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An Introduction to Efficiency and Productivity Analysis is designed as a primer for anyone seeking an authoritative introduction to efficiency and productivity analysis. It is a systematic treatment of four relatively new methodologies in Efficiency/Production Analysis: (a) Least-Squares Econometric Production Models, (b) Total Factor Productivity (TFP) Indices, (c) Data Envelopment Analysis (DEA), and (d) Stochastic Frontiers. Each method is discussed thoroughly. First, the basic elements of each method are discussed using models to illustrate the method's fundamentals, and, second, the discussion is expanded to treat the extensions and varieties of each method's uses. Finally, one or more case studies are provided as a full illustration of how each methodology can be used. In addition, all four methodologies will be linked in the book's presentation by examining the advantages and disadvantages of each method and the problems to which each method can be most suitably applied. The book offers the first unified text presentation of methods that will be of use to students, researchers and practitioners who work in the growing area of Efficiency/Productivity Analysis.
The book also provides detailed advice on computer programs which can be used to calculate the various measures. This involves a number of presentations of computer instructions and output listings for the SHAZAM, TFPIP, DEAP and FRONTIER computer programs.

Inhaltsverzeichnis

Frontmatter

1. Introduction

Abstract
This book is concerned with measuring the performance of firms, which convert inputs into outputs. An example of a firm is a shirt factory which uses materials, labour and capital (inputs) to produce shirts (output). The performance of this factory can be defined in many ways. A natural measure of performance is a productivity ratio: the ratio of outputs to inputs, where larger values of this ratio are associated with better performance. Performance is a relative concept. For example, the performance of the factory in 1996 could be measured relative to its 1995 performance or it could be measured relative to the performance of another factory in 1996, etc.
Tim Coelli, D. S. Prasada Rao, George E. Battese

2. Review of Production Economics

Abstract
The primary purpose of this chapter is to provide a review of some key production economics results at the level one would expect an undergraduate economics student to achieve. This chapter draws heavily upon a number of economics textbooks, which are referenced throughout the chapter, especially Call and Holahan (1983) and Beattie and Taylor (1985).
Tim Coelli, D. S. Prasada Rao, George E. Battese

3. Additional Topics in Production Economics

Abstract
The production economics concepts discussed in Chapter 2 should provide sufficient background for many of the basic efficiency and productivity measurement methods discussed in this book. Much of the Chapter 2 material is similar to what one would be likely to encounter in an undergraduate microeconomics course. The present chapter reviews some additional, more advanced, production economics material. Our primary focus in this chapter is on duality and multiple-input, multiple-output distance functions. An appreciation of the material in this chapter will ensure a deeper understanding of the basic productivity and efficiency measurement methods, and will also assist with the interpretation of more advanced methods, such as the measurement of allocative efficiency using stochastic frontier cost functions, which is discussed in Chapter 9.
Tim Coelli, D. S. Prasada Rao, George E. Battese

4. Index Numbers and Productivity Measurement

Abstract
Index numbers are the most commonly used instruments to measure changes in levels of various economic variables. Index numbers relating to various economic phenomena are regularly compiled and published. The consumer price index (CPI), which measures the changes in prices of a range of consumer goods and services, is the most widely used economic indicator. Other important index numbers include the price deflators for national income aggregates; financial indices such as the All Ordinaries Index (Australia) and the Dow Jones Index (U.S.A.); and indices of import and export prices.
Tim Coelli, D. S. Prasada Rao, George E. Battese

5. Economic Theory and Index Numbers

Abstract
This chapter is primarily devoted to a detailed examination of the economic-theoretic foundations of the various index numbers discussed in Chapter 4. Given the importance attached to index numbers in TFP measurement, it is hardly surprising that economic theory is extremely relevant in understanding what these index numbers actually measure and in making a proper application of the formulae described. This chapter is also important in that it provides a base from which we integrate the three principal approaches, viz., the index number, DEA and stochastic frontier approaches, in the context of productivity and efficiency measurement.
Tim Coelli, D. S. Prasada Rao, George E. Battese

6. Efficiency Measurement Using Data Envelopment Analysis (DEA)

Abstract
This chapter is a pivotal chapter in this book. We now begin to explicitly consider the issue of inefficiency. In the previous four chapters we have discussed least squares econometric methods and index number methods, which implicitly assume that all firms are fully efficient. In the remaining chapters, we relax this assumption and describe methods which may be used to estimate frontier functions and measure the efficiencies of firms relative to these estimated frontiers.
Tim Coelli, D. S. Prasada Rao, George E. Battese

7. Additional Topics on Data Envelopment Analysis

Abstract
This chapter continues the discussion of data envelopment analysis (DEA) which began in the previous chapter. In the previous chapter, we introduced the efficiency measurement concepts of Farrell (1957) and described how they could be implemented using the linear programming approach known as DEA. We discussed the basic constant returns to scale (CRS) and variable returns to scale (VRS) DEA models from both the input- and output-orientations.
Tim Coelli, D. S. Prasada Rao, George E. Battese

8. Efficiency Measurement Using Stochastic Frontiers

Abstract
DEA and stochastic frontiers are two alternative methods for estimating frontier functions and thereby measuring efficiency of production. DEA involves the use of linear programming whereas stochastic frontiers involve the use of econometric methods.
Tim Coelli, D. S. Prasada Rao, George E. Battese

9. Additional Topics on Stochastic Frontiers

Abstract
The discussion in Chapter 8 focused upon a stochastic frontier model with the following characteristics:
  • the technical inefficiency effects, ui, had half-normal distribution;
  • it specified a Cobb-Douglas functional form;
  • it was a production function; and
  • it involved cross-sectional data.
Tim Coelli, D. S. Prasada Rao, George E. Battese

10. Productivity Measurement Using Efficiency Measurement Methods

Abstract
In this chapter we draw upon much of what has been covered in earlier chapters. We illustrate how, with access to suitable panel data, one can use the frontier estimation methods discussed in the previous four chapters to obtain estimates of TFP growth which do not require one to accept the restrictive assumptions inherent in the Tornqvist/Fisher index approach discussed in Chapter 5. That is, we do not need to assume that all firms are cost minimisers and revenue maximisers. This is of particular benefit when we are analysing public sector and not-for-profit organisations where these assumptions are unlikely to be valid.
Tim Coelli, D. S. Prasada Rao, George E. Battese

11. Conclusions

Abstract
Scattered throughout earlier chapters are a number of useful lists of points which summarise the characteristics and relative merits of the various methods that we have considered. The purpose of this final chapter is to bring together some of these lists so we can reflect upon them.
Tim Coelli, D. S. Prasada Rao, George E. Battese

Backmatter

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