Product Description
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata.

As an expert in Stata, the author successfully guides readers from the basic elements of Stata to the core econometric topics. He first describes the fundamental components needed to effectively use Stata. The book then covers the multiple linear regression model, linear and nonlinear Wald tests, constrained least-squares estimation, Lagrange multiplier tests, and hypothesis testing of nonnested models. Subsequent chapters center on the consequences of failures of the linear regression model's assumptions. The book also examines indicator variables, interaction effects, weak instruments, underidentification, and generalized method-of-moments estimation. The final chapters introduce panel-data analysis and discrete- and limited-dependent variables and the two appendices discuss how to import data into Stata and Stata programming.

Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book serves both as a supplementary text for undergraduate and graduate students and as a clear guide for economists and financial analysts. ... Read more

Customer Reviews (3)

Best econometrics text for applied economists I have ever read!
Christopher Baum's "An Introduction to Modern Econometrics Using Stata" is simply the best econometrics text for applied economists I have ever read. It reviews most major topics in econometrics in a concise manner and shows how to treat these issues using Stata. In doing so the book also introduces a number of very useful commands, which you will find yourself using in all your regressions. Remember, however, that this is "An Introduction" and therefore other books will be necessary for a more in depth exposition of certain topics. Regardless, this book is perfect for both postgraduate students as well as researchers looking to re-familiarise themselves with econometrics.

good crash intro to necessary STATA commands
This book gives a good overview of some of the commands one would need to do regression analysis with STATA.I needed something to give me a quick intro to STATA and this book has helped me a lot.Howver, just like MS Excel, STATA has tons of commands that I probably will never touch!

much cheaper from stata-press website
Not a review, sorry, but a tip for potential purchasers:

This book is much cheaper from stata-press dot com.
... Read more

Product Description
This classic text has proven its worth in university classrooms and as a tool kit in research--selling over 40,000 copies in the United States and abroad in its first edition alone. Users have included undergraduate and graduate students of economics and business, and students and researchers in political science, sociology, and other fields where regression models and their extensions are relevant. The book has also served as a handy reference in the "real world" for people who need a clear and accurate explanation of techniques that are used in empirical research.
Throughout the book the emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus. Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases. And while a relatively high degree of rigor is preserved, every conflict between rigor and clarity is resolved in favor of the latter. Apart from its clear exposition, the book's strength lies in emphasizing the basic ideas rather than just presenting formulas to learn and rules to apply.
The book consists of two parts, which could be considered jointly or separately. Part one covers the basic elements of the theory of statistics and provides readers with a good understanding of the process of scientific generalization from incomplete information. Part two contains a thorough exposition of all basic econometric methods and includes some of the more recent developments in several areas.
As a textbook, Elements of Econometrics is intended for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in econometrics. Researchers in the social sciences will find it an invaluable reference tool.
A solutions manual is also available for teachers who adopt the text for coursework.
Jan Kmenta is Professor Emeritus of Economics and Statistics, University of Michigan.
... Read more

Customer Reviews (14)

An excellent reference but a very difficult read
I did an independent study in econometrics as a doctoral student in educational policy studies, and some of the readings were taken from the first edition of Kmenta's Elements of Econometrics.At the time, I recognized that Kmenta's text was long and difficult, but it was also clear that some topics that were simply unreadable in other econometric accounts, especially Jack Johnston's Econometric Methods, were presented with greater clarity and less mathematical density by Kmenta.For me, the fact that most of Kmenta's account did not require a working knowledge of matrix algebra was a definite plus.

That was thirty years ago, and I have since bought a copy of the second edition of Kmenta's book.No less demanding than the first edition, Kmenta's updated text remains comprehensive and wonderfully informative.As with the first edition, moreover, the second edition avoids undue reliance on matrix algebra.

I have learned, however, that for my purposes this book serves best as a reference.When I was having trouble understanding maximum likelihood methods for the estimation of regression coefficients, I turned to Kmenta and found an accessible explanation, as well as a graphical account that brought the notion of maximum likelihood to life, making it seem almost commonsensical.Similarly, when I struggled to learn why procedures such as tobit were useful as an antidote to certain forms of sample selection bias, I turned to Kemnta and found what I needed.This included a clearer understanding of just what sample selection bias means in this context.

I have read substantial chunks of Kmenta's book, but I doubt that I will ever sit down and undertake the daunting task of reading it from start to finish.Nevertheless, Kmenta's second edition occupies a conspicuous and important place on my book shelf precisely because it serves so usefully as a reference.For those of us who are often forced to work on or just beyond the borders of our readily available statistical knowledge, this text is well worth the price.

A Classic.
I had the fortune of taking two undergraduate statistics courses under Professor Kmenta just prior to his retirement at the University of Michigan. The first was a standard introductory statistics course for economics majors, the second a more advanced class for honors students. Of course, this was the text assigned for those courses.

Since then, I have read other Statistics textbooks, and few, if any, will provide you with a more fundamental understanding of what statistics is and how it works than "Elements of Econometrics".

As other reviewers have noted, this textbook may not be the best introduction to statistics for people without a solid mathematical background. But even if your mathematical skills are on the rusty side, if you are willing to put forth the effort, I think that you will find yourself well rewarded with a more profound knowledge of statistics than you will find elsewhere. If on the other hand, you are looking for a quick primer on how to do simple regressions, for example, then you may be better off looking elsewhere.

An excellent introduction to econometric analysis!,
Jan Kmenta's "Elements of Econometrics" is a must read for all students of economics. It is a valuable reference guide which serves as an introduction to statistical regression methods that are used in economic modeling. It should be quite comprehensible to those who have had introductory courses in economics principles and statistics.

I used this text quite extensively in my graduate research when I was attempting to build a quantitative model to study the impact of the removal of trade barriers. I highly recommend it as an indispensible text which builds the foundation for a thorough understanding of the many statistical tools which have become necessary in conducting economic experimentation.

Very good reference- Review from Brazilian time series person
Very good book. I have been using this reference in my course and it has been very welcome by the students.
I would suggest this book for all people interested in Econometric theory.

A must-have for any econometrician
I have been using this book since grad school and continue to use it at work. I enjoy his clear explanation of concepts and would recommend it to the bookshelf of any applied statistician/econometrician. ... Read more

Product Description
The first cutting-edge guide to using the SAS® system for the analysis of econometric data

Applied Econometrics Using the SAS® System is the first book of its kind to treat the analysis of basic econometric data using SAS®, one of the most commonly used software tools among today's statisticians in business and industry. This book thoroughly examines econometric methods and discusses how data collected in economic studies can easily be analyzed using the SAS® system.

In addition to addressing the computational aspects of econometric data analysis, the author provides a statistical foundation by introducing the underlying theory behind each method before delving into the related SAS® routines. The book begins with a basic introduction to econometrics and the relationship between classical regression analysis models and econometric models. Subsequent chapters balance essential concepts with SAS® tools and cover key topics such as:

• Regression analysis using Proc IML and Proc Reg

• Hypothesis testing

• Instrumental variables analysis, with a discussion of measurement errors, the assumptions incorporated into the analysis, and specification tests 

• Heteroscedasticity, including GLS and FGLS estimation, group-wise heteroscedasticity, and GARCH models

• Panel data analysis

• Discrete choice models, along with coverage of binary choice models and Poisson regression

• Duration analysis models

Assuming only a working knowledge of SAS®, this book is a one-stop reference for using the software to analyze econometric data. Additional features include complete SAS® code, Proc IML routines plus a tutorial on Proc IML, and an appendix with additional programs and data sets. Applied Econometrics Using the SAS® System serves as a relevant and valuable reference for practitioners in the fields of business, economics, and finance. In addition, most students of econometrics are taught using GAUSS and STATA, yet SAS® is the standard in the working world; therefore, this book is an ideal supplement for upper-undergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for real-world careers. ... Read more

Customer Reviews (1)

A useful book for both students and practitioners.
This book provides an introduction to a variety of analytical methods and how to implement them using SAS.Each topic covered starts with a concise overview of the theory, and demonstrates how to implement the method using matrix algebra with SAS IML, then discusses examples using the relevant SAS procedures. Many of the examples are drawn from standard textbooks used for university econometrics courses.Very few colleges seem to use SAS as the programming environment for econometrics or statistics courses even though SAS is pervasive in the business world where most students will spend their working careers. This book will be useful for both students and practitioners. ... Read more

Product Description
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory.

Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications. ... Read more

Customer Reviews (16)

Econometrics of Financial Markets
Fresh look at the beating heart of the financial markets by one of the best people in the field.

CML: An Unnecessary Addition to a Saturated Literature
I was also skeptical of the negative reviews surrounding this book ("CML"). However after buying and reading this book, I now believe they had merit.

Simply stated, this book does not cater to its readers. If you have the prerequisites that the authors demand, then this book is comprehensive but ultimately below what ought to challenge you. And if you don't, then I guarantee you will be very lost. Unlike many similar volumes, CML is not self-contained (nor does it claim to be). And unlike many books that build a self-contained "model" of asset pricing dynamics, CML is full of literature-specific jargon and inconsistent notation. In fact much of this notation changes intrachapter.

Suppose you are a reader at the level CML insist their readers be. Then all the better to spend more time understanding Duffie's "Dynamic Asset Pricing," or Cochrane's veritable tour-de-force, "Asset Pricing." Both books are more contemporary and also at a better level for the readers CLM had in mind.

If you don't have the requisite knowledge, please ignore CML and try Luenenberger and Casella/Berger, as well as Greene for econometric-specific stats, Hamilton for time-series. You will not regret these purchases.

CML claims to fill a gaping hole in the secondary literature. But in reality, CML sits right in the middle of two types of readers, and caters effectively to none.

Last quartile on the subject
This book used to be a must the first time it has been published but after ten years it is getting old and the topic is now better covered by some others authors. The arch/garch section is really weak and this book by its sole is not enough to implement advanced models.
The authors also forgot to include practical implementation of the models with Splus or Matlab or whatever language, which is now almost a standard in many financial engineering related books.

An oldie but goodie
For the past ten years, this boook was the standard of financial time series and cross sectional analysis.There are several more recent books on the subject, but as the first good book in the field, it is still keeping up.Lot of the derivation in the book is a bit spotty - but that is expected at this level of sophistication and originality.There are some frustrating parts in the book, but if you cannot chew through that material, you should probably read an easier book.

Absolutely useless
I'm not sure what the audience for this extremely poorly written book is.Is it graduate-level students?If so, this book will drive them totally crazy and depressed, thanks to its confusing structure, lack of contextual motivation for the topics covered, and nonsensical, semi-rigorous mathematical treatment of the subject.Is it "quant" practitioners?If so, it'll leave them more confused and pessimistic about their trade than ever -- or just leave them feeling disappointed and frustrated, which was how I felt when I tried to read this book.

This book is so bad it serves as neither a textbook nor a reference.It has no value whatsoever.Want to know the technical details of VAR models and when to use them and when not to use them?You won't find it here.Ditto for GARCH models.Ditto for ECM models.Ditto for dynamic pricing models.I'm pretty well-grounded in advanced math, statistics, econometrics, and financial economics, and I have to confess I had no clue what the word and sentences and math notations in this book meant.The contents are totally incoherent.

Please do everyone a favor and don't buy this absolutely worthless book, so publishers won't be encouraged to kills trees in order to print such trash. ... Read more

Product Description
Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one-semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet.

All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM . Empirical examples and case studies specific to this volume include:

• Factor analysis with orthogonal regressions and using principal component factors;
• Estimation of symmetric and asymmetric, normal and Student t GARCH and E-GARCH parameters;
• Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization;
• Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management;
• Simulation of normal mixture and Markov switching GARCH returns;
• Cointegration based index tracking and pairs trading, with error correction and impulse response modelling;
• Markov switching regression models (Eviews code);
• GARCH term structure forecasting with volatility targeting;
• Non-linear quantile regressions with applications to hedging.

Customer Reviews (8)

excellent book
practical financial econometrics is a very useful book for all connected with the field of finance.

It is a real treasure. The description in the book is very practical. It successfully addresses and accommodates the issues that researcher encounters.

The efforts of the author for crafting such a master piece is highlyappreciable.The book offers much more via discussion forum as well. It is really wonderful and creative idea to remain connected with the world's greatest authority in the field of risk management through the websites. I think these website have been adding the life in the book and make it an alive entity.

Great work by the author.

Another great book by a leader in risk management
Like her previous book "Market Models", this book is very well written, clearly explained, and very complete.I like her style of writing because it's precise, intuitive, and goes straight to the point.Carol Alexander is a seasoned professional, and that is certainly reflected in this book.I like it a lot and recommend it highly.

Fabulous resource
This book is a "must have" for financial analysts.Carol Alexander is one of the best technical finance writers around, and has the ability to convey complex concepts in a way that practitioners can understand.

I particularly like the chapters on GARCH and copulas.She includes loads of examples that bring the subject matter to life.

A great insight for both students and practitioners
Carol writes both cogently and accessibly on financial mathematics here, covering a very broad area of topics in an easily intelligible manner -a welcome break from some of the drier mathematical texts. It definitely merits space on your desk if you're a practitioner or student - however small your desk is!

Dont miss it!
Just one hint, from somebody who learned a lot from Carol - if somebody with her experience decides to invest 5 years in sharing their understanding of the world of finance, I wouldn't miss the chance to read it! The scope of the book is unparalleled, and it doesn't come at the expense of thoroughness and clarity. And what you wouldn't get from four other books on those topics, is a unified, consolidated, approach to analysing and understanding areas which traditionally have been seen in isolation. I don't need to mention what difference it makes in practice, once you have the details, to be able to take one step back and see the bigger picture. ... Read more

Product Description

Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observations. It explores a wide range of alternative topics, including maximum likelihood and Bayesian estimation, various types of spatial regression specifications, and applied modeling situations involving different circumstances.

Leaders in this field, the authors clarify the often-mystifying phenomenon of simultaneous spatial dependence. By presenting new methods, they help with the interpretation of spatial regression models, especially ones that include spatial lags of the dependent variable. The authors also examine the relationship between spatiotemporal processes and long-run equilibrium states that are characterized by simultaneous spatial dependence. MATLAB^® toolboxes useful for spatial econometric estimation are available on the authors’ websites.

This work covers spatial econometric modeling as well as numerous applied illustrations of the methods. It encompasses many recent advances in spatial econometric models—including some previously unpublished results.

Customer Reviews (1)

Interesting new field
A very interesting new field that is bound to receive increasing attention in the future. ... Read more

Product Description

Advanced Econometrics is both a comprehensive text for graduate students and a reference work for econometricians. It will also be valuable to those doing statistical analysis in the other social sciences. Its main features are a thorough treatment of cross-section models, including qualitative response models, censored and truncated regression models, and Markov and duration models, as well as a rigorous presentation of large sample theory, classical least-squares and generalized least-squares theory, and nonlinear simultaneous equation models.

Although the treatment is mathematically rigorous, the author has employed the theorem-proof method with simple, intuitively accessible assumptions. This enables readers to understand the basic structure of each theorem and to generalize it for themselves depending on their needs and abilities. Many simple applications of theorems are given either in the form of examples in the text or as exercises at the end of each chapter in order to demonstrate their essential points.

Customer Reviews (6)

Consice feedback.
An excellent solid GRADUATE level classic econometrics book. At this level, it is very hard to find other books having the same quality as this one. Surely one of the best in the market. Enjoy!!!

Excellent reference, but not an easy read!
This book is justly considered a classic. It has been around for many years, and with some reasons. It provides a very rigorous treatment of many fundamental concepts in cross-section econometrics, such as linear and non-linear models, M-estimation, maximum likelihood, limited dependend variable models. It also has one of the best and more rigorous yet accessible treatments of basic asymptotic theory (the examples and countexamples in this section are uncommonly good). Amemiya is very very rigorous, and this a book where typos and sloppiness do now dwell. Overall, it is not an easy read, though, unless you have a very strong math/stat background, or you are genius. One thing I always liked about this book, indeed, is the very honest title, ADVANCED econometrics, not "Introduction" to econometrics. This book is mostly used as part of the reading list in second-year PhD courses in cross-sectional econometrics. I don't think it would be a good choice for a first year course. But if econometrics is a serious component of your professional life you will be happy to have Amemiya around, and you will keep reaching for it, once in a while. It is a bit too techinical, difficult, and dry to be my ideal textbook, but it is outstanding nonetheless. I find the chapters on asymptotic theory and limited dependent variables particularly well written. On the minus side, it is now a relatively old book, and you will find here many obsolete technical tools, as well as the absence of many important and modern techniques. In particular, note that you will NOT find anything here about nonparametric and semiparametric techniques, panel data, time series. There are many (very short) empirical applications scattered around the book, but most of them are (necessarily, given the publication year) very very obsolete.
Overall, still a great book highly recommended for people who are into advanced econometrics. But if you want an introduction to cross-section econometrics, you may want to look at other textbooks such as Greene, Ruud, Davidson-McKinnon, Hayashi (more time-series oriented) and especially the "graduate" Wooldridge (Econometric Analysis of Cross-Section and Panel Data), which in my humble opinion is currently the very best option around.
P.S. Harvard University Press also has merit of printing Amemiya on top-quality paper and choosing a very nice format for the book. It's a pleasure to browse its pages!

Jackpot/Bingo/Royal Flush
This is THE bible for understanding most empirical econ papers out there. I wished I had found it earlier.

Top choice
Both comprehensive and well-structured this book proves indispensable for anyone delving into the realms of econometrics. Starting from classical least squares the author guides the reader to time series analysis, gls,nonlinear simultaneous equations models up to qr and tobit models. Ifformulas are a necessary condition for a good study book in econometrics,the clear language of this book fulfills the sufficient condition for anybook in this category.

The best book I have read for this subject.
I strongly recommend this book as a textbook for this subject. After reading and using this book, I gained a solid knowledge of econometrics. ... Read more

Product Description
Introduction to Econometrics provides an introduction to econometrics using analytical and intuitive methods of the classical linear regression model. Mathematical notation is kept simple and step-by-step explanations of mathematical proofs are provided to facilitate learning. The text also provided to facilitate learning. The text also contains a large number of practical exercises, enabling students to practice what they have learned.

This new edition has been substantially updated and revised with the inclusion of new material on specification tests, binary choice models, tobit analysis, sample selection bias, nonstationary time series, and unit root tests and basic cointegration. The new edition is also accompanied by a website with Powerpoint slideshows giving a parallel graphical treatment of topics treated in the book, cross-section and time series data sets, manuals for practical exercises, and lecture note extending the text. ... Read more

Customer Reviews (4)

Superb
Clear and complete, often shedding light on nuanced details left unexplained elsewhere, this book is masterfully written. In the past I've found statistics and numerical methods to be nauseatingly dull but this book is interesting and keeps your attention.

Best introductory book
Although I have taken numerous courses in statistics, I have sometimes struggled to fully understand some of the key concepts in Econometrics. I finally decided to start from the beginning, and I read this book cover to cover. This text has made a world of difference for me as I am now able to pick up the standard Econometrics texts (Maddala, Woolridge, Greene, etc) and better understand more complex models. Another advantage of this text is that Dougherty uses Stata output and offers explanations on interpreting the output. This is a must read for anyone wanting a straightforward presentation of basic Econometrics.

An excellent introduction to the fields of studies
a clear introduction to econometrics without use of advanced mathematics.

A terrific book.
An excellent guide to someone starting out on an econometrics courese at university level. It really cuts through all the mathematical jargon that is usually found in books of this type and leaves the reader with a realunderstanding of the subject. ... Read more

Product Description
Econometric Theory and Methods provides a unified treatment of modern econometric theory and practical econometric methods. The geometrical approach to least squares is emphasized, as is the method of moments, which is used to motivate a wide variety of estimators and tests. Simulation methods, including the bootstrap, are introduced early and used extensively.
The book deals with a large number of modern topics. In addition to bootstrap and Monte Carlo tests, these include sandwich covariance matrix estimators, artificial regressions, estimating functions and the generalized method of moments, indirect inference, and kernel estimation. Every chapter incorporates numerous exercises, some theoretical, some empirical, and many involving simulation.
Econometric Theory and Methods is designed for beginning graduate courses. The book is suitable for both one- and two-term courses at the Masters or Ph.D. level. It can also be used in a final-year undergraduate course for students with sufficient backgrounds in mathematics and statistics.

FEATURES


·Unified Approach: New concepts are linked to old ones whenever possible, and the notation is consistent both within and across chapters wherever possible.


·Geometry of Ordinary Least Squares: Introduced in Chapter 2, this method provides students with valuable intuition and allows them to avoid a substantial amount of tedious algebra later in the text.


·Modern Concepts Introduced Early: These include the bootstrap (Chapter 4), sandwich covariance matrices (Chapter 5), and artificial regressions (Chapter 6).


·Inclusive Treatment of Mathematics: Mathematical and statistical concepts are introduced as they are needed, rather than isolated in appendices or introductory chapters not linked to the main body of the text.


·Advanced Topics: Among these are models for duration and count data, estimating equations, the method of simulated moments, methods for unbalanced panel data, a variety of unit root and cointegration tests, conditional moment tests, nonnested hypothesis tests, kernel density regression, and kernel regression.


·Chapter Exercises: Every chapter offers numerous exercises, all of which have been answered by the authors in the Instructor's Manual. Particularly challenging exercises are starred and their solutions are available at the authors' website, providing a way for instructors and interested students to cover advanced material. ... Read more

Customer Reviews (6)

Clear and self-contained
This is a very good introductory econometrics textbook for the mathematically well-prepared. No prior knowledge of econometrics or statistics is assumed, and the discussion of the necessary probability and statistics concepts is integrated into the main text rather than being relegated to appendices. All you need to read this book is a good knowledge of linear algebra and calculus. Once you finish it you will have a firm grasp of the basic methods and models used by econometricians and be prepared for going to more advanced sources like Wooldridge's Econometric Analysis of Cross Section and Panel Data or Hamilton's Time Series Analysis

Throughout the book Davidson and MacKinnon focus on developing intuition rather than on mechanical calculation. In particular, their geometric approach to ordinary least squares estimation is a must read. By focussing on the geometry and making clever use of the Frisch-Waugh-Lovell theorem, they make the properties of OLS very intuitive. Many of the standard results usually proved by opaque matrix algebra in other books, become clear and easy to prove in this framework.

The book also has the advantage of covering topics like GMM estimation, the bootstrap and numerical methods that cannot be found in older textbooks.

Yet, I have three quibbles with this book.

The first, minor one, is that its treatment of time series methods is too short, and unlike the rest of the book tries to trade off depth for breadth.

The second, bigger problem with this book is that it is entirely about econometric 'theory'. It teaches you how to find estimators and test statistics with good properties for particular models. But it does not train the student at all in the applied/methodological aspects of econometrics: given that I have a vague question about economic phenomena in mind, and given a bunch of data, how do I proceed? What questions can be meaningfully asked, how to choose between alternative models, how to present and interpret results, are questions that are given a short shrift in this book. Even data-based exercises are few and seem to have been reluctantly included.

The third problem with this book is that it completely ignores the Bayesian approach to econometrics. Though this is in line with the general frequentist dominance of the econometrics profession, I feel that without at least an introduction to the Bayesian approach, the training of an econometrician will remain one-sided.

The first two shortcomings of this book can be addressed by complementing it with Hayashi's Econometrics. Many interesting papers on methodology can be found in the book Modelling Economic Series edited by Granger.

Insufficient explanations/background info for an intermediate text.
I took the econometrics class from Davidson at McGill University that used this book, and it was not the best learning experience. This book is a good, rigorous "reference" text, with good definitions, for someone with a really solid knowledge of the subject, who wants an in-depth reference on matrix-based approach to econometrics. Or you just need a teacher who explains all the concepts and derivations in great detail and provides examples and solutions (which Davidson did not do in class or in this textbook). The text itself does not contain explanations of the material, so unless this is your 2nd or 3rd graduate-level econometrics class, expect to need several more accessible backup/background texts/teachers.

Best buy
Definitely the best and clearest book so far on this subject!! Written by a real top expert in this field (I took his course, the best eco. course I have taken). Much better than Green's book. If you are a serious graduate student in economics and management, especially those of you who are pursuing a PhD instead of only taking a course, it is the best for you. In-depth! Also frankly, it is not for a vaint brain and a guy with weak background.

Only with this book and Johnston & Dinardo's, read and enjoy, then you will understand econometrics absolute confidently.

Don't wast your money on other books!

Hayashi Much Better
Campared to Hayashi, Davidson and Mackinnon's book is too "prose-like" and this style in my opinion isn't pedagogically suited for a first serious look into econometrics beyond the undergrad level.A model's assumptions and relevant properties are scattered throughout a chapter, burried in paragraphs, which can be annoying or even comfusing when you need to reference back.Hayashi, on the other hand, presents models with clear listed assumptions, propositions, relevant derivations.DM's book is in my opinion extremely pedagogically inferior in this sense.

However, there're still things you may take away from this book.For example, they present the classical regression model in the framework of matrix project, subspaces, etc., which is not usually treated this way in other texts.This approach makes many tedious matrix manipulation easier.

In my opinion, if you are looking for your first metrics book beyond the undergrad level, definately go for Hayashi first.This is simply the BEST book in terms of learning.For some more depth and alternative pespective, then consider this one.

The best so far!
Of several graduate econometric textbooks I've read so far, this is the best. Compared to Greene (2003), its explanations are much clearer and its mathematical results are adequately derived. Compared to Johnston & Dinardo (1997), its coverage is more complete. Compared to Hayashi (2000), its discussion of IV method is more explicit. To be fair, however, Hayashi is also extemely well-written. ... Read more

Product Description
Using Stata for Principles of Econometrics is a cutting edge text which incorporates the capabilities of Stata software to practically apply the principles of econometrics. Readers will learn how to apply basic econometric tools and the Stata software to estimation, inference and forecasting in the context of real world economic problems. In order to make concepts more accessible, it also offers lucid descriptions of techniques as well as appropriate applications to today's situations. Along the way, readers will find introductions to simple economic models and questions to enhance critical thinking. ... Read more

Customer Reviews (1)

Good book for applied econometrics using STATA
This book will be useful if you have taken a intro/intermediate course in econometrics and know little bit about STATA. But if you have no background of either then this book is not for you.
I found this book very useful. Before reading this book I had taken 2 courses in econometrics. We used the book by Greene. The treatment of that book and that of my Prof. was very theoretical. I wanted a more " how to do the stuff" approach and this book satisfied that need.

... Read more

Product Description
This is a first course in Econometrics in Economics Departments also Economic/Business Forecasting. Statistics is a prerequisite but no calculus. This book helps the student understand the art of model building. With a clear four part structure, the text includes strong cover of time series and forecasting. Users can claim student accessibility, comprehensive, and appropriate and extensive examples. It requires no matrix algebra. It includes data disk. ... Read more

Customer Reviews (8)

Fine
Some mistakes in equations. but overall it is a good quality book. Time series part is not excellent. But as a entry-level book, it gives you a general idea of all kinds of knowledge you need in Econometrics.

muddy reading
The notation can be hard to follow if you don't have a grasp or natural incline for statistical regression.Steps are hard to come by in some problems because too many steps are skipped for a beginner.It is almost necessary to have at least a basic statistics background before reading this.

Even though I had a background and had read ahead, I had to depend on my professor to truly understand the material at all.If your professor has an accent or goes quite fast, and if you don't have classmates you can work with, using this book alone will be more than painful.

I would suggest a supplement such as "Using Econometrics: A Practical Guide (4th Edition should suffice) [Hardcover] by Studenmund" if you are just beginning to learn about regression.

Deceivingly more information than you think - half way between introductory and advanced
In sum: This book is half-way in between an introductory text (i.e. Wooldridge - Introductory Econometrics) and an advanced graduate textbook (Greene - Econometric Analysis).

Wooldridge's introductory textbook is certainly better suited for a first class in econometrics.Pindyck and Rubinfeld provide an excellent complement however, particularly for mid-level graduate students.Appendices show the matrix form derivations of most estimators, and provides a treatment of the GMM estimator, neither of which you will find in an purely introductory course.Really the appendices are where the more advanced treatments are offered to the interested reader.

Sections on forcasting and time series models in this book are greatly superior than what is offered in introductory texts (which usually is no presentation at all).

Pindyck and Rubinfeld do not waste a word in this textbook.There's a discussion on pretty much all the estimators, although some of these are short (one paragraph and no equations for the ordered probit - but you can't have it all!).

If you know nothing about econometrics then this is not the book for you.I was forced to buy it in my introductory econometrics class and had no idea what was going on.Then I had a competent instructor and lots of Wooldridge reading.This book helped me through Master's level econometrics and makes for good subway reading, but will definitely be shy of what you need for a PhD in economics.For PhD you will need Greene OR [Hamilton (1994) AND Wooldridge's Cross Section and Panel Data book].

Good beginners' book
This is a beginners' book, and for those, I would recommend its use, but only in addition to using it with Gujarati's. Pindyck's book is very simple and well explained. Its advantage over other books is that it is concerned with forecasting, something that other basic books do not do. It is a little bit more advanced than Gujarati's but lays between that one and Maddala's book.

Great equations, bad explanations
The subject of econometrics is difficult for the beginner. I have yet to encounter a text that does a great job at explaining both the concepts and the math required to be proficient in this field. I completed three courses, two undergraduate and one graduate level, for which this book was the required text. Like most of my classmates I was never able to fully comprehend the concepts behind the numbers using this text alone. Now that I have a better grasp of econometrics I will vehemently suggest that this text provides a poor verbal description of what a student is actually doing when analyzing data. I found myself reading the chapters 2 or 3 times and still felt unsure of what was going on. Where this book is strong is in its presentation of equations. I highly recommend supplementing this text with Peter Kennedy's, "A Guide to Econometrics," which gives excellent verbal explanations but de-emphasizes the math. These two texts together make a great study for a difficult subject. ... Read more

Product Description
A classic text in the field, this new edition features a new co-author and provides a well-balanced and comprehensive study of current econometric theory and practice for undergraduate or graduate study.Traditional topics are carefully blended with newer techniques and trends. While the authors of this text assume students have taken a basic course in statistics, they provide a complete appendix on basic statistical theory for those who may need a refresher. In addition, the authors include in an appendix a review of all relevant topics in matrix algebra.Includes data disk. ... Read more

Customer Reviews (11)

The Best Basis for a Knowledge of Econometrics
I have been a practicing econometrician for a total of about eighteen years in American industry (starting in 1980).I used an earlier version of Johnston in graduate school.The book of Johnston et al is, in my view, the very best place to start studying econometrics, and a great place to return to.As a practitioner, I know how valuable this book truly is.There are others of its ilk, but this one book will give the reader a very solid foundation in econometrics.In my experience, this is the bedrock on which my knowledge of econometrics rests.

the best book to start with
Few econometrics books will give you the mathematical detail and clear-cut logic that this book will give you. Too many beginner books just gives you the formulas without explaining why they work, but this book is very different to those.

If you are an Economics student do not cheat yourself by doing simplistic books on econometrics such as Studentmund, and mammoth books like Wooldridge, with alot of words but comparatively weak in mathematical rigour. Especially if you plan to continue with more advanced studies.

Mathematically it is on the same level as Gujarati's Basic Econometrics, but I think that Johnston's book is much more focused and clearer than Gujarati's and that the latter book is too big and time-consuming to be efficient. The former book works well both for beginners and for revision.

Prerequisites for the book are: basic calculus, matrix algebra and statistics. I.e any first-year books on business mathematics and statistics.

As a Masters student using this book for revision, I can say that this book is one of the best preparations you can have before more advanced studies with books such as Greene's Econometric Analysis. It is also a good preparation for studies into econometric time-series and forecasting.

Like a previous reviewer said, I also wish I had used this book during my Bachelor's, it would have made my later studies so much clearer and less frustrating.

In general content it covers pretty much what all beginner books covers: multiple regressions; tests for heteroskedasticity; AR,MA, and ARMA models; VAR etc.
The exception is its final chapter coverage of Tobit and Logit models, most beginners book will not teach you these methods.

The significant difference between this book and most others is that it will explain the mathematics behind what you are doing. This builds up a superior intuitive knowledge, which you simply do not get when you use books that only give your formulas (i.e. Studenmund etc). When the time comes and you write your first thesis you will glad to have used this book.

Also, this is not a book on software use, the book focuses on mathematical theory and not on how to do things using software.
Although I think it would be a nice idea for a future edition to include Stata or SAS instructions...as long as they do not change anything else in the book.

classical and modern econometrics
The bread and butter of econometrics are the statistical tools of regression and time series analysis. This is the fourth edition of a highly respected and widely used text on econometric methods.
The authors cover regression, correlation and least squares in Chapter 1, starting with the simplest linear regression involving a single regressor variable. This allows for an easy introduction to the basic concepts that provide the foundation for what is to come. Chapter 2 introduces the idea of using time as regressor variable. This is a natural lead-in to the more sophisticated time series models of later chapters. It presents important econometric concepts such as elasticity. It also provides some probability theory and time series theory.

Multiple linear regression is then introduced in Chapter 3 along with the important concepts of partial correlation, the Gauss-Markov theorem and variable selection criteria. Also, parameter restrictions are considered in Chapter 3. Chapter 4 includes diagnostic checking of models and the trick of introducing dummy variables into the model to handle dichotomous and categorical variables.

The material becomes more difficult and there is an increase in the mathematical sophistication in Chapter 5. More realistic econometric models enter the discussion and the techniques of maximum likelihood, generalized least squares and Lagrange Multipliers are needed. Instrumental variables are introduced to handle such problems as the error in variables model. The technique of two stage least squares is also introduced here. Basic time series ideas and theory were introduced in Chapter 2 but first really get exploited in Chapter 6 where the concepts of heteroscadasticity and autocorrelation are introduced. Formal univariate time domain analysis of time series including the ARIMA models and trending methods are covered in Chapter 7. More complications and advanced theory are in Chapter 8.

In Chapter 9, the subject of simultaneous equations is introduced. Generalized Method of Moment methods are presented in Chapter 10 as a reasonable and simple estimation approach that is valid in large samples.

Freedman, Navidi, Peters among others have pointed out that the estimators of standard error for parameters in many of the standard econometric methods depend on asymptotic theory and often are very poor for practical problem sizes. They have shown that bootstrap methods can provide much better estimates. It is therefore nice to see that these authors recognize the importance of these resampling methods They devote a full chapter to them. Chapter 11 "A Smorgasbord of Computationally Intensive Methods" covers such resampling techniques as permutation tests, the bootstrap ("nonparametric")and the parametric bootstrap and other computer-intensive methods such as nonparametric density estimation and regression.

Other problems that are unique to econometrics are covered in Chapters 12 and 13. Also included are appendices on matrix algebra and basic statistics along with useful statistical tables. The book also includes a diskette with data examples in ASCII files.

a bit dense
This is a good textbook for a graduate level student but if you're not familiar with Econometrics it might be a little hard to catch up.

excellent text!
Given my relatively weak background in econometrics and statistics, I was afraid I wouldn't be able to understand my graduate econometrics class.However, ever since I started reading from this book, I have managed to follow what my teacher is saying.The steps on how the equations are derived are explained, but without making it too easy for the reader.This textbook is a great help.No wonder this has been around for some time.Nevertheless, I was hoping that there's an answer key for the problems. ... Read more

Product Description
The student version of EViews 4.1, a leading econometrics software program, can be packaged with Addison-Wesley econometrics textbooks at a reduced student rate. EViews offers access to powerful statistical, forecasting, and modeling tools through an easy-to-use, Windows-based interface. It is ideal for anyone who works with time series, cross-section, or longitudinal data. Please contact your Addison-Wesley sales representative at www.aw-bc.com/replocator for more information. ... Read more

Customer Reviews (7)

Practical Econometrics
Studenmund has written a great undergraduate textbook for students wishing to use econometrics as a research tool.The book is light on math and doesn't offer any in depth discussion of the statistical theory behind econometrics.The book focuses on single-equation linear regression analysis with panel and time series data.I would recommend the book to beginning undergraduate econ students as well as business students and anyone in the social sciences.

econometrics
this was the best amazon purchace i have made, fast delivery and perfect condition. and twice as cheap than the books at my school store

Could be better
I looked into getting the 4th edition of this book because it's very cheap (i.e old edition). The text in both of these books is very very similar and indeed some parts are literally the same. Some sections of this book have pretty clear explanation, yet others seem to lack true substance. I would say if you are reading this book for pleasure its passable. If you are using it for a class and won't be doing the exercises at the end of each section; look into purchasing the 4th edition.

overall good product
It is a require for my class next sem, but the software with it, eview, can't handle large database like others can.

Excellent econometrics text book.
This is one of the better text books I have ever come across.If you need this for a class, feel lucky that your professor chose this and if you are buying it for "fun," pick this one. ... Read more

Product Description

Customer Reviews (2)

Excellent first year book
I have the Applied Econometrics not revised, published in 2006. The book is excellent for first year students. It is easy to understand and the formulas are stated in a simple manner, and commented on. I believe the book is even useful for those who are doing second year econometrics, though it will not be sufficient.

A great book
I bought the book by Amazon, It cameon time and the book is really helpful especially if you want to learn with eviews. ... Read more

Product Description

This is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of econometric models, from classical linear regression models for cross-section, time series or panel data and the common non-linear models of microeconometrics such as logit, probit and tobit models, to recent semiparametric extensions. In addition, it provides a chapter on programming, including simulations, optimization, and an introduction to R tools enabling reproducible econometric research.

An R package accompanying this book, AER, is available from the Comprehensive R Archive Network (CRAN) at http://CRAN.R-project.org/package=AER.

It contains some 100 data sets taken from a wide variety of sources, the full source code for all examples used in the text plus further worked examples, e.g., from popular textbooks. The data sets are suitable for illustrating, among other things, the fitting of wage equations, growth regressions, hedonic regressions, dynamic regressions and time series models as well as models of labor force participation or the demand for health care.

The goal of this book is to provide a guide to R for users with a background in economics or the social sciences. Readers are assumed to have a background in basic statistics and econometrics at the undergraduate level. A large number of examples should make the book of interest to graduate students, researchers and practitioners alike.

Product 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

Customer Reviews (5)

Decent introduction, not really mathematically elegant
I was compelled to buy this book because I am a practitioner who needed to know what it means to use a kernel regression to separate the trend from the cycle in macroeconomic statistics.I have been out of graduate school for a while now, and I am not up to speed on non-parametric techniques in econometrics.

The authors are adept at introducing the subject, and they use the natural logical progression: first they show how to estimate a density; and then they lead the reader to think of a kernel regression as the conditional moment of a bivariate density.

The author's notation confused me because to estimate a density is really to estimate a function at each of the points in its domain.Sometimes the authors made this point clear and sometimes their arguments obfuscated this subtlety.

A strength seems to be the breadth of the bibliographic references.Another strength seems to be the empirical applications that follow the cursory theoretical discussions.

The book will appeal to a middle-brow reader like myself, but mathematicians and good statisticians may find the analysis a trifle loose.

The best introduction to the field
I think this is the best introduction to nonparametric and semiparametric estimation to date. It covers an impressive amount of material, and the focus is on density and regression estimation. The exposition is clear, a lot of crucial results are proved, and an immense quantity of others are sketched or at least mentioned. Most of the book is fairly or very advanced, but all topics are introduced in a neat, simple, and intuitive way, so even a beginner can benefit from several parts of this book (previous good knowledge of math & statistics are still necessary, of course). Densities, regressions, discrete dependent variable models, simultaneous equation models, selection models, it's all in here. The field is expanding, but this book really has almost all you need to know about what the field has done until the publication date.

There is also a nice and useful appendix for many of the asymptotic results used in the book. The only drawback (besides a few typos, but not so many to be annoying) is the scant presence of empirical applications, but this book is not supposed to be a guide for applied econometricians (at least, not mainly), so I don't think it's a serious shortcoming. If you are more interested in the applied side of np regression, but you still want a rigorous treatment, you may look at Yatchew's "Semiparametric regression for the applied econometrician", in the same Cambridge series. For an even simpler, shorter, and low-tech introduction to np esimation of densities and regression, I would suggest instead the last pages of Ch. 3 in the splendid "The analysis of household surveys", by Angus Deaton.

This book is really worth its price (which, by the way, is kept at a very decent level by the worthy Cambridge University Press. I wish Wiley or Chapman and Hall stopped with their policy of immoral prices...). Highly recommended.

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

Product Description
Vol 1 covers fundamental econometric techniques and tools on recent advances in financial econometrics. Parametric and nonparametric, in continuous time and discrete time, these techniques and tools include Markov processes, a system for categorizing volatility concepts, a simulated method of moments indicator, and models for the timing of events. Together they reveal the ways that local characterizations can lead to long-run implications and how relationships between observed and unobserved values can be inferred.  Vol 2 covers important research even as they make unique empirical contributions to the literature. These subjects are familiar: portfolio choice, trading volume, the risk-return tradeoff, option pricing, bond yields, and the management, supervision, and measurement of extreme and infrequent risks. Yet their treatments are exceptional, drawing on current data and evidence to reflect recent events and scholarship.

• Set is the collection of Volumes 1 & 2


• Contributors include Nobel Laureate Robert Engle and leading econometricians


• Offers a clarity of method and explanation unavailable in other financial econometrics collections

Customer Reviews (1)

It is simply the BEST!
Both handbooks are really pleasent to read and easy to understand.The structure and articulation of the chapters are well designed and very nicely presented.The examples used through out the chapters are very useful which helps to tease out the technical aspects where many people gets stuck. The list of journal articles at the end of each chapters (Volume 1) are also very valuable and practical to relate the chapter topics to finance journal articles.Volume 2 is also very constructive and functional because it shows the direct applications of various models and mehods.Both handbooks (vol 1 & 2) are Excellent! ... Read more

Product Description
This highly accessible and innovative text (and accompanying CD-ROM) uses Excel (R) workbooks powered by Visual Basic macros to teach the core concepts of econometrics without advanced mathematics. It enables students to run monte Carlo simulations in which they repeatedly sample from artificial data sets in order to understand the data generating process and sampling distribution. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations.The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. ... Read more

Customer Reviews (8)

Big On Concepts
I give this book such a high score because it really does a great job at presenting the concepts.I know many people who attempt to perform a regression analysis, but have no understanding of what it is they are doing.This book does a great job at presenting what is going on and the effect data generations procresses have on the regression estimate.This book does not provide the detailed mathematics, but who cares.That can be picked from another book on linear modeling.All in all, this book is a good place to start when learning linear modeling.

Disapointed
Where is the application??

The author uses very little, if any, examples of applying econometrics to financial topics.The book is strewn with Larry Bird free-throw stats and SAT scores, height weight distributions and skiing training!I was expecting daily returns on the S&P 500.

I'm giving 2 stars because the CD included has some useful things, although the VB code is very amateurish.

Introductory Econometrics
Introductory Econometrics: Using Monte Carlo Simulation with Microsoft Excel
This book is a waste of time and money.It is basically a book on statistics.Verbose but not much teaching.90% of it I (as well as most people who have studied basic statistics) already know and do not need it.The other 10% I don't know, it does not teach me except by giving me a few button to press.

Excellent book for practitioners
Excellent book for everybody who would like to understand statistics and econometrics. It concentrates on regression and Monte Carlo simulation. I see the biggest value of the book in the way the statistical concepts are introduced. The authors build the intuition of the reader using meaningful examples, explaining thoroughly all the concepts and using Monte Carlo simulations to visualize them. Simulations are used as a tool for estimating parameters, but also support the reader's intuition and visualize the stochastic variables, their distributions, the role of chance in statistical inference, hypothesis testing etc. The examples in the book are not just illustration of the text, they are meant to open reader's eyes to some unexpected / counterintuitive features, that are difficult to capture just by studying the theory.

Tremendous Introduction To The Field ...
For the numerically inclined, this is one of the best introductory texts I have ever digested.This book is an essential tool for all who practice the art of analysis and are uninitiated with the fundamentals of econometrics. ... Read more

Product Description
This book deals with a number of mathematical topics that are of great importance in the study of classical econometrics.There is a lengthy chapter on matrix algebra, which introduces the reader from the most elementary aspects to partitioned inverses, characterisic roots and vectors, symmetric, orthogonal and positive (semi) definite matrices. The book also covers psuedo-inverses, solutions to systems of linear equations, solutions of vector difference equations with constant coefficients and random forcing functions, matrix differentiation, permutation matrices etc. Among its novel features is an introduction to asymptotic expansions, and examples of applications to the general linear model (regression) and the general linear structural econometric model (simultaneous equations).Professor Dhrymes is currently a Professor of Economics at Columbia University. Earlier he taught at Harvard, University of Pennsylvania, University of California at Los Angeles, and Monash University in Australia.He is a Fellow of the Econometric Society and the American Statistical Association. He has been a managing editor and editor of the International Economic Review (itl), and one of the founding editors of the Journal of Econometrics (italicize). Professor Dhrymes serves on the Editorial Advisory Boards of the Journal of Ecophometrics, and Econometric Theory. ... Read more

Customer Reviews (3)

Excellent Linear Algebra Review
Well, I was a student of Professor Dhrymes, so I am a bit biased as a reader. This book would be extremely helpful for a 1st year graduate course in Econometrics, as it contains many useful linear algebra results. I am glad it was reprinted, as we had had to use photocopies of the previous edition.

The Quality isn't a good explanatory variable for the price
Actually I do think that this book is too expensive, it is not worth to buy it. It spends five chapter (167 pages), more than 60% of the book, to teach matrix algebra, reader can easy read the detail matrix algebra review from many econometric texts such as Greene and Johnston. I don't think this part is helpful. For the last three chapters, it just discuss the material about OLS, all of these can be easy found in some introductory econometric text. I don't think it is very useful for anyone to read this book before studying other econometic text.

Best Book On Mathematical application in economics
I have done masters degree in MATHEMATICS and have done some management courses also. Here I am a PROFESSOR in a COLLEGE where students do B.SC. from LONDON university under EXTERNAL PROGRAM. One of the subjects I teach is "MATHEMATICS FOR ECONOMICS".This book has not only no alternate but also written in very simple way with technical examples and flow diagrams. My students last year got the DISTINCTION in this subject and this year I am also expecting DISTINCTION again from students. So I wanted to contact the auther and compliment the person. Finally as a teacher I would recommend strongly this book for the students of BSC. in Mathematics for economics as this book has a number of mathematical topics that are of great importance in the study of classical econometrics. And this is according to said syllabus. ... Read more

Product Description
Now in its fourth edition, this landmark text provides a fresh, accessible and well-written introduction to the subject. With a rigorous pedagogical framework, which sets it apart from comparable texts, the latest edition features an expanded website providing numerous real life data sets and examples. ... Read more

Customer Reviews (3)

Give me Matrix Algebra!
G.S. Maddala, who held the University Eminent Scholar Professorship in the Department of Economics at Ohio State University, was widely regarded as one of the professions most prolific and influential econometricians of the last forty years.Throughout the 1990s, Maddala was one of most often cited researchers, and he ranked among the top five most cited authors during the years 1988-1994, according to the Social Science Citation Index.His contributions to distributed lags, generalized least squares, panel data, and simultaneous equations have advanced the field tremendously.

Unfortunately, his "Introduction to Econometrics," now in its third edition, is, at best, a mediocre principles textbook.While his explanations of crucial ideas, such as least squares methodology, heteroskedasticity, or autocorrelation, are concise and extremely clear, a student who wants a more rigorous mathematical introduction to econometrics will be searching for another book.Linear algebra, which makes a number of proofs and tests far simpler and less burdensome to follow than calculus, is resigned to pages in the dark recesses of the appendix.Although these incidentals are well written, they remain peripheral, when they should be the focus of any undergraduate econometrics textbook.

To its credit, Maddala's text does an excellent job of explaining concepts and problems in plain English, which would do well to supplement a purely mathematical approach.The book is full of techniques and tricks that might be helpful to reduce problems of serial correlation and heteroskedasticity, and the later chapters do a very good job of introducing students to more advanced topics, such as panel data analysis and vector autoregression.Nevertheless, the book's treatment of time-series analysis isscattered and atrocious, and many students will find themselves searching for other texts especially for information on this area.

For students who do not mind a bit of mathematical simplicity and would rather seek to grasp the general ideas behind linear regression and its difficulties, G.S. Maddala's "Introduction to Econometrics" should be a good read.Yet, for students who want to pursue their knowledge of econometrics further, this book will most likely not be very helpful.As many courses taught at an undergraduate level tend to vary on their level of rigor, it probably will not hurt to have this book, but it may not help.

Very good, but not for everyone
I found this book to be a very useful bridge between my undergraduate statistics class and my graduate econometrics class.However, I would not say that it is an ideal first book on econometrics for the beginner.The best features of Maddala's text are: it's integrated treatment of different estimation methods, including least squares, method of moments and maximum likelihood; an appropriate level of mathematical sophistication, with appendices in several chapters deriving the main results using matrix notation; and a comprehensive coverage of important topics in econometrics for an introductory level text.When Greene's graduate text didn't make sense to me on first reading, Maddala really helped to clear things up.It was much better for this purpose than Kennedy's 'A Guide to Econometrics'.

I would have no reservation recommending this book to other readers.It is certainly better that Gujarati's 'Basic Econometrics.'However, I think Wooldridge's 'Introductory Econometrics' is a better choice for the beginner, especially in it's coverage of cross section and panel data and its abundance of examples.Unfortunately, since Maddala passed away before the third edition was completed the last three chapters, including the chapter on panel data, do not contain any exercises.

To sum up: An excellent text overall, with some minor shortcomings.

Critical, good, but sometimes too advanced for beginners
This is is a comprehensive and critical treatment of standard and modern econometrics. Its main strength is the presentation of recent developments in econometrics in terms accessible to advanced undergraduates (for instance, cointegration, exogeneity, model selection).However, it is too advanced to be used as a book for beginners.

In sum, I think the book is sometimes too elementary to be used for advanced students, while it was too advanced to be used alone as an introductory textbook. I would recommend using/reading selected chapters (such as ch. 12 on model selection), which are accessible as well as dealing with topics not normally included in many textbooks. ... Read more