The directional hybrid measure of efficiency in data envelopment analysis

The efficiency measurement is a subject of great interest. The majority of studies on DEA models have been carried out using radial or non-radial approaches regarding the application of DEA for the efficiency measurement. This paper, based on the directional distance function, proposes a new generalized hybrid measure of efficiency under generalized returns to scale with the existence of both radial and non-radial inputs and outputs. It extends the hybrid measure of efficiency from Tone (2004) to a more general case. The proposed model is not only flexible enough for the decision-maker to adjust the radial and non-radial inputs and outputs to attain the efficiency score but also avoids the computational and interpretive difficulties, thereby giving rise to an important clarification and understanding of the generalized DEA model. Furthermore, several frequently-used DEA models (such as the CCR, BCC, ERM and SBM models) which depend on the radial or non-radial approaches are derived while their results were compared to the ones obtained from this hybrid model. The empirical examples emphasize the consequence of the proposed measure

Calculating the scale elasticity in DEA models.

In economics scale properties of a production function is charcterised by the value of the scale elasticity. In the field of efficiency studies this is also a valid approach for the frontier production function. It has no good meaning to talk about scale properties of inefficient observations. In the DEA literature a qualitative characterisation is most common. The contribution of the paper is to apply the concept of scale elasticity from multi output production theory in economics to the piecewise linear frontier production function, and to develop formulas for calculating values of the scale elasticity for radial projections of inefficient observations. Illustrations also on real data are provided, showing the differences between scale elasticity values for the input- and output oriented projections and the range of values for efficient observations.Scale elasticity; DEA, production theory; Farrell efficiency measures

COOPER-framework: A Unified Standard Process for Non-parametric Projects

Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the ‘COOPER-framework’ a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly.DEA, non-parametric efficiency, unified standard process, COOPER-framework.

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”

Input, Output and Graph Technical Efficiency Measures on Non-Convex FDH Models with Various Scaling Laws: An Integrated Approach Based upon Implicit Enumeration Algorithms

In a recent article, Briec, Kerstens and Vanden Eeckaut (2004) develop a series of nonparametric, deterministic non-convex technologies integrating traditional returns to scale assumptions into the non-convex FDH model. They show, among other things, how the traditional technical input efficiency measure can be analytically derived for these technology specifications. In this paper, we develop a similar approach to calculate output and graph measures of technical efficiency and indicate the general advantage of such solution strategy via enumeration. Furthermore, several analytical formulas are established and some algorithms are proposed relating the three measurement orientations to one another.Data Envelopment Analysis, Free Disposal Hull, technical efficiency

New Models for Data Envelopment Analysis. Measuring Efficiency Outwith the VRS Frontier

Some models are presented in this paper which extend the concept of measuring superefficiency to the useful case of variable returns-to-scales (VRS), thus enabling the ranking of efficient as well as inefficient units. Two models, namely the Universal Radial Model and the Universal Additive Model, are presented that also have strong invariance properties (units and translation invariance). For both of these models a method for normalising the efficiency scores on a (0-1+) scale is presented. These models have been implemented in a software package and applied to the ranking of units in an industrial context.Data envelopment analysis (DEA), Superefficiency, Universal models

Market structure and hospital efficiency: Evaluating potential effects of deregulation in a national health service

In this article we examine the potential effect of market structure on hospital technical efficiency as a measure of performance controlled by ownership and regulation. This study is relevant to provide an evaluation of the potential effects of recommended and initiated deregulation policies in order to promote market reforms in the context of a European National Health Service. Our goal was reached through three main empirical stages. Firstly, using patient origin data from hospitals in the region of Catalonia in 1990, we estimated geographic hospital markets through the Elzinga--Hogarty approach, based on patient flows. Then we measured the market level of concentration using the Herfindahl--Hirschman index. Secondly, technical and scale efficiency scores for each hospital was obtained specifying a Data Envelopment Analysis. According to the data nearly two--thirds of the hospitals operate under the production frontier with an average efficiency score of 0.841. Finally, the determinants of the efficiency scores were investigated using a censored regression model. Special attention was paid to test the hypothesis that there is an efficiency improvement in more competitive markets. The results suggest that the number of competitors in the market contributes positively to technical efficiency and there is some evidence that the differences in efficiency scores are attributed to several environmental factors such as ownership, market structure and regulation effects.Geographic markets, market concentration, technical efficiency, data envelopment analysis, censored regression model