranking them through the super-efficiency notion.This work was co-financed from the European Social Fund through the Sectoral Operational Programme Human Resources Development 2007–2013, project number POSDRU 159/1.5/S/134197 “Performance and excellence in doctoral and postdoctoral research in Romanian economics science domain”

Evaluating Greek equity funds using data envelopment analysis

This study assesses the relative performance of Greek equity funds employing a non-parametric method, specifically Data Envelopment Analysis (DEA). Using an original sample of cost and operational attributes we explore the e¤ect of each variable on funds' operational efficiency for an oligopolistic and bank-dominated fund industry. Our results have significant implications for the investors' fund selection process since we are able to identify potential sources of inefficiencies for the funds. The most striking result is that the percentage of assets under management affects performance negatively, a conclusion which may be related to the structure of the domestic stock market. Furthermore, we provide evidence against the notion of funds' mean-variance efficiency

PENGUKURAN KINERJA BANK KOMERSIAL BERDASARKAN PENDEKATAN EFISIENSI (STUDI TERHADAP PERBANKAN GO-PUBLIC DI INDONESIA)

This Study offers an application of non-parametric analitye technique (data envelopment analysis, DEA) in measuring the performance af the Indonesian banking sector. It explores the efficiency at Indonesia commercial bank with the use of a number of suggested financial eficiency ratio for the time period 2005-2007. In this way the purpored model offers an empirical reference sector comparing the inefficient banks with the efficient one. It departs from most frontier studies of bank performance, by using these suggested ratios as output measures and with no use of input measures. The purposed model is compare to be conventionally used input-output analysis as well as to the simple ratio analysis. It is shown that data envelopment analysis can be used as either an alternative or complement to the ratio analysis at an organization's performance. The study found 51.5% of Indonesia commercial banks run in efficient operation. Keyword: Commercial Bank, Efficiency, Data Envelopment Analysis

Canonical correlation analysis and DEA for azorean agriculture efficiency

In this paper we will document the application of canonical correlation analysis to variable aggregation using the correlations of the original variables with the canonical variates. A case study, about farms in Terceira Island, with a small data set is presented. In this data set of 30 farms we intend to use 17 input variables and 2 output variables to measure DEA efficiency. Without any data reduction procedure several problems known as “curse of dimensionality” are expected. With the data reduction procedures suggested it was possible to conclude quite acceptable and domain consistent conclusions.N/

Technical efficiency in electricity generation - the impact of smallness and isolation of island economies

Technical efficiency in electricity generation - the impact of smallness and isolation of island economie