- Paperback: 296 pages
- Publisher: Kluwer Academic Publishers (30 Nov 1997)
- Language English
- ISBN-10: 0792380622
- ISBN-13: 978-0792380627
- Product Dimensions: 23.4 x 15.5 x 1.6 cm
- Amazon Bestsellers Rank: 3,809,510 in Books (See Top 100 in Books)
- See Complete Table of Contents
An Introduction to Efficiency and Productivity Analysis
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Product Description
Product Description
"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.
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First Sentence
This book is concerned with measuring the performance of firms, which convert inputs into outputs. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
This book is concerned with measuring the performance of firms, which convert inputs into outputs. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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4.8 out of 5 stars (5 customer reviews)
4 of 5 people found the following review helpful:
4.0 out of 5 stars
Graduate level book, 10 Nov 2006
By Mapster "Mapster" - Published on Amazon.com
This review is from: An Introduction to Efficiency and Productivity Analysis (Hardcover)
Im using this book for a class on the same topic as the name of the book. My prof is someone who is an expert on the topic and he knows the author well. In fact he's writing his own book. I find the topics advanced, maybe for senior level econ-math majors and more for graduate study. Reader must have a decent background in economics and mathematics to grasp concepts as the into, which was supposed to be a crash course in microecon would not be helpful to someone with no prior training.
2 of 3 people found the following review helpful:
5.0 out of 5 stars
An excellent introductory book on productivity measurement., 5 April 2008
By Jorge O. Pires - Published on Amazon.com
This review is from: An Introduction to Efficiency and Productivity Analysis (Hardcover)
This book covers three major approaches to productivity measurement, namely: Index Numbers, Data Envelopment Analysis and Stochastic Frontiers. Examples and applications are provided using software available from the authors' website for free. No doubt it's the best starting point for those who want to learn about the subject.
1 of 2 people found the following review helpful:
5.0 out of 5 stars
An introduction to efficiency and production analysis, 28 Mar 2008
By Kenji Inoue - Published on Amazon.com
This review is from: An Introduction to Efficiency and Productivity Analysis (Paperback)
I bought this book for using the Coelli's software of DEA. This text is useful for expanding the area of this type of study. We can get a manual of his program from the book's site, though. We are able to understand more easily how to put together many data.
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