Book Description
The second edition of
An Introduction to Efficiency and Productivity Analysis is designed to be a general introduction for those who wish to study efficiency and productivity analysis. The book provides an accessible, well-written introduction to the four principal methods involved: econometric estimation of average response models; index numbers, data envelopment analysis (DEA); and stochastic frontier analysis (SFA). For each method, a detailed introduction to the basic concepts is presented, numerical examples are provided, and some of the more important extensions to the basic methods are discussed. Of special interest is the systematic use of detailed empirical applications using real-world data throughout the book.
In recent years, there have been a number of excellent advance-level books published on performance measurement. This book, however, is the first systematic survey of performance measurement with the express purpose of introducing the field to a wide audience of students, researchers, and practitioners. Indeed, the 2
nd Edition maintains its uniqueness: (1) It is a well-written introduction to the field. (2) It outlines, discusses and compares the four principal methods for efficiency and productivity analysis in a well-motivated presentation. (3) It provides detailed advice on computer programs that can be used to implement these performance measurement methods. The book contains computer instructions and output listings for the SHAZAM, LIMDEP, TFPIP, DEAP and FRONTIER computer programs. More extensive listings of data and computer instruction files are available on the book's website: (www.uq.edu.au/economics/cepa/crob2005).
Customer Reviews:
Graduate level book.......2006-11-10
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.
efficiency and productivity analysis`.......2006-11-06
I am very happy to receive my order even before the expected date. it was in good order.
An Introduction to Efficiency and Productivity Analysis.......2005-07-19
A complete and an excellent book that provides the gist to efficiency and productivity analysis, and surely an important and particularly a very useful resource to those involve in study/research of the field.
Book Description
About two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events in the light of accumulating evidence. Though his method has extensive applications to the work of economists, it is only recent advances in computing that have made it possible to exploit its full power.In this new and expanding area, Tony Lancaster 's text provides a comprehensive introduction to the Bayesian way of doing applied economics. Using clear explanations and practical illustrations and problems, the text presents innovative, computer-intensive ways for applied economists to use the Bayesian method. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.
Customer Reviews:
Good book!.......2007-04-12
I'm taking an intro to Bayesian stats class and we are using the Carlin & Louis book -- it is a POS.
I found this book in the library and it is much better. It gives very clear explanations of the ideas, and lots of concrete worked examples. Props to the author.
Clear as crystal and plenty of workouts.......2006-07-25
This is as clear as crystal. It also has plenty of workouts. It is a very useful volume.
Great Book.......2006-03-19
If you are looking for a book for Bayesian estimation, this is the one. The first several chapters say it all about Bayesian methods. The rest of the book is applications. Very helpful reading for learning the method.
Book Description
Recent years have seen a great variety of applications of DEA (Data Envelopment Analysis) for use in evaluating the performances of many different kinds of entities engaged in many different activities in many different contexts in many different countries. One reason is that DEA has opened up possibilities for use in cases which have been resistant to other approaches because of the complex (often unknown) nature of the relations between multiple inputs and multiple outputs involved in many of these activities (which are often reported in non-commeasurable units). Examples include the maintenance activities of U.S. Air Force bases in different geographic locations, or police forces in England and Wales as well as performances of branch banks in Cyprus and Canada and the efficiency of universities in performing their education and research functions in the U.S., England, and France. These kinds of applications extend to evaluating the performance of cities, regions and countries with many different kinds of inputs and outputs that include "social" and "safety-net" expenditures as inputs and various "quality-of-life" dimensions as outputs which, in turn, have led to dealing with important issues such as identifying sites for new locations (away from Tokyo) for the capital of Japan.
Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References has been carefully designed by the authors to provide a systematic introduction to DEA and its uses as a multifaceted tool for evaluating problems in a variety of contexts. The authors have been involved in DEA's development from the beginning. William Cooper (with Abraham Charnes and Edwardo Rhodes) is a founder of DEA. Lawrence Seiford and Kaoru Tone have been actively involved as researchers and practitioners from its earliest beginnings. All have been deeply involved in uses of DEA in practical applications as well as in the development of its basic theory and methodologies. The result is a textbook grounded in authority, experience and substance.
Book Description
This Second Edition of the highly acclaimed introduction to econometrics retains its comprehensive nature and strong authorship, while incorporating much new material. New to this edition are a complete treatment of Bayesian inference, sampling theory, an appendix on linear algebra, and a computer handbook. Presentation covers modern statistical models and focuses on the sampling theory process by which the data were generated, and the statistical consequences of alternative decisions under uncertainty. Asymptotics are introduced early on, for use throughout. Includes at least one applied example to illustrate each model, and contains many analytical and numerical exercises.
Customer Reviews:
Introduction to the Theory and Practice of Econometrics.......2000-05-12
The book is excellent for the mathematically inclined student who masters well linear lagebra. It uses matrix notaion extensively and enables one to generalize results without getting lost. I used that book in my intermediate econometrics course at the undergraduate level. I am convinced it is a mistake to start learning econometrics by first using the algebraic approach then the matrix approach. This only brings about confusion. This book is excellent as when one thinks hard through theoretical results it is much easier to get a good grasp of the empirical results one finds in applied work. I always consult this book first when I am a bit rusty in classical and special topics in econometrics. The book is not up to date to more modern econometrics such as cointegration and unit root analysis (those subjects don't exist in it).
Book Description
In An Introduction to Classical Econometric Theory Paul A. Ruud shows the practical value of an intuitive approach to econometrics. Students learn not only why but how things work. Through geometry, seemingly distinct ideas are presented as the result of one common principle, making econometrics more than mere recipes or special tricks. In doing this, the author relies on such concepts as the linear vector space, orthogonality, and distance. Parts I and II introduce the ordinary least squares fitting method and the classical linear regression model, separately rather than simultaneously as in other texts. Part III contains generalizations of the classical linear regression model and Part IV develops the latent variable models that distinguish econometrics from statistics. To motivate formal results in a chapter, the author begins with substantive empirical examples. Main results are followed by illustrative special cases; technical proofs appear toward the end of each chapter. Intended for a graduate audience, An Introduction to Classical Econometric Theory fills the gap between introductory and more advanced texts. It is the most conceptually complete text for graduate econometrics courses and will play a vital role in graduate instruction.
Customer Reviews:
Another excellent econometric textbook.......2007-07-23
This is another good, modern textbook on parametric, cross-sectional econometrics (don't look for non/semi-parametric or time-series econometrics in here). It is, I think, in the same league as Wooldridge, which is however less technical and spends more time describing empirical applications. I think Ruud is a very nice addition to an econometric shelf. The notation is good, and the math/stat appendix is one of the best I have ever seen (the section on multivariate differentiation in particular is outstanding and very useful). Overall, if you want to have 3 *relatively* basic books on parametric cross-section econometrics, I think this is a good companion to Wooldridge and Cameron and Trivedi (a nice compendium of applied tools, which also includes some non-parametrics, for which the best introduction is likely Pagan and Ullah). If time-series is important to you, Hayashi is a good choice. As you may have guessed, I am not a big fan of Greene, which I do own but never look at.
nice.......2006-02-04
here we have just another big graduate textbook. the style reminds me of simon/blume (brrrr): a lot of material, reader likes it, solves the excercises (ahh I'm doing econometrics) and is left without a clue. at least for me ;) I think most of the 1000 pages is quite useless. too many distracting pictures and the proofs are either 'technical' (i.e. boring and dispensable) or very intuitive. most of the details you forget anyway. hopefully, since i find all the padding very confusing. don't get me wrong, intuition is very good but the term is short and the next one is probably harder => buy a maths book instead!
The book is OK, but not good really.......2001-09-01
I gave it a one-star to balance those biased 5 stars. The first part of the book is pretty good, intuitively explains what an OLS regression is really like geometrically. The second part of the book is just horrible. The author just goes on and on and on without being able to clearly explain the theories. The book is used in my program for one year and then stopped. Now we use Yamashi's book, which is much better.
Simply the Best.......2001-01-19
I have just completed reading Professor Ruud's textbook from cover to cover. It is the clearest, most insightful graduate-level econometrics book I have read. Whereas many texts seem to be compendiums of theorems and proofs with little in the way of explanation, Ruud takes the time to explain things thoroughly. At over 800 pages, however, Ruud's book is never verbose. A good explanation takes time, but Ruud never takes more time than is needed. Yet, in addition to all concepts being thoroughly explained, they are introduced with practical examples, and--what is most amazing--the proofs are built up systematically in such a way that you can actually read though them and be enlightened rather than convinced.
Previous econometrics texts have a "Losing sight of the forest for the trees" sort of feel to them. Ruud's text, however, works like the old drill Seargent in the Kipling poem who explained his teaching method as "Firsts I tells 'em what I'ms goings to tells em; then I tells 'em; and then I tells 'em what's I tolds 'em." Ruud does this by first building up the fundamental concept of matrix projection. Then he demonstrates how that can be used to explain Ordinary Least Squares regression. Then he adds onto that all the common assumptions: independent, identically distributed errors; normality of the errors, etc. He builds things up one assumption at a time. And all the while he tells you what he's doing and why the content of each chapter matters and how it is related to what has come before and to what will come afterwards.
But, then--in a master stroke of pedagogy--he tears it all down. He starts taking away, one at a time, all the assumptions like normality that he just spent chapters building up and shows how econometricians deal with matters when they *do* in fact remove the standard assumptions. In this way he can introduce consistent estimators, non-linear regression, latent variables, and so on as what they were historically: practical solutions needed when the assumptions of the classical model fail to hold.
By systematically showing which assumptions imply which results and then showing how to deal with things when a given assumption fails to hold, Ruud's book produces a better econometrician. Too often have previous books left previous readers unable to really understand the art of data analysis, which involves taking a data set, seeing what assumptions can be fairly made about it, and then analyzing it given those fairly made assumptions.
Professor Ruud deserves many plaudits for writing what will surely become the standard text for the next generation of graduate students.
Econometrics finally makes sense!.......2001-01-13
Econometrics seemed to me a technically demanding subject with results that are either magic (stated without derivation) or based on some arcane mathematical tricks. But after reading Ruud's textbook, econometrics finally makes sense. It provides a great exposition of graduate econometrics with all the main results and techniques clearly spelled out. Furthermore, it actually has derivations of the results. I also really like the emphasis on the geometry behind econometrics; it provides a systematic approach and the results even become intuitive.
So, if you want more than just a recipe book and actually understand econometrics, read this book!
Book Description
General Equilibrium Theory: An Introduction, presents one of the great achievements of modern economic analysis (recognized by two Nobel Prizes). General equilibrium analysis studies an economy as a whole, recognizing many interacting markets where prices in one market can affect supply and demand in another. The book is suitable for graduate students and advanced undergraduates in economics and mathematics. It starts with elementary models, presents mathematical preparation and more sophisticated treatments. The treatment emphasizes clarity and accessibility through use of examples and intuition.
Customer Reviews:
Very sloppy; a lot of serious mistakes.......2006-05-01
I agree with the previous reviewer that this book is an effort at a step-by-step approach to General Equilibrium for the student who cannot swallow everything all at once. Nevertheless, big flaws mar the exposition in a way that makes it very annoying to the expert and confusing to the point of uselessness for the beginner.
There are at least five big theorems -- and probably more -- in which key assumptions are misstated; or not stated at all; or assumptions are stated which are not needed and are never used. Signs are messed up in key parts of proofs, leading to no end of confusion.
In general, the sloppiness of the exposition is breathtaking. The sophisticated student will find himself able to prove the theorems more elegantly and correctly than the author and will be annoyed by the author's errors. The beginning student will often be completely lost in the proofs or statements which are incomprehensible (because they are wrong, but the student does not know that). Chapter 17 is a particularly egregious example.
This book is a stab at something that is sorely needed -- a readable, elementary, and accessible introduction to General Equilibrium. Unfortunately, Starr flubs it. A second edition of this book, with the mistakes eliminated, might be quite good. As it stands, I would not recommend it to anyone who does not want to spend hours of frustration correcting the author's sloppiness.
Concise introduction to the mechanics of General Economics.......2001-02-03
This textbook is a concise technical introduction to the mechanics of General Equilibrium, one of two main branches of economic theory. The text does not cover this extensive field in all its capacity. Instead, we have a step-by-step construction of the main models presented with great care for details, so that the reader can learn precision, careful modeling and all necessary details. Moreover, it's useful for people who have difficulty proving theorems.
There is a special bonus that might encourage you to buy the text. The fixed-point theorems are covered in a brilliant, really excellent way. There is no way around that tool in General Equilibrium, and while having difficulty with more sophisticated texts, I found Starr's book to be very helpful in this respect.
Average customer rating:
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Introduction to Multiple Time Series Analysis
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Time Series Analysis
ASIN: 3540569405 |
Book Description
This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
Book Description
Intended primarily to prepare first-year graduate students for their ongoing work in econometrics, economic theory, and finance, this innovative book presents the fundamental concepts of theoretical econometrics, from measure-theoretic probability to statistics. A. Ronald Gallant covers these topics at an introductory level and develops the ideas to the point where they can be applied. He thereby provides the reader not only with a basic grasp of the key empirical tools but with sound intuition as well.
In addition to covering the basic tools of empirical work in economics and finance, Gallant devotes particular attention to motivating ideas and presenting them as the solution to practical problems. For example, he presents correlation, regression, and conditional expectation as a means of obtaining the best approximation of one random variable by some function of another. He considers linear, polynomial, and unrestricted functions, and leads the reader to the notion of conditioning on a sigma-algebra as a means for finding the unrestricted solution. The reader thus gains an understanding of the relationships among linear, polynomial, and unrestricted solutions. Proofs of results are presented when the proof itself aids understanding or when the proof technique has practical value.
A major text-treatise by one of the leading scholars in this field, An Introduction to Econometric Theory will prove valuable not only to graduate students but also to all economists, statisticians, and finance professionals interested in the ideas and implications of theoretical econometrics.
Customer Reviews:
How to complicate simple things.......2007-08-22
This little overpriced textbook is an unrivaled guide on how to complicate simple topics. If you need to un-learn much of what you thought you knew about basic probability, look no further than the pages this book devotes to the "well-known" and "illuminating" game of crap(s). If you want to know enough about measure theory to know it exists, but not enough to understand what it is about, this book is for you. The title of the book is a joke, and a very solid understanding of all the material covered is required before you can really appreciate its content. In grad school we used to make jokes about how you could kill someone just brandishing this textbook.
Prof. Gallant truly knows statistics but this book is, really, obscure. On the bright side, the book is very light, the color of the pages is very pleasant, and the symbols are truly stylish. But that's about it. MAYBE this could be a good choice for a PhD in statistics who wants to know more about advanced econometrics, but as a first year textbook for an ECON PhD I think it's a very bad choice.
For basic, first year econ-PhD econometrics there are many MUCH better options out there (e.g. Wooldridge, Ruud, Hayashi), and as an introduction to advanced classical parametric econometrics Amemiya is still unrivaled.
Gallant approach to econometrics.......2004-06-11
The book is absolutely brilliant. It's short and compact, and beautifully written. The introductory account of probability, based on 4 examples but most particularly the game of "craps", is so much richer than conventional accounts based on rolling a single die (or a pair of dice, but he does that too). In 50 years nobody bothered (not even Halmos or Feller) to make this stuff fun until Gallant.
It is true that this is an introduction to econometrics (i.e. all you need to know before you study econometrics seriously) rather than an introductory text in econometrics. But the account of properties of estimators and tests is so accurate and so liberating: look for quotes on pp. 148, 152 and 154. If you can't read those online then check out the reviews on the back cover.
How can we persuade this guy to write a general text on (more) advanced econometrics? He would earn a million or more.
Barry
This is a beautiful book!!.......2004-05-27
I studied probability theory with this book when I was a first year PhD student in Economics. If I list the best graduate level textbooks in economics, this one would definitely be one of them. Strongly recommended.
A very disappointing book with a deceiving title.......2001-03-28
I bought this book because I read the front lap and I was hoping to find here a really good introduction to advanced themes in econometrics. My first disillusion came when I read the contents: it's an advanced probability introduction and it has been written not for economists, not at least the ones having little knowledge in measure theory and having only a standard probability background. The title should be "Probability elements in econometric theory". The second disillusion was a particular one referring to those not knowing too much of gambling games played at the casinos or not mastering the English language. The first chapter begins with an incomprehensible explanation of a dice game, "craps". If you want a good overview of what is done currently in econometrics, I would rather recommend you the Johnston and Dinardo introductory book, "Econometric Methods"; there you'll learn the basics of econometrics. If what you want it's a probability approach, then you should rather combine the Hamilton's book ("Time Series Analysis") with a probability theory introductory book, such as Monfort's and De groot's. I admit that mathematicians and advanced econometrics researchers would appreciate this book, but they probably won't buy it because the title is misleading. If you want to buy this book, you should be aware that it is a difficult one and -if you are an economist- you'll need a solid background in probability or a wise combination with other probability books.
Excellent book, but takes time to understand it........1999-10-30
Concise book, but shows the necessary ideas. Reading carefully, I come to know how the author describe contents with the minimum use of words. At the same time, many expressions are too neat, and I have to refer the other books to understand the topic. Good textbook, but not for self-study.
Book Description
This treatment of extreme value theory is unique in book literature in that it focuses on some beautiful theoretical results along with applications. All the main topics covering the heart of the subject are introduced to the reader in a systematic fashion so that in the final chapter even the most recent developments in the theory can be understood.
Key to the presentation is the concentration on the probabilistic and statistical aspects of extreme values without major emphasis on such related topics as regular variation, point processes, empirical distribution functions, and Brownian motion.
The work is an excellent introduction to extreme value theory at the graduate level, requiring only some mathematical maturity.
Customer Reviews:
for very speculative applications.......2007-06-02
Initially, the problem seems intractable. How to understand a probability distribution with a long tail of possible values? Where this is little or no observed data at these large values. This probably stymied any serious research into this field until recent decades. The book discusses what can be deduced about such distributions, based on known observations at small values.
It is an advanced statistical monograph. Perhaps best suited for at least the graduate level. It differs qualitatively from most texts, but uses standard ideas like the maximum likelihood estimation, and moment estimators.
As to the applications of this book, that is also speculative. It is hoped that in fields like finance, the ideas can be used to posit more realistic models of rare but potentially catatrophic events.
Book Description
This is a survey of the recent developments in the rapidly expanding field of asymptotic distribution theory, with a special emphasis on the problems of time dependence and heterogeneity. The book is designed to be useful on two levels. First as a textbook and reference work, giving definitions of the relevant mathematical concepts, statements, and proofs of the important results from the probability literature, and numerous examples; and second, as an account of recent work in the field of particular interest to econometricians, including a number of important new results. It is virtually self-contained, with all but the most basic technical prerequisites being explained in their context; mathematical topics include measure theory, integration, metric spaces, and topology, with applications to random variables, and an extended treatment of conditional probability. Other subjects treated include: stochastic processes, mixing processes, martingales, mixingales, and near-epoch dependence; the weak and strong laws of large numbers; weak convergence; and central limit theorems for nonstationary and dependent processes. The functional central limit theorem and its ramifications are covered in detail, including an account of the theoretical underpinnings (the weak convergence of measures on metric spaces), Brownian motion, the multivariate invariance principle, and convergence to stochastic integrals. This material is of special relevance to the theory of cointegration.
Customer Reviews:
Fantastic introductdory reference book.......2007-08-13
As another reviewer noted, there are absolutely no "real world" examples in this book. But that's not really the point. This book covers many of the theorems and techniques you would need to prove asymptotic results for time series, and I refer to it almost daily. The book would be extremely difficult for someone who hasn't taken a graduate sequence in econometrics or had similar mathematical preparation.
It's the first book I look at when I want to understand the details of a concept (mixing, for example), and I wish that Davidson had included some more topics that are related to my current research... that combination should make this an ideal introductory book, even though the material is inherently difficult.
Get ready for a hard time.......2005-09-13
Yes, I know it's a standard game of reviewers to show off by describing books as "a good introduction", implying one's capability of easily absorbing the material.
I shall try to judge the book by its stated mission, viz. to be an "introduction for econometricians". In my view it isn't, the material doesn't resemble much of what you are likely to have encountered in your econometrics education. If anything it is a course in applied measure theory. I should add that I don't know how the original sources look like (e.g. Billingsley), perhaps they're even worse. I just don't see where the book is supposed to be tailored to the background and needs of econometricians (with the exception of convergence to stochastic integrals at the very end, relevant for unit root econometrics etc.). Motivation and relevant examples (e.g. links to econometrics which one might reasonably expect in view of the title) are scarce, or to put it in Davidson's words, they occur on a set with measure zero. The book is thus extremely terse. It's Theorem - Proof - Corollary at its best. The back cover even recommends the book to business econometricians also (whatever that may be). This must be a marketing gag by the publisher, as far as I can judge the business world.
On the other hand it is quite self contained, which means most concepts you need in the later parts of the book are developed (if briefly) in the introductory chapters. Davidson frequently helps you with the task of understanding the proofs (which cover an estimated 2/3 of the book) by referring you to the relevant places.
It is only fair to acknowledge that Davidson does a remarkable job of explaining the material rigorously, but just don't be fooled by the title. It's hard work, you have to spend time on each word and (there is a lot more of that obviously) (in)equality.
Happily, it's worth it. Once you're through this, some of these obscure appendices in Econometrica may at last become more accessible to you. (The converse also holds: if you have never been interested in the details of the proofs save your money.)
Stochastic limit theory for beginners.......2005-06-09
This is a very good book on stochastics as it covers a lot of advanced topics in detail. I particularly found helpful the coverage of weak convergence. If you want to master the realm of stochastic processes, this could be a great place to start.
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