Showing papers on "Data envelopment analysis published in 1992"
TL;DR: In this article, a stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time, and the best predictor for the technical efficiency of an individual firm at a particular time period is presented for this timevarying model.
Abstract: Frontier production functions are important for the prediction of technical efficiencies of individual firms in an industry. A stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time. The best predictor for the technical efficiency of an individual firm at a particular time period is presented for this time-varying model. An empirical example is presented using agricultural data for paddy farmers in a village in India.
2,884 citations
TL;DR: In this paper, a partition of the optimal frontier into three parts corresponding to increasing, constant, and decreasing returns to scale is proposed, characterized in terms of optimal primal solutions and optimal dual solutions for both the original Charnes, Cooper, Rhodes model (1978) and the later Banker-Charnes-Cooper model (1984) and relying on concepts developed by R.D. Banker and R.M. Thrall.
702 citations
TL;DR: In this article, the authors studied the productivity growth during the deregulation of the Norwegian banking industry and found that productivity regress at the average bank prior to the deregulation, but rapid growth when deregulation took place.
Abstract: Productivity growth during the deregulation of the Norwegian banking industry is studied within the framework of Data Envelopment Analysis, which explicitly allows for multiple outputs. Introducing Malmquist indices for productivity growth, total growth can be decomposed into frontier growth and change in each bank's distance to the frontier. Both the total growth index and its components can be consistently chained over time. We find productivity regress at the average bank prior to the deregulation, but rapid growth when deregulation took place. Deregulation also led to less dispersion of productivity levels within the industry.
625 citations
Book•
01 Oct 1992
TL;DR: In this article, the authors present an overview of frontier efficiency concepts and data envelopment analysis in English local education authorities and a preliminary evaluation of the Peer Group of the DEA.
Abstract: Introduction. Motivation: Why DEA? Overview and Plan of the Book. An Introduction to Frontier Efficiency Concepts and Data Envelopment Analysis. Introduction. The Need for Weights in the Public Sector. The Nature of a Frontier Efficiency Comparison. The Measurement of Efficiency in Data Envelopment Analysis. Returns to Scale. Total Factor Productivity Measurement in English Local Education Authorities: A Non-Parametric Approach. Introduction. Measurement in the Public Sector. The Efficiency of Educational Production in English Local Education Authorities. A Preliminary Evaluation of the Peer Group. Appraisal. Appendix 3.1: Local Education Authority Data Set. Total Factor Productivity Measurement in Local Prisons and Remand Centres: A Further Application of Data Envelopment Analysis. Introduction. Analytical Background to Relative Efficiency Measurement. Empirical Investigation of Prison Efficiency. Inert Production: A New Interpretation with DEA. Conclusion. Appendix 4.1: Local Prisons and Remand Centres Data Set. Programme-Efficiency Implications of Data Envelopment Analysis. Introduction. The Cost Efficiency of a Multi-Branch Public Spending Programme: The Case of Local Prisons and Remand Centres. Evaluation of the Impact of a New Reference Technology on Branch and Programme Efficiency. Excess Costs and the Nesting of Empirical DEA Technologies. Additional Sources of Variation in Excess Costs: The Identification of Scale Inefficiences. Sensitivity of the Returns to Scale Measure. Conclusion. The Interpretation of Efficiency in Data Envelopment Analysis. Introduction. The Definition of Best-Practice. The Definition of Pareto Efficiency and the DEA Efficiency Score. A New Utility Basis for DEA Efficiency. The DEA Target as a Pareto Improvement. Some Remaining Difficulties with the DEA Target. Conclusion. Aspects of the Discriminating Power of Data Envelopment Analysis. Introduction. The Need for Clustering of LEA Performance. Results on LEA Efficiency after Clustering. Aspects of the Discriminating Power of DEA. Conclusion. A Conclusion and Appraisal. The Public Sector and DEA. Overview of the Empirical Results. Directions for Future Research. References. List of Tables. List of Figures.
276 citations
TL;DR: The paper illustrates the practical usefulness of the models developed and highlights the alternative measures of relative efficiency implicit in the modelsDeveloping models which can be used to estimate alternative input-output target levels to render relatively inefficient organisational units efficient.
276 citations
TL;DR: This study examines the relative strengths of two different methodologies - stochastic frontier models (SF) and data envelopment analysis (DEA) in estimating firm-specific technical efficiency and indicates that for simple underlying technologies the relative performance of the stochastics frontier models vis-a-vis DEA relies on the choice of functional forms.
268 citations
TL;DR: Yue et al. as mentioned in this paper used the DEA computer code to improve their paper and reported a significant improvement in the quality of the DEA's computer code, which led to a significant increase in the accuracy.
Abstract: Piyu Yue, a research associate at the IC2 Institute, University of Texas at Austin, was a visiting scholar at the Federal Reserve Bankof St. Louis when this article was written. Lynn Dietrich providedresearch assistance. The author would like to thank A. Charnes, Roll Fare and Shawna Grosskopf for theirconstructive comments and useful suggestions. Their DEA computer code led to a significant improvement ofthe paper
218 citations
TL;DR: In this paper, the authors applied the Data Envelopment Analysis (DEA) to a sample of public (government-owned) and not-for-profit hospitals operating in Michigan in 1982.
209 citations
TL;DR: In this paper, the sensitivity of the additive model's classifications in data envelopment analysis (DEA) is investigated by means of new DEA formulations focusing on the stability (sensitivity) of an organization's classification (whether efficient or inefficient).
Abstract: In contrast to existing sufficient conditions for preservation of efficiency under special perturbations and matrix structural assumptions, sensitivity of the additive model's classifications in data envelopment analysis (DEA) is investigated by means of new DEA formulations focusing on the stability (sensitivity) of an organization's classification (whether efficient or inefficient). The formulations for the additive model are linear programming problems whose solutions yield a particular region of stability, a ‘cell’, in which an organization's classification remains unchanged. The largest such cell can always be easily computed for each organization and additionally theoretically characterized simply as optimal solutions of particular linear programming problems.
192 citations
Abstract: This paper examines productivity growth in electricity retail distribution in Sweden in a multiple output-multiple input framework The approach used is nonparametric Data Envelopment Analysis (DEA) Productivity is measured by means of the Malmquist index Productivity comparisons are made between different types of ownership and between different service areas The study indicates a high rate of productivity growth, due to economies of density, when measured over a period of 17 years The results show no significant differences in productivity growth between different types of ownership or economic organization
177 citations
TL;DR: By using a single measure for each of these criteria, this paper provides a more robust indicator of transit peformance than the widely used multiple ratio analysis performed in the Irvine Performance Evaluation Method (IPEM).
Abstract: Governmental agencies need to be able to assess the performance of transit agencies and to compare them with peer agencies. This assessment must measure not only how efficient the agency is in producing transit service, but also how effective it is in having that service consumed. This paper uses data envelopment analysis (DEA) to develop a single measure for the efficiency and a single measure for the effectiveness of a transit agency relative to other agencies within the same peer group. By using a single measure for each of these criteria, this paper provides a more robust indicator of transit performance than the widely used multiple ratio analysis performed in the Irvine Performance Evaluation Method (IPEM). The DEA model is applied to two transit agency peer groups—one serving large metropolitan areas and the other serving relatively small cities and large towns.
TL;DR: The FRONTIER model as discussed by the authors provides maximum likelihood estimates for parameters of a number of stochastic frontier production function models, including the one described in this paper, with the most general model formulation.
TL;DR: In this article, the efficiency of the Norwegian district courts with the aim of suggesting ways of improving this efficiency is examined. And the questions of how the information from DEA can be used by the courts to become more efficient.
Abstract: This paper examines the efficiency of the Norwegian district courts with the aim of suggesting ways of improving this efficiency. Pooling the observations for the period 1983 to 1988 efficiency measures are calculated for each court using the nonparametric data envelopment analysis (DEA) method. The results show estimates of overmanning due to technical inefficiency. Comparisons are made between the specialized city courts and the generalized rural courts. When using the yearly observations Malmquist indices are calculated to estimate the rate of productivity change. Finally the paper addresses the questions of how the information from DEA can be used by the courts to become more efficient.
TL;DR: In this paper, the efficiency of electricity retail distributors in Sweden in a multiple output multiple input (MIMIMI) framework is examined using the nonparametric Data Envelopment Analysis (DEA) method.
Abstract: This article examines the efficiency of electricity retail distributors in Sweden in a multiple output multiple input framework. Productive efficiency measures are calculated by use of different versions of the non-parametric Data Envelopment Analysis (DEA) method. Comparisons are made between different types of ownership and between different types of service areas.
TL;DR: In this paper, composed error models for maximum likelihood estimation from nonparametrically specified classes of frontiers are proposed. But the problem of frontier estimation is not solved by using parametric functional forms, but by combining parametric and nonparametric approaches.
Abstract: In this paper we bring together the previously separate parametric and nonparametric approaches to production frontier estimation by developing composed error models for maximum likelihood estimation from nonparametrically specified classes of frontiers. This approach avoids the untestable restrictions of parametric functional forms and also provides a statistical foundation for nonparametric frontier estimation. We first examine the single output setting and then extend our formulation to the multiple output setting. The key step in developing the estimation problems is to identify operational constraint sets to ensure estimation from the desired class of frontiers. We also suggest algorithms for solving the resulting constrained likelihood function optimization problems.
TL;DR: In this article, Data Envelopment Analysis (DEA) was used to evaluate efficiency measures for the 45 distribution districts of the Greek Public Power Corporation (PPC) and compared with simple productivity indices used by PPC and with efficiency measures produced by econometric methods.
Abstract: In this paper Data Envelopment Analysis (DEA) is used to evaluate efficiency measures for the 45 distribution districts of the Greek Public Power Corporation (PPC). Results are derived under different sets of assumptions and are compared with simple productivity indices used by PPC and with efficiency measures produced by econometric methods. DEA scores appear to be more reliable than simple productivity indices. Comparison of the different cases explains the reason for the low efficiencies, which can be due to the management of controllable inputs, the design of the supply system or other environmental factors.
TL;DR: This paper employed data envelopment analysis to generate efficiency indices for individual nursing homes relative to a best-practice frontier and found that for-profit homes have higher mean levels of efficiency and a more efficient production frontier than nonprofit homes.
Abstract: This paper employs data envelopment analysis to generate efficiency indices for individual nursing homes relative to a best-practice frontier. Further analysis then shows that these ‘unadjusted’ indices represent factors other than efficiency. Regression analysis purges the indices of these confounding influences. The resulting ‘adjusted’ efficiency indices demonstrate that for-profit homes have higher mean levels of efficiency and a more efficient production frontier than non-profit homes. These results support the property rights hypothesis that forprofit homes are inherently more efficient than non-profit ones.
TL;DR: Very few (5 at most) of the candidates for overall efficiency were viable economic firms in 1985 and 1986, and strikingly different energy policy conjectures follow from this micro analysis than from the U.S. Department of Energy's macro analysis in its Energy Security study.
TL;DR: In this paper, various conditions that are imposed on the multipliers in a DEA analysis are examined, and an approach is suggested for breaking ties on the frontier. But this approach is not suitable for a large number of applications.
TL;DR: In this paper, Data Envelopment Analysis (DEA) can be used to track the performance of a selected supplier DEA modeling allows managers to consider not only financial and economic measures simultaneously, but also to incorporate quantitative measures of satisfaction.
TL;DR: In this paper, the data envelopment analysis (DEA) approach is applied to find the inefficient forest districts in Taiwan, ROC, and the Taiwan Forestry Bureau proposes three alternatives for reorganizing the thirteen districts into eight districts.
TL;DR: In this article, an empirical study that was employed in analyzing the operating productivities of a set of 44 bank branches of a major commercial bank offering relatively homogeneous products in a multi-market business environment was conducted.
Abstract: Productivity analysis and its strategic implications are not only important for manufacturing sector but equally essential for other sectors as well Branch banking sector is no exception in this sense and banks have to operate more efficiently and effectively in an increasingly competitive environment to sustain or improve their relative positions This paper discusses the methodology of an empirical study that was employed in analyzing the operating productivities of a set of 44 bank branches of a major commercial bank offering relatively homogeneous products in a multi-market business environment The methodology was based on the concepts and principles of Data Envelopment Analysis (DEA) The results of the study have indicated that this kind of productivity analysis is not only complementary to traditionally used financial ratios but also is a useful bank management tool in reallocating resources between the branches in order to achieve higher efficiencies
TL;DR: In this paper, the authors employed the data envelopment analysis method to evaluate the efficiency of the five bus firms in Taipei city, and concluded that the publicly owned Taipei Municipal Bus had increased (not increased) its technical efficiency after the government liberalized the urban bus market.
Abstract: This article has employed the data envelopment analysis method to evaluate the efficiency of the five bus firms in Taipei city. When vehicle kilometers (revenue or the measure combining vehicle kilometers, revenue and the number of traffic trips on routes) was used as the output measure, it concluded that the publicly owned Taipei Municipal Bus had increased (not increased) its technical efficiency after the government liberalized the urban bus market. This article also found that in both the one output (vehicle kilometers) and three outputs cases, Taipei Municipal Bus had, on an average, lower efficiency scores than the private firms, and that while each firm usually employed a linear production technology for several, consecutive years the private firms were more flexible in adopting different technologies.
TL;DR: In this paper, a data envelopment analysis/assurance region (DEA/AR) method was used to measure the industrial performance of 35 selected Chinese cities and explored the returns-to-scale (RTS) of these cities.
Abstract: The concept of allocative efficiency (AE) is discussed from the perspective of urban planning in China. The AE measurement is analytically achieved by data envelopment analysis/assurance region (DEA/AR) method. Using DEA/AR, this study illustrates the potential of AE to empirically measure the industrial performance of 35 selected Chinese cities. Besides the AE measurement, the current study explores the returns-to-scale (RTS) of these cities. The importance of the RTS measurement is that it does not assume uniqueness in its solution. This article thus presents an extended use of DEA in an attempt to improve the economic achievement within Chinese cities.
TL;DR: In this paper, the DEA model is used to evaluate the efficiency of health centres and to identify the most efficient ones, which can be used in the selection of those centres in which operational audits should be carried out.
Abstract: In this paper we have tried to evaluate the usefulness of the DEA model as a management tool when applied to the measurement of the efficiency of health centres. We have chosen the DEA model because it does not need prior specifications. This could be very useful when we lack data on costs. The overall evaluation of a number of health centres provides information on the distinctive features and comparative advantages of the most efficient ones. The information gathered could also be of great use in the selection of those centres in which operational audits should be carried out.
TL;DR: An effectively-designed algorithm for measuring technical, allocative and overall efficiencies, using data envelopment analysis (DEA) is presented, which takes advantage of unique features related to the DEA algorithm.
Abstract: This study presents an effectively-designed algorithm for measuring technical, allocative and overall efficiencies, using data envelopment analysis (DEA). The specially designed DEA code takes advantage of unique features related to the DEA algorithm. Computational efficiency of the proposed DEA algorithm is confirmed by a Monte Carlo simulation study.
TL;DR: In this article, the authors examine the relationship between the first two areas, i.e., analysis of firm and industry programming models of technology and performance, and compare the industry and firm models in a general programming form.
Abstract: Programming models of technology are enjoying a revival in several strands of literature. One such strand is the growing literature devoted to the assessment of firm performance based on the work of Farrell (1957) and the later popularized by Charnes, Cooper and Rhodes (1978) under the name of data envelopment analysis (DEA); for an early programming model, see Boles (1966). A second strand of literature seeks to model the industry production function and is associated with Johansen (1972), Fbrsund and Hjalmarsson (1987) and Aigner and Chu (1968). A third strand of literature uses programming techniques such as nonparametric tests of regularity conditions in production; see Afriat (1972), Hanoch and Rothschild (1972), Diewert and Parkan (1983) and Varian (1984). One of the purposes of this paper is to examine the relationship between the first two areas, i.e., analysis of firm and industry programming models of technology and performance. In order to compare the industry and firm models, we restate them in a general programming form, and ignore issues of functional form. Examination of these models in primal and dual form reveals that the industry approach constructs technology from firm data but allows (hypothetical) reallocation of aggregate resources across firms to yield an industry function. The firm models also construct technology from the data on all firms in the sample/industry, but do not allow for reallocation of inputs across firms. This suggests a natural hybrid: an industry model which allows for both firm specific inputs and inputs which can be reallocated across firms.' The paper unfolds as follows. We begin by presenting a stylized version of the Aigner and Chu and Johansen models of industry production. We
TL;DR: Methods of measuring economic efficiency of input-output systems by employing a fuzzy statistical approach are explored here in the context of the recent technique of data envelopment analysis, which utilizes a nonparametric approach to measure efficiency.
TL;DR: It is shown how efficiency scores differ when quality variables and/or operating income are included and the usefulness of DEA information to both the home administrator and chain managers for improving operating efficiency is demonstrated.
Abstract: Data envelopment analysis (DEA) is used to evaluate the relative technical efficiency and assist in the management of a chain of nursing homes. As with any DEA model, variables chosen are particularly important. The study looks at two possibly critical issues. The first is the appropriateness of models that include only financial and economic measures to evaluate administrators when quality care is an expected output. The second issue is the appropriateness of using noncontrollable variables, in this case operating income, to evaluate administrators. We show how efficiency scores differ when quality variables and/or operating income are included. We also demonstrate the usefulness of DEA information to both the home administrator and chain managers for improving operating efficiency.
01 Jan 1992