Book Description

In the theory and practice of econometrics the model, the method and the data are all interdependent links in information recovery-estimation and inference. Seldom, however, are the economic and statistical models correctly specified, the data complete or capable of being replicated, the estimation rules ‘optimal and the inferences free of distortion. Faced with these problems, Maximum Entropy Economeirics provides a new basis for learning from economic and statistical models that may be non-regular in the sense that they are ill-posed or underdetermined and the data are partial or incomplete. By extending the maximum entropy formalisms used in the physical sciences, the authors present a new set of generalized entropy techniques designed to recover information about economic systems. The authors compare the generalized entropy techniques with the performance of the relevant traditional methods of information recovery and clearly demonstrate theories with applications including

• Pure inverse problems that include first order Markov processes, and input-output, multisectoral or SAM models to
• Inverse problems with noise that include statistical models subject to ill-conditioning, non-normal errors, heteroskedasticity, autocorrelation, censored, multinomial and simultaneous response data, as well as model selection and non-stationary and dynamic control problems

Book Description

Focusing on the many advances that are made possible by simulation, this book describes the new generation of discrete choice methods. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics.The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing. ... Read more

Reviews (1)

An important Book
More than others tipycal books of QLDV and Panel Data the book show methods for analysis and estimation of QLDV models using the important and widely method of simulation (i.e. methods as GHK for estimation of multivariate probabilities and Gibbs sample method are described). ... Read more

Book Description

Offers an ideal combination of econometric theory and hands-on practical training for undergraduate and graduate courses. The authors ambition is to provide realistic applications without sacrificing theoretical underpinnings. He uses a logical step-by-step approach to walk readers through numerous real-world examples of model specification, estimation, and hypothesis testing. The book also succeeds at being self-contained. By including background information on mathematics, probability, statistics, and software applications, readers have all the information they need in one place. ... Read more

Reviews (5)

Outstanding introduction to econometrics
I can not express enough the quality of this book for the desired target audience. As the title suggests, this is a book for those looking to gain insight into the basics of econometrics. If you've taken even a little calculus, and basic statistics, you should be ok. If not, you've no business trying to tackle econometrics, so I will not let that requirement taint my 5 star rating.

If you have a desire to learn anything about econometrics, especially if you've seen some basic information about regression / OLS in a stats class before, this is the place to start. What is learned here is not only the underlying math but also the all important intuition behind the math and the stats and ultimately the econometrics itself. You don't just learn why a formula works, how it is written, and what the proof looks like. The author goes to length to ensure that you also gain a broad appreciation for the assumptions upon which the methods are based, and ultimately what happens when you violate those assumptions. This is a critical part of learning statistics and econometrics, one which is far too often neglected by students, instructors, and authors alike. A key part of any statistical exercise is the intuition behind it, and a working knowledge of how and why the methods chosen are valid. Ramanathan does an excellent job of making sure you understand these ideas every step of the way, throughtout the text. There are plentiful references to earlier sections with related concepts, constantly linking new ideas with those covered in previous sections and chapters. Appendices between chapters also delve into the related mathematics and provide additional proofs for those interested.

I believe there is no better introduction to the subject of econometrics than this work. My instructor required this text in our beginning econometrics course. He never taught directly from the book nor did he assign work from it. We were merely told to purchase it as a requirement for the class so that we would have it as a reference whether we thought we needed it or not. I found myself reading this book constantly, despite never having been required to so much as open it for the class. The book is more than worth it, even at twice the price.

Wonderful deal!
The book is really new, in good condition. The delivery is faster than expected! If I buy a book next time, I will choose this dealer again!

Econometrics for Dummies
I was in Prof. Ramu's econometrics classes using this book. Statistically innocent to statistically savvy in 20 weeks. Currently I use this book on my job as first point of reference. Concise, not too much technical, many examples, etc.

Fantastic
Great book. Professor Ramanathan has created a book with real life examples that make sense and elucidate the topic at hand. A definite must-have and must-keep for any economist.

econometrics=big headache, do something, try this book
all the economists we have a problem sometimes and this problem is that we are not mathematicians who, on the other hand, are the people who have develop most of the mathematical economics. in this sense, econometrics is a monster that normally is not well explained and one is very happy when finishes and passes the test for it. so the result is that you do not love it. Mr. Ramanathan has done something very very good, he will show you the secrets, step by step. if you need econometrics, try this and do not forget to ask for the sofware. ... Read more

Book Description

This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics.

In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation.

The original contribution of Dynamic Economics: Quantitative Methods and Applications lies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation. ... Read more

Book Description

APPLIED REGRESSION ANALYSIS focuses on the application of regression to real data and examples while employing commercial statistical and spreadsheet software. Designed for both business/economics undergraduates and MBAs, this text provides all of the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis.While only a prior introductory statistics course is required, a review of all necessary basic statistics is provided in chapter 2. The text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets. ... Read more

Reviews (1)

Panel Data for econometrician of time series
The Arellano's Book is an excellent reference for panel data and time series, the book also includes topics on QLDV and panel data, when I stars the book fast I feel the difference with the classics of panel data, the approach of this book is time series, and the book show the power of panel data with examples in economics, includes also the Arellano's contribution to Dynamic Panel Data. ... Read more

Book Description

Time series analysis has undergone many changes during recent years with the advent of unit roots and cointegration. This textbook by G. S. Maddala and In-Moo Kim is based on a successful lecture program and provides a comprehensive review of these topics as well as structural change. G. S. Maddala is one of the most distinguished writers of graduate and undergraduate econometrics textbooks today and Unit Roots, Cointegration and Structural Change represents a major contribution that will be of interest both to specialists and graduate and undergraduate students. ... Read more

Reviews (5)

modern econometrics with latest developments
This is a book on specialized topics in econometric modeling. Like Franses recent book it deals with ARIMA models with unit roots and advances in the theory of cointegration. This book is somewhat advanced but is perfect for the right audience, the statisticians and econometricians that deal with time series modeling (univariate and multivariate ) and structural equation modeling.

The asymptotic theory is well covered but the unique feature of the book is that it points out that the asymptotics can give very poor approximations in small to moderate sample sizes. The authors provide alternatives including the use of the bootstrap for standard error estimates, confidence bounds and hypothesis testing (particularly tests for unit roots).

It is clear and covers the important literature. Much like Franses book it covers bootstrap and Bayesian methods and really does provide a current and useful approach to important problems and methodology in econometrics.

It could be used for a special topics graduate course or as a supplement to a graduate course in econometrics.

Excellent Book
Excellent book

This one of the best book about cointegration.

Intuition behind modern time series analysis
This book is extremely well written. It gives a good intuition behind unit roots and cointegration. It tells us to be critical when it comes to unit roots and cointegration; they are not very powerful in a statistical sense. The authors warn of using such techniques blindly. This book is a good start for an intuitive feel after a tough Time Series course where one is all entangled in sophisticated statistical techniques.It is also a good book for the professional economist not very knowlegeable in time series econometrics. I personally learned a lot from that book and it increased my critical capacity when it comes to econometrics.

A good reference

The book by Maddala and Kim is a very good and relativelynontechnical pointer to the time series literature on unit roots andcointegration. The book is meant to be used as a reference, not readas a text.

Maddala and Kim do a good job of discussing the strengths and weaknesses of the myriad unit root and cointegration tests that have appeared in recent years. If you want to know more about the asymptotic theory, then refer to _Time Series Analysis_ by Hamilton or read the original journal articles.

For a more balanced review of the Maddala and Kim book, one might also take a look at the book review written by Heather Anderson in the December 1999 issue of the Economic Record. END

the worst book I have ever had!
I was required to read this book as a part of my field course in econometrics. The book is full of mistakes, especially on asymptotic distributions of estimators. Since the properties of these estimators of unit root tests depend on those asymptotic distributions, this kind of mistake is crucial. Also, the results they derive are sometimes misleading and other times even outright wrong! This book is a mere survey of papers other people wrote and not a good one at that. In summary, do not spend your money on this book! ... Read more

Reviews (3)

The Bible of market microstructure theory
This is the quintessential book on the theory of the microstructure of financial markets. Although it is not meant for people with just a casual interest in the area, it is nevertheless an indispensable book for academics and for people serious about the topic.

It is also far more readable and understandable than Daniel Spurber's book which provides little of the working intuition of O'Hara. In fact Spurber is meant more for the theoretical economist with an interest in market microstructure, whereas O'Hara appeals to a broader audience in the field of finance.

A Counter Point
This book does not need praise. It is widely considered the best introduction to the academic work in market microstructure. The only reason I've listed this review is to counter the unfortunate review already listed. This book is perfect for the researcher or PhD student interested in the issues addressed in market microstructure. Although the book is not written for the average mba student, a careful read would benefit anyone interested in the structure of markets.

Lacks in both organization and clarity .
The book is meant to describe market microstructure. My discovery is that one needs to know a lot about the subject matter to get anything out of it. I had the feeling of reading footnotes without seeing the text! It quotes authors and papers without the slightest indication as to what they are about. I do not recommend it. But there are other books covering the subject. Campbell, Lo and McKinlay (The Econometrics of Financial Markets) proovides in one chapter more information that this book. FInally, there is a French book on the topic that is excellent; it would call for a translation (the authors are Biais,Foucault & Hillion). ... Read more

Book Description

This book explores econometrics using an intuitive approach that begins with an economic model. It emphasizes motivation, understanding, and implementation and shows readers how economic data are used with economic and statistical models as a basis for estimating key economic parameters, testing economic hypotheses and predicting economic outcomes. ... Read more

Reviews (4)

Very good for learning
This book is a shortened version of "Learning and Practising Econometrics (1993)", which itself is a shortened version of "The Theory and Practice of Econometrics (1982)".

Hill's "Undergraduate Econometrics" instills understanding by slowly going through derivations and principles, while at the same time motivating econometric analysis by referring to economic situations where it can be used. Much better than Gujarati (which tends to be a "cookery book" rather than giving an integrated treatment).

The book both motivates the student and takes them through the steps and methods they will need to adopt in further econometric studies, and always provides a good reference (often to one of the parent books mentioned above) when it omits proofs and other details.

The only weakness of the book reveals what is (to my mind) an unhealthy preoccupation with estimation issues, as opposed to those of data quality. As people like Granger have consistently pointed out, the real issues in 21st century econometrics have to do with what sort of data we have, and what methods are most appropriate in different situations. Despite this, Hill et al almost exclusively dwell on the identically and independently distributed (iid) specification. However, I should point out in the book's defence that this preoccupation is shared by most other introductory (and graduate) textbooks on econometrics.

The book's good points far outweigh these weaknesses. Finally, the second edition has some updates, and discusses such developments as time series econometrics. "Undergraduate Econometrics" should definitely be purchased by anyone wishing to learn about modern empirical methods.

Excellent intuition BUT A POOR BRIDGE TO THE DREADFUL GREENE
This book is the best book to use for the very first course in econometrics. It takes you by the hand to teach you all you need in terms of the basics.
I only give it 4 stars for two reasons. First, while this book is non-mathematical (and I agree with that) it should have nonetheless appendices that make use of matrices and differential calculus.
Second, this book is extremely expensive.
This book can easily earn 5 stars if in the next edition it contains appendices that will create a bridge towards intermediate econometrics. A more reasonable price would also be welcomed.
Overall, this is the best book to use for a very first course in econometrics.
BUT BEWARE: THIS BOOK IS A POOR BRIDGE TO THE DREADFUL GREENE!!!!THE BEST BRIDGE IS "LEARNING AND PRACTICING ECONOMETRICS" BY THE SAME AUTHOURS OF "UNDERGRADUATE ECOMETRICS" I.E. HILL, GRIFFITHS, AND JUDGE.
By the way, for those that are looking for a good substitue to "Undergraduate Econometrics", you have "Basic Econometrics" by Gujarati.

Thank you,

carter makes me not-so-afraid of metrics...
this is one of those econometrics (i'll call it "metrics" from now on to save on typing) books which you know has to cover alot of the slow, boring stuff which lecturers expect students to know by the time they take metrics options and hated by undergraduates. having said that, this book does it quite well. one thing i hate in metrics texts is dense mathematical proofs. especially proofs which assume the reader knows other proofs intimately. this book nicely avoids that, dropping in an adequate and useful amount of proofs, especially the Gauss-Markov Theorem and a proof of why OLS estimation outshines any other method in simple regression analysis. the book does this without being overwhelming - in my opinion, mathematics has to be appreciated through discussion and argument, which Hill et al do quite admirably. Also, metrics is about interpretation of results, not just calculating them, and this book keeps that in mind very well from beginning to end. The reason i gave this book 4 stars is simple. when i was doing my last minute cramming for exams, i was able to move through the book quickly and easily, whilst still appreciating the main points, the big picture, and also the subtleties of more advanced topics like GLS, moments-based estimation and distributed lags in a short space of time. the book also comes with useful end-of-chapter "should know" points and problems. the best thing about the problems is the "real-world" nature of the tasks, often drawing on real-life data and economic intuition. using that data and being able to become comfortable with computer techniques is the most vital thing to a beneficial study of metrics. i found gujarati's "basic econometrics" a nice companion to this book (but then again everyone likes gujarati to some extent), but mostly i was satisfied with this book as a stand-alone manual to second-year metrics studies, good for laying the foundations for studies in topics like maximum likelihood estimation and financial econometrics. oh, and it's small and not too heavy. good for carrying around to classes all day!

A Nice Beginner's Textbook
This book begins with simple concepts and gradually introduces more complex methods at a pace that is very comfortable for self-study. It also can be used in a one-quarter course for undergraduates who have had basic courses in calculus and linear algebra. However, it doesn't give all proofs for the statistical theorems in the text. ... Read more

Book Description

Applied Time Series Modelling and Forecasting provides a relatively non-technical introduction to applied time series econometrics and forecasting involving non-stationary data. The emphasis is very much on the why and how and, as much as possible, the authors confine technical material to boxes or point to the relevant sources for more detailed information.

This book is based on an earlier title Using Cointegration Analysis in Econometric Modelling by Richard Harris. As well as updating material covered in the earlier book, there are two major additions involving panel tests for unit roots and cointegration and forecasting of financial time series. Harris and Sollis have also incorporated as many of the latest techniques in the area as possible including: testing for periodic integration and cointegration; GLS detrending when testing for unit roots; structural breaks and season unit root testing; testing for cointegration with a structural break; asymmetric tests for cointegration; testing for super-exogeniety; seasonal cointegration in multivariate models; and approaches to structural macroeconomic modelling. In addition, the discussion of certain topics, such as testing for unique vectors, has been simplified.

Applied Time Series Modelling and Forecasting has been written for students taking courses in financial economics and forecasting, applied time series, and econometrics at advanced undergraduate and postgraduate levels. It will also be useful for practitioners who wish to understand the application of time series modelling e.g. financial brokers.

Data sets and econometric code for implementing some of the more recent procedures covered in the book can be found on the following web site www.wiley.co.uk/harris ... Read more

Reviews (1)

Petition: info about authors
Please provide brief bios of these two authors. ... Read more

Book Description

When John Nash won the Nobel prize in economics in 1994, many people were surprised to learn that he was alive and well. Since then, Sylvia Nasar's celebrated biography, the basis of a new major motion picture, has revealed the man. The Essential John Nash reveals his work--in his own words. This book presents, for the first time, the full range of Nash's diverse contributions not only to game theory, for which he received the Nobel, but to pure mathematics, in which he commands even greater acclaim among academics. Included are nine of Nash's most influential papers, most of them written over the decade beginning in 1949.

From 1959 until his astonishing remission three decades later, the man behind the concepts "Nash equilibrium" and "Nash bargaining"--concepts that today pervade not only economics but nuclear strategy and contract talks in major league sports--had lived in the shadow of a condition diagnosed as paranoid schizophrenia. In the introduction to this book, Nasar recounts how Nash had, by the age of thirty, gone from being a wunderkind at Princeton and a rising mathematical star at MIT to the depths of mental illness.

In his preface, Harold Kuhn offers personal insights on his longtime friend and colleague; and in introductions to several of Nash's papers, he provides scholarly context. In an afterword, Nash describes his current work, and he discusses an error in one of his papers. A photo essay chronicles Nash's career from his student days in Princeton to the present. Also included are Nash's Nobel citation and autobiography.

The Essential John Nash makes it plain why one of Nash's colleagues termed his style of intellectual inquiry as "like lightning striking." All those inspired by Nash's dazzling ideas will welcome this unprecedented opportunity to trace these ideas back to the exceptional mind they came from. ... Read more

Reviews (12)

Fascinating Reading
Even without the Nobel Prize for Economics, the outstanding movie by Ron Howard ("A Beautiful Mind"), or the exceptional biography by Sylvia Nasar (also "A Beautiful Mind"), Professor John Nash would a legend. While cursed with severe mental illness, Dr. Nash was and is an extraordinary man. His contributions to game theory were so ahead of their time it took over 30 years for economists and business leaders to apply them fully. When they were applied, they advanced everything from international trade talks and arms control treaties, to radio frequency auctions and the study of evolutionary biology. Dr. Nash's work has had a profound, highly practical impact on negotiation and decision making throughout business and government. He created a path toward win-win solutions to complex, multi-party agreements.

This book is largely a collection of Dr. Nash's own writings, each a significant contribution to mathematics or economics. Nash's papers are thoughtfully introduced and explained - thankfully so given the complexity of Nash's writings. Also included is Nash's own touching and revealing autobiography.

The result is a compelling glimpse inside the thought processes of a genius - a beautiful mind indeed. Thanks to Harold Kuhn and Sylvia Nasar for pulling this wonderful collection together.

An excellent compilation
Having written about the life of the mathematician John Nash in the excellent biography "A Beautiful Mind", Sylvia Nasar teams up with the mathematician Harold W. Kuhn to produce a book that introduces the mathematical contributions of Nash, something that was done only from a "popular" point of view in Nasar's biography. For those who have the background, this book is a fine overview of just what won Nash acclaim in the mathematical community, and won him a Nobel Prize in economics.

It is always easy to dismiss ideas as trivial after they have been discovered and have been put into print. This is apparently what John von Neumann did after discussing with Nash his ideas on noncooperative games, dismissing his ideas as a mere "fixed point theorem". At the time of course, the only game-theoretic ideas that had any influence were those of von Neumann and his collaborator, the Princeton economist Oskar Morgenstern. The rejection of ideas by those whose who hold different ones is not uncommon in science and mathematics, and, from von Neumann's point of view at the time, he did not have the advantage that we do of examining the impact that Nash's ideas would have on economics and many other fields of endeavor. Therefore, von Neumann was somewhat justified, although not by a large measure, in dismissing what Nash was proposing. Nash's thesis was relatively short compared to the size on the average of Phd theses, but it has been applied to many areas, a lot of these listed in this book, and others that are not, such as QoS provisioning in telecommunication and packet networks. The thesis is very readable, and employs a few ideas from algebraic topology, such as the Brouwer fixed point theorem.

The paper on real algebraic manifolds though is more formidable, and will require a solid background in differential geometry and algebraic geometry. However, from a modern point of view the paper is very readable, and is far from the sheaf and scheme-theoretic points of view that now dominate algebraic geometry. It is interesting that Nash was able to prove what he did with the concepts he used. The result could be characterized loosely as a representation theory employing algebraic analytic functions. These functions are defined on a closed analytic manifold and serve as well-behaved imbedding functions for the manifold, which is itself analytic and closed. These manifolds have been called 'Nash manifolds' in the literature, and have been studied extensively by a number of mathematicians.

I first heard about John Nash by taking a course in algebraic topology and characteristic classes in graduate school. The instructor was discussing the imbedding problem for Riemannian manifolds, and mentioned that Nash was responsible for one of the major results in this area. His contribution is included in this book, and is the longest chapter therein. Here again, the language and flow of Nash's proof is very understandable. This is another example of the difference in the way mathematicians wrote back then versus the way they do now. Nash and other mathematicians of his time were more 'wordy' in their presentations, and this makes the reading of their works much more palatable. This is to be contrasted with the concisness and economy of thought expressed in modern papers on mathematics. These papers frequently employ a considerable amount of technical machinery, and thus the underlying conceptual foundations are masked. Nash explains what he is going to do before he does it, and this serves to motivate the constructions that he employs. His presentation is so good that one can read it and not have to ask anyone for assistance in the understanding of it. This is the way all mathematical papers should be written, so as to alleviate any dependence on an 'oral tradition' in mathematical developments.

Nash's proof illuminates nicely just what happens to the derivatives of a function when the smoothing operation is applied. The smoothing operator consists of essentially of extending a function to Euclidean n-space, applying a convolution operator to the extended function, and then restricting the result to the given manifold. Nash gives an intuitive picture of this smoothing operator as a frequency filter, passing without attenuation all frequencies below a certain parameter, omitting all frequencies above twice this parameter, and acting as a variable attenuator between these two, resulting in infinitely smooth function of frequency.

The next stage of the proof of the imbedding theorem is more tedious, and consists of using the smoothing operator and what Nash calls 'feed-back' to construct a 'perturbation device' in order to study the rate of change of the metric induced by the imbedding. Nash's description of the perturbation process is excellent, again for its clarity in motivating what he is going to do. The feed-back mechanism allows him to get a handle of the error term in the infinitesimal perturbation, isolating the smoother parts first, and handling the more difficult parts later. Nash reduces the perturbation process to a collection of integral equations, and then proves the existence of solutions to these equations. A covariant symmetric tensor results from these endeavors, which is CK-smooth for k greater than or equal to 3, and which represents the change in the metric induced by the imbedding of the manifold. The imbedding problem is then solved for compact manifolds by proving that only infinitesimal changes in the metric are needed. The non-compact case is treated by reducing it to the compact case. The price paid for this strategy is a weakening of the bound on the required dimension of the Eucliden imbedding space.

The last chapter concerns Nash's contribution to nonlinear partial differential equations. I did not read this chapter, so I will omit its review.

Good Collection of Nash Writings!
I only rate books that I really enjoy reading. While this one has some techy chapters, readers without a strong math background can still enjoy it.

Professor Nash's story was brought to life by the movie, this book shows why. One day his manifold theory will rule! ;)

excellent
Personally, I found this book to be very interestring. The proofs and ideas are presented in clear and non-rigomorphic fashion. One is able to read the works of Nash in the way he himself presented them, and hopefully appropriate some mental strategies used by this genius. There is much that goes on behind the scene of creation of proofs. I think mathematicians of today would greatly benefit from availability of larger number of books which would contain the mathematical works in the way they were originally presented. This is certainly a major step in that direction.

A Most Welcome Mathematical Banquet
I can't begin to express how deeply satisfying it was to peruse these papers by John Nash. You almost felt you were right there at his side, as he penned them.

There is even something in the book for non-mathematical types: Sylvia Nasar's Introduction and the autobiographical essay (Chapter Two). But for me the greatest interest resided in the remaining chapters: 4-11.

Of these, I particularly enjoyed reading the original presentation of Nash's Thesis on 'Non-Cooperative Games' (Chapter 6), and was fascinated not only with the air-tight logic of his proofs, but the use of hand written-in symbols.

Of course, Chapter 7 is just the re-hashing of Ch. 6, but in proper type-set form, rather than Nash's original script. But - give me the former any day! Reading the original form and format almost made me feel like Nash's Thesis aupervisor, including the same excitement of a new discovery!

Chapter 8 'Two person Cooperative Games' nicely extends the mathematical basis to cover this species of interaction.(And in many ways, people will find the cooperative game model easier to understand than the non-cooperative).

Chapter 9 is important because it delves into the issue of parallel control, and logical functions such as used in high speed digital computers. This chapter was of much interest to me since particular aspects of parallel control figured in my own model of consciousness - recently presented in Chapter Five of my book, 'The Atheist's Handbook to Modern Materialism'. Astute readers who read both books will quickly see the analog between the Schematic of Logical Unit Function (p. 122) and my own Figure 5-13 ('Development of Neural Assemblies', p. 156).

I enjoyed Chapter 10, 'Real Algebraic Manifolds' because of my ongoing interest in Algebraic Topology, and especially homology and homotopy theory. In his chapter, Nash presents a cornucopia of methods for representation, which I am still playing with for different manifolds.

Chapter 11, 'The Imbedding Problem for Riemannian Manifolds', is a delight for anyone familiar with Einstein's General Relativity, or even differential geometry. When you read through this chapter, you also will understand why Nash is still very interested (and involved) in research to do with general relativity and cosmology. Particularly fun for me was his section on 'Smoothing of Tensors' (p. 163) and 'Derivative Size Concept for Tensors' (p. 164).

Chapter 12, 'Continuity of Solutions of Parabolic and Elliptic Equations' is like 'dessert' for anyone who is intensely interested (as I am) in modular functions, which themselves are related intimately to elliptic equations.

In short, I think this book has something for both mathematicians and non-math types alike. Obviously, the former are likely to get more out of it, so the question the latter group must ask is whether the purchase is worth satiating their curiosity about Nash.

I know how I would answer, even if I couldn't tell a derivative from a differential. However, this book can be read on all kinds of levels, and that's the beauty of it. ... Read more

Book Description

A Guide to Econometrics has established itself as a preferred text for teachers and students throughout the world. It provides an overview of the subject and an intuitive feel for its concepts and techniques without the notation and technical detail that characterize most econometrics textbooks.

The fifth edition has two major additions, a chapter on panel data and an innovative chapter on applied econometrics. Existing chapters have been revised and updated extensively, particularly the specification chapter (to coordinate with the applied econometrics chapter), the qualitative dependent variables chapter (to better explain the difference between multinomial and conditional logit), the limited dependent variables chapter (to provide a better interpretation of Tobit estimation), and the time series chapter (to incorporate the vector autoregression discussion from the simultaneous equations chapter and to explain more fully estimation of vector error correction models). Several new exercises have been added, some of which form new sections on bootstrapping and on applied econometrics.

This edition is for sale in all of the Americas, the West Indies, and U.S. dependencies only. ... Read more

Reviews (17)

Non-Optional Reading for ANYONE involved in econometrics.
If you are taking a course in econometrics, graduate or undergraduate, there is no good excuse for failing to purchase this book. Kennedy has a tremendous gift for giving readers a vision for the "Forest" of econometrics, which is very handy for those readers trapped in the "trees" of Pindyck & Rubinfeld and William Greene's texts (both of which are excellent, but relatively technical).

Kennedy covers an amazingly broad selection of topics in his books. While those having difficulty understanding the field will definitely get a great deal out of the book, don't think for a second that the book is overly simplistic -- an econometrics primer. No, this is not a mere review of OLS for the Gauss-Markov impaired. Kennedy's text covers Bayesian Analysis, Vector Error-Correction Models, and even touches, albeit lightly for my tastes, on such subjects as Kalman filtering and recursive least squares. Kennedy's notes are also very insightful and bring up many issues that dominant textbooks skirt around.

Best "Intuition" for and Explaination of Econometrics
Unfortunately, I found this book at the END of too many PhD courses where I was swamped by assumptions the instructor and various authors were making. If I had only read this book FIRST - and then read Green, Greene, Johnston, Goldberger, etc., I would have gotten much more out of the courses with less stress. Peter Kennedy writes the type of book that students dream of finding (and I dream of writing someday). Each chapter is in 3 parts: 1) Overview of what and why, 2) Some more detail and 3) The nitty gritty that you'll worry about in Amemiya's book and others. This is the perfect book for PhD students interested in learning econometrics as a tool instead of an area of research (i.e. developing new models). Once you learn the basics, you can go to Greene's Econometrics Analysis for the details regarding implementation. My recommendation for "reading" this book is to whip through Part 1 of each chapter for the best overview of econometrics ever. (Peter Kennedy is an excellent writer, so this is actually an enjoyable and interesting experience.) Then revisit the relevant chapters before tackling the assigned readings for your course.

Mandatory Reading for Economists
Kennedy's Guide to Econometrics explains econometrics more clearly than any other book I have read. This book will not make you into an econometrician. But, this is definitely the place to start your education on empirical methods in economics.

For a book of this size, he covers a lot of territory. He covers the CLR model and hypothesis testing well, and discusses a few other things too. This guide is hardly encyclopedic. However, it covers the things economists need to know most.

Kennedy does more than just explain econometrics. He spells out the limits of econometric analysis. Texts often pay little attention to the 'con in econometrics'. Not Kennedy. He discusses the limitations and defects in standard techniques, as well as their advantages.

The only thing wrong with this book is that it does not carry the reader along far enough. After reading this book, most reader's will likely move on to a standard (i.e. badly written) econometrics textbook. In contrast, this book is written so well that it almost makes learning econometrics fun!

the best backup there is
I have tried three econometrics textbooks so far (Johnston and DiNardo, Hayashi and Greene) but this is the only one that I can read without having a headache. This is because aside from its technical contents, it also contains lots of anecdotes that make it a pleasure to read. From this book, I could presume that Prof. Kennedy is not only a great researcher but an excellent teacher too. Even the answers to selected problems are explained thoroughly and clearly. Besides, the price is so affordable. Nevertheless, I would prefer to see the geometry of least squares than the Ballantine-Venn diagram utilized in the book. I also agree that GMM should be included in the subsequent editions.

Non technical Econometrics Book!!!!
I agree with the other reviewers, so my contribution is marginal.

The book attains its objectives of making Econometrics easier.
But it is a companion book.

Since it is a non-technical text, alone, this book will not help to implement econometric models.

Next editions must contain GMM method.

It has a good competitor: Learning and Practice of Econometrics, by Griffith, et alli. ... Read more

Book Description

This book systematically and thoroughly covers a vast literature on the nonparametric and semiparametric statistics and econometrics that has evolved over the past five decades. Within this framework, this is the first book to discuss the principles of the nonparametric approach to the topics covered in a first year graduate course in econometrics, e.g., regression function, heteroskedasticity, simultaneous equations models, logit-probit and censored models. Professors Pagan and Ullah provide intuitive explanations of difficult concepts, heuristic developments of theory, and empirical examples emphasizing the usefulness of modern nonparametric approach. The book should provide a new perspective on teaching and research in applied subjects in general and econometrics and statistics in particular. ... Read more

Reviews (3)

Great Book on Non-Parametrics
I just started reading it, and I love the clear exposition of the book. Its a very fast-growing field, so don't expect this book to be the last word on the subject. Still, it's a must for an advanced graduate student in econometrics in need of a good introduction to non-parametric estimation.

A comprehensive review of nonparametrics statistics
Nonparametrics seems to be one of the most promising fields in econometrics. All econometricians should be aware of that and try to learn the basic tools. This book is a great beginning (perhaps you should read the chapter of nonparametrics in Johnston and Dinardo's "Econometric Methods" to get used to the very basic concepts). The manual contains practically all the stuff that has been done in the field. It begins pretty fast with the kernel estimation method and, by page 19, you will be face to nonparametric derivatives estimation equations. In the introduction there is a clear explanation of the difference between parametrics and nonparametrics; you will also learn the main basic methods and concepts, such as the nearest Neighborhood Estimator and the window's size problem. After that, you'll have to read about the statistical properties (finite sample and asymptotics) of the estimators. There is also a lot of stuff of semiparametric methods. You shouldn't expect an extremely easy-to-read manual, because nonparametrics is a pretty complex subject. The first 50 pages are easy and fun to read. You'll get excited by learning such interesting theory. But then, the hard topics begin and if you want to understand them all, you'll have to make a big effort. Not overwhelmingly complicated, neither elementary, this book is an excellent reference in the field, but I advice you to have two or three more books of the same subject (Hardle, for example) so you can understand faster some of the developments presented. A fairly good mathematical and probability knowledge is required.

Up to date
This is the most accessible and the most comprehensive text on nonparametric econometric methods I have seen. The field is highly technical, and there has been a need for the book that would combine ease-of-use with the scope. Moreover, the book is up to date and covers all econometric methods, instead of focusing on a specific branch. Recommended. ... Read more

Book Description

"Judd's book is a masterpiece which will help transform the way economic theory is done. It harnesses the computer revolution in the service of economic theory by collecting together a whole array of numerical methods to simulate and quantify models that used to be purely algebraic and qualitative." -- Avinash K. Dixit, Sherrerd University Professor of Economics, Princeton University

To harness the full power of computer technology, economists need to use a broad range of mathematical techniques. In this book, Kenneth Judd presents techniques from the numerical analysis and applied mathematics literatures and shows how to use them in economic analyses.

The book is divided into five parts. Part I provides a general introduction. Part II presents basics from numerical analysis on Rn, including linear equations, iterative methods, optimization, nonlinear equations, approximation methods, numerical integration and differentiation, and Monte Carlo methods. Part III covers methods for dynamic problems, including finite difference methods, projection methods, and numerical dynamic programming. Part IV covers perturbation and asymptotic solution methods. Finally, Part V covers applications to dynamic equilibrium analysis, including solution methods for perfect foresight models and rational expectation models. A web site contains supplementary material including programs and answers to exercises. ... Read more

Reviews (2)

I don't know how to use this book
Yes! this book covers everything and Professor Judd tries to make it a reference book for everything. However, as a "numerical methods" book, how could you not deal with technical details? I don't see how I can use this book. Assume I know the methodology, why do I need the book? it covers exactly what I know, no more than that; Assume I do not know the methodology, this book does not provide any technical detail to implement the method. I don't deem it a useful book. It's like a dictionary, a lot of cheap talk about the methodology, but no real contents.

An essential resource for all applied economists.
Judd ties together a vast amount of material--from the most basic to the most advanced--that is essential to anyone doing computational work in economics, econometrics or finance. The book is sufficiently self-contained to serve as the single reference book on computational methods for the average economist. In addition, Judd highlights the origins of most methods and points to strengths, weaknesses, and future theoretical research directions. Economic/finance examples are used throughout the book to make the concepts easy to understand and apply. The only thing keeping this book from being perfect is a complete set of software tools, but given the breadth of the book, this might be too much to ask. ... Read more

Book Description

This book introduces one of the most powerful tools of modern economics to a wide audience: those who will later construct or consume game-theoretic models. Robert Gibbons addresses scholars in applied fields within economics who want a serious and thorough discussion of game theory but who may have found other works overly abstract. Gibbons emphasizes the economic applications of the theory at least as much as the pure theory itself; formal arguments about abstract games play a minor role. The applications illustrate the process of model building--of translating an informal description of a multi-person decision situation into a formal game-theoretic problem to be analyzed. Also, the variety of applications shows that similar issues arise in different areas of economics, and that the same game-theoretic tools can be applied in each setting. In order to emphasize the broad potential scope of the theory, conventional applications from industrial organization have been largely replaced by applications from labor, macro, and other applied fields in economics. The book covers four classes of games, and four corresponding notions of equilibrium: static games of complete information and Nash equilibrium, dynamic games of complete information and subgame-perfect Nash equilibrium, static games of incomplete information and Bayesian Nash equilibrium, and dynamic games of incomplete information and perfect Bayesian equilibrium. ... Read more

Reviews (16)

The Best Book for Learning Applied Game Theory
For the advanced student with some knowledge of basic game theory, this is the best book on applications. There is really a rather amazing array of examples covered and worked out in detail on some major topics of noncooperative game theory -- static and dynamic games, with complete and incomplete information. Gibbons gets right down to the key moving parts of the models he presents and in the process provides great examples of what can be done with game theory.

This is not, however, the best book as an introduction to pure game theory, at any level (and obviously isn't meant to be). If you use it that way you may be disappointed. While it does cover the theory it uses, and pretty rigorously at that, it cannot by its nature get deep enough into the guts of equilibrium concepts and refinements for that purpose.

If it's used in conjunction with a pure game theory book, particularly Myerson, it will provide an excellent foundation for graduate students in social science, particularly economics. In fact it can be a very useful tool when using a more theoretically oriented book to get a better idea of what the basic concepts are really all about. (The discussion of sequential equilibrium and the intuitive criterion is especially good for building intuition.)

Simply, a great book
I read this book for my MSc course in Economics. I found it very straightforward and to the point. If you can handle this book, consider yourself prepared to go into deeper game theory books such as Jean Tirole's Game Theory, among others. The organisation of the book is quite simple and logic, and makes you understand the differences between games in a very easy manner. This is a must read book for every serious economist.

Beware of the last chapter
Overall this is a very well written intro to game theory. However I want to raise one point which was never mentioned here. Unfortunately Gobbons' writing style deteriorate as the book progresses, and gets downright careless in the last chapter, which happens to be filled with examples. (there are typos as well, which are not present in other chapters.) I don't know if he was under the pressure to finish the book quickly, but it is clear not much attention was paid to that chapter. The explanations are not clear and confusing (it is a consensus from my classmates.) I'm giving four stars still because I think it is a pretty good introductory text. Just be mindful of that chapter.

Basic, but well written
This book provides a very simple, intuitive introduction to game theory, avoiding technical details. The author's style of writing is extremely clear. However, the book lacks sufficient rigor to make a good "stand-alone" introductory text for a graduate course in game theory. It would work well as a main text for an undergraduate course. Finally, most of the exercises in the book are well chosen and useful, unlike certain other texts on game theory I could mention.

Simplifies a complex topic
This book provides a difficult, but thorough introduction to applied game theory. I used it as a reference for a mathematics course that did not delve into game theory so deeply, so I have not as of yet read the entire book. However, I did read the first few chapters, and am fascinated by the simple way Gibbons explains complicated game theoretical models ... Read more