List of Tables. List of Figures. Preface. 1. General Discussion. 2. The Basic CCR Model. 3. The CCR Model and Production Correspondence. 4. Alternative DEA Models. 5. Returns to Scale. 6. Models with Restricted Multipliers. 7. Discretionary, Non-Discretionary and Categorical Variables. 8. Allocation Models. 9. Data Variations. Appendices. Index.

Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software

http://d1c25a6gwz7q5e.cloudfront.net/papers/67.pdf

Efficiency of financial institutions: International survey and directions for future research

Estimation and inference in two-stage, semi-parametric models of production processes

http://people.stern.nyu.edu/wgreene/FrontierModeling/Reference-Papers/Greene-JE2005-Heterogeneity.pdf

Reconsidering heterogeneity in panel data estimators of the stochastic frontier model

This article designs a framework for evaluating the causes, consequences, and future implications of financial services industry consolidation, reviews the extant research literature within the context of this framework (over 250 references), and suggests fruitful avenues for future research. The evidence is consistent with increases in market power from some types of consolidation; improvements in profit eAciency and diversification of risks, but little or no cost eAciency improvement on average; relatively little eAect on the availability of services to small customers; potential improvements in payments system eAciency; and potential costs on the financial system from increases in systemic risk or expansion of the financial safety net. ” 1999 Elsevier Science B.V. All rights reserved.

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The consolidation of the financial services industry: Causes, consequences, and implications for the future

This work focuses on measuring and explaining producer performance. The contributors to this volume view performance as a function of the state of technology and economic efficiency. They show that insights can be gained by allowing for the possibility of a divergence between the economic objective and actual performance, and by associating this inefficiency with causal variables subject to managerial or policy influence. The book is derived from a series of lectures held on techniques and applications of the three approaches to the construction of production frontiers and measures of efficiency.

The measurement of productive efficiency : techniques and applications

1. Efficiency and Productivity 2. The Econometric Approach To Efficiency Analysis 3. DEA - The Mathematical Programming Approach to Efficiency Analysis 4. Statistical Inference in Nonparametric Frontier Models: Recent Developments and Perspectives 5. Efficiency and Productivity: Malmquist and More

The measurement of productive efficiency and productivity growth

In this paper we propose a new technique for incorporating environmental effects and statistical noise into a producer performance evaluation based on data envelopment analysis (DEA). The technique involves a three-stage analysis. In the first stage, DEA is applied to outputs and inputs only, to obtain initial measures of producer performance. In the second stage, stochastic frontier analysis (SFA) is used to regress first stage performance measures against a set of environmental variables. This provides, for each input or output (depending on the orientation of the first stage DEA model), a three-way decomposition of the variation in performance into a part attributable to environmental effects, a part attributable to managerial inefficiency, and a part attributable to statistical noise. In the third stage, either inputs or outputs (again depending on the orientation of the first stage DEA model) are adjusted to account for the impact of the environmental effects and the statistical noise uncovered in the second stage, and DEA is used to re-evaluate producer performance. Throughout the analysis emphasis is placed on slacks, rather than on radial efficiency scores, as appropriate measures of producer performance. An application to nursing homes is provided to illustrate the power of the three-stage methodology.

Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis

The ability of a production unit to transform inputs into outputs is influenced by its technical efficiency and external operating environment. This paper introduces a nonparametric, linear programming, frontier procedure for obtaining a measure of managerial efficiency that controls for exogenous features of the operating environment. The approach also provides statistical tests of the effects of external conditions on the efficient use of each individual input (for an input oriented model) or for each individual output (for an output oriented model). The procedure is illustrated for a sample of nursing homes.

Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency

This chapter begins with a brief discussion of variations in productive efficiency using airlines as an example. It then presents the main purpose of the book, which is to study inefficiency in production and its impact on economic and financial performance. The chapter then provides background material and focuses on hypotheses that have been proposed in literature that would explain variation in producer performance; lays the theoretical foundation for the measurement of productive efficiency; offers a brief introduction to alternative techniques that have been developed to quantify inefficiency empirically; introduces various econometric approaches to efficiency estimation; introduces variants of the mathematical programming approach to efficiency estimation; introduces the Malmquist productivity index and shows how to decompose it into various sources of productivity change, including variation in productive efficiency; and describes three ways of approximating a Malmquist productivity index: the use of superlative index numbers, the use of econometric techniques, and the use of mathematical programming techniques. An overview of the succeeding chapters is also presented

Harold O. Fried

Papers

The measurement of productive efficiency : techniques and applications

The measurement of productive efficiency and productivity growth

Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis

Incorporating the Operating Environment Into a Nonparametric Measure of Technical Efficiency

Efficiency and productivity