An Introduction To Efficiency And Productivity Analysis
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An Introduction to Efficiency and Productivity Analysis
Author: Timothy J. Coelli
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
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.
Productivity and Efficiency Analysis
This book provides a coherent description of the main concepts and statistical methods used to analyse economic performance. The focus is on measures of performance that are of practical relevance to policy makers. Most, if not all, of these measures can be viewed as measures of productivity and/or efficiency. Linking fields as diverse as index number theory, data envelopment analysis and stochastic frontier analysis, the book explains how to compute measures of input and output quantity change that are consistent with measurement theory. It then discusses ways in which meaningful measures of productivity change can be decomposed into measures of technical progress, environmental change, and different types of efficiency change. The book is aimed at graduate students, researchers, statisticians, accountants and economists working in universities, regulatory authorities, government departments and private firms. The book contains many numerical examples. Computer codes and datasets are available on a companion website.
An Introduction to Efficiency and Productivity Analysis
Author: Timothy J. Coelli
language: en
Publisher: Springer Science & Business Media
Release Date: 2005-12-06
The second edition of this book has been written for the same audience as the first edition. It is designed to be a "first port of call" for people wishing to study efficiency and productivity analysis. The book provides an accessible introduction to the four principal methods involved: econometric estimation of average response models; index numbers; data envelopment analysis (DEA); and stochastic firontier analysis (SFA). For each method, we provide a detailed introduction to the basic concepts, give some simple numerical examples, discuss some of the more important extensions to the basic methods, and provide references for further reading. In addition, we provide a number of detailed empirical applications using real-world data. The book can be used as a textbook or as a reference text. As a textbook, it probably contains too much material to cover in a single semester, so most instructors will want to design a course around a subset of chapters. For example, Chapter 2 is devoted to a review of production economics and could probably be skipped in a course for graduate economics majors. However, it should prove useful to undergraduate students and those doing a major in another field, such as business management or health studies.