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2011 | Buch

Benchmarking with DEA, SFA, and R

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Über dieses Buch

This book covers recent advances in efficiency evaluations, most notably Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) methods. It introduces the underlying theories, shows how to make the relevant calculations and discusses applications. The aim is to make the reader aware of the pros and cons of the different methods and to show how to use these methods in both standard and non-standard cases.

Several software packages have been developed to solve some of the most common DEA and SFA models. This book relies on R, a free, open source software environment for statistical computing and graphics. This enables the reader to solve not only standard problems, but also many other problem variants. Using R, one can focus on understanding the context and developing a good model. One is not restricted to predefined model variants and to a one-size-fits-all approach. To facilitate the use of R, the authors have developed an R package called Benchmarking, which implements the main methods within both DEA and SFA.

The book uses mathematical formulations of models and assumptions, but it de-emphasizes the formal proofs - in part by placing them in appendices -- or by referring to the original sources. Moreover, the book emphasizes the usage of the theories and the interpretations of the mathematical formulations. It includes a series of small examples, graphical illustrations, simple extensions and questions to think about. Also, it combines the formal models with less formal economic and organizational thinking. Last but not least it discusses some larger applications with significant practical impacts, including the design of benchmarking-based regulations of energy companies in different European countries, and the development of merger control programs for competition authorities.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction to Benchmarking
Abstract
This chapter gives a overview of the questions and methods covered in this book. What is the idea of efficiency analyses and benchmarking?Why do we benchmark? What are the state–of–the–art methods that we shall discuss in this book? The chapter is mainly conceptual and can be read with a minimum of technical skills. The idea is to get an elementary and intuitive introduction to the subject. Still, to get a flavor of the approach of the book, we do formalize a few simple production economic models.
Peter Bogetoft, Lars Otto
Chapter 2. Efficiency Measures
Abstract
In Chap. 1, we introduced efficiency as the use of the fewest inputs (resources) to produce the most outputs (services). This idea is fundamental to much of modern benchmarking literature because it allows us to evaluate performance without clearly defined preferences. That is, we avoid the difficult task of estimating preference functions and deciding on exact priorities. We will expand on this below.
Peter Bogetoft, Lars Otto
Chapter 3. Production Models and Technology
Abstract
In Chap. 1, we briefly introduced the concept of a production set or a technology as a way to characterize the production possibilities in a given application. This concept is crucial in advanced benchmarking because it defines the set of possible performance outcomes against which we can evaluate the actual performance of a given firm.
Peter Bogetoft, Lars Otto
Chapter 4. Data Envelopment Analysis DEA
Abstract
In this and the next chapter, we cover the basics and some additional material on Data Envelopment Analysis (DEA). DEA combines the estimation of the technology with the measurement of performance as related to this technology. It thereby integrates the two basic problems of a) defining a performance standard, the technology, and b) evaluating achievements against the established standard. There are several DEA methods that differ in terms of the estimated technology and the efficiency concept used. We will cover the most important ones and emphasize what unites the class of methods that make up DEA.
Peter Bogetoft, Lars Otto
Chapter 5. Additional Topics in DEA
Abstract
We covered the basics of DEA in the previous chapter. In this chapter, we will cover some additional topics that we find particularly relevant both to applications and to our understanding of DEA.
Peter Bogetoft, Lars Otto
Chapter 6. Statistical Analysis in DEA
Abstract
DEA is often classified as a non-statistical or deterministic approach that does not easily allow genuine hypothesis testing. Although DEA has not historically emphasized the use of traditional statistical tests, considerable progress has been made in this respect over the last 15 years. We will cover some important results in this chapter.
Peter Bogetoft, Lars Otto
Chapter 7. Stochastic Frontier Analysis SFA
Abstract
As explained in Chap. 1, there are two dominant approaches to modern benchmarking. One is the non-parametric, deterministic DEA approach discussed in some detail in the last three chapters; other is the stochastic frontier analysis (SFA), which we will cover in this and the next chapter. In the subsequent chapters, we will discuss a series of major applications of both approaches and examine the underlying benchmarking problem.
Peter Bogetoft, Lars Otto
Chapter 8. Additional Topics in SFA
Abstract
In this chapter, we continue our coverage of Stochastic Frontier Analysis (SFA).We extend the use of SFA to the estimation of general multi-input, multi-output productions functions and show how to estimate cost functions rather than the production functions that we focused on in Chap. 7. We also discuss hypothesis testing within an SFA framework.We conclude with a more methodological discussion of possible problems related to the use of SFA.
Peter Bogetoft, Lars Otto
Chapter 9. Merger Analysis
Abstract
The quantitative literature on productivity has focused mainly on measuring the efficiency of individual firms and organizations. The results demonstrate how much can be gained by individual improvements, by learning best practices and by designing appropriate incentive schemes at the firm level.
Peter Bogetoft, Lars Otto
Chapter 10. Regulation and Contracting
Abstract
One of the more prominent applications of state-of-the-art benchmarking is in the regulation of natural monopolies in general and electricity and gas networks, in particular. Benchmarking studies applied to inform such regulation has considerable economic impact on firms and consumers alike.
Peter Bogetoft, Lars Otto
Backmatter
Metadaten
Titel
Benchmarking with DEA, SFA, and R
verfasst von
Peter Bogetoft
Lars Otto
Copyright-Jahr
2011
Verlag
Springer New York
Electronic ISBN
978-1-4419-7961-2
Print ISBN
978-1-4419-7960-5
DOI
https://doi.org/10.1007/978-1-4419-7961-2

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