Product Description
Designed to promote students' understanding of econometrics and to build a more operational knowledge of economics through a meaningful combination of words, symbols and ideas. Each chapter commences in the way economists begin new empirical projects--with a question and an economic model--then proceeds to develop a statistical model, select an estimator and outline inference procedures. Contains a copious amount of problems, experimental exercises and case studies. ... Read more

Product Description
A new book in the Econometric Exercises series, this volume contains questions and answers to provide students with useful practice, as they attempt to master Bayesian econometrics. In addition to many theoretical exercises, this book contains exercises designed to develop the computational tools used in modern Bayesian econometrics. The latter half of the book contains exercises that show how these theoretical and computational skills are combined in practice, to carry out Bayesian inference in a wide variety of models commonly used by econometricians. Aimed primarily at advanced undergraduate and graduate students studying econometrics, this book may also be useful for students studying finance, marketing, agricultural economics, business economics or, more generally, any field which uses statistics. The book also comes equipped with a supporting website containing all the relevant data sets and MATLAB computer programs for solving the computational exercises. ... Read more

Customer Reviews (2)

A pratical reference book
One good thing about this book is that there're lots of Bayesian model examples that you can search for. So, it's super pratical! On the other hand, if you want to dig deeply the Bayesian theories, then you need another kind of textbook.

Mathy but good.
I was looking for a little more explanation - but this is good. It is a little mathy, and I like other bayes econ books a little better. If you have some extra cash and are building a library - good book. If you need one text - others might be better. ... Read more

Product Description
Offering students a unifying theoretical perspective, this innovative text emphasizes nonlinear techniques of estimation, including nonlinear least squares, nonlinear instrumental variables, maximum likelihood and the generalized method of moments, but nevertheless relies heavily on simple geometrical arguments to develop intuition.One theme of the book is the use of artificial regressions for estimation, inference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, series correlation, heteroskedasticity and other types of misspecification.Other topics include the linear simultaneous equations model, non-nested hypothesis tests, influential observations and leverage, transformations of the dependent variable, binary response models, models for time-series/cross-section data, multivariate models, seasonality, unit roots and cointegration, and Monte Carlo methods, always with an emphasis on problems that arise in applied work.Explaining throughout how estimates can be obtained and tests can be carried out, the text goes beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package.A comprehensive and coherent guide to the most vital topics in econometrics today, this text is indispensable for all levels of students of econometrics, economics, and statistics on regression and related topics. ... Read more

Customer Reviews (13)

Comparison to Hayashi
We were recommended to use this book as a complement to Hayashi, which we had used as our initial primary text for the 2nd and 3rd quarter of a first-year graduate econometrics sequence.

I think I would have found the exposition here rather challenging had this been my initial text. A few comparisons between the two books:

H - GMM as organizing principle.
D&M - Least squares as organizing principle.
I think the latter was in many ways a more intuitive way of viewing these techniques (for me), but perhaps provides a less fully integrated view of the estimators.

H - Matrix algebra and first order conditions as justifying estimation techniques.
D&M - Geometric projection as justifying estimation techniques.
The geometry is a powerful tool for understanding these concepts, but I think serves me better as a complement rather than a primary motivator.

H - Treats homoskedasticity and lack of serial correlation as special cases.
D&M - Treats heteroskedasticity and serial correlation as extensions of iid models.

H - Treats nonlinear models as extensions.
D&M - Treats linear models as special cases.

H - Offers a large number of economic applications.
D&M - Basically entirely theoretical in its justification of theorems and techniques.
This would be among the most frustrating things about using D&M as a primary text.

Just a few thoughts that might be useful to someone considering this book. The organization around least squares is very useful, I think, and a geometric intuition for econometrics must be a powerful tool as one progresses in the field.

A nice book
Mackinnon's is a good one. But I would say it's a bit more difficult in terms of math and depth of expanations than Greene's one.
Nevetheless, that's my choice!

Much Better Than Green's In Terms of Quality and Price.
Green's textbook was the assigned text when I took my econometrics sequence.Like many others, I found it not well written and the explanations are pretty bad. Also, Green's is priced sky-high (around $100 for a brand new copy).

Davidson and MacKinnon is different.Both expositions and explanations are clear and easy to follow. I was so delighted after picking up a copy from the libarary. This is the one econometrics students should have. The price is also hard to beat. The reason I think it is not widely adopted is because of the geometric analysis of regression (Chapter 2).But if you don't like geometrics, you can simply skip it.

An improved version of this book is just published under the new title "Econometric Theory and Methods".This new version contains a chapter on unit-root and cointegration, as well as some new numerical methods.I urge interested buyers to take a look at the new version.

No one like this
It's a nice piece of work.
There is no one like this.
The only problem is the way the contents are presented. There is no a logical order that help us in a course. I agree that there is not a clear structured inside the chapters or in the entire work. But this is the book that reach the deepest point being readable. Another books are better structured or more intutive but too superficial or old-fashioned.
With the modern computers and software the old classical books based on small sample theory are unsuitable. Davidson and MacKinnon point us to the econometry of the future.
It would be a good idea to combine this book with Berndt's one on applied econometrics, plus a good software like Stata 8 or matrix-based programming software like MATLAB.
That's the best way to access the econometry.

This is the book!
I do not know better book on nonlinear estimation and inference in econometrics.

Overall the book is very well written and relatively easy to understand, considering its subject. However, if you have not been introduced to linear econometrics, the book can become very hard, mainly if the reader is not acquainted with matrix algebra.

The first chapter on the geometrics of regression is simply marvelous, although a better picture is in Ruud's.

The style is someway formal, but different from the traditional lemma-theorem-proof-corollary way. This makes the book easier to read.

Future improvements include:

a. More examples (please);
b. Make the early 2 chapters on asymptotics clearer;
c. Extend the GMM approach interconnecting it with other chapters (it's more general);
d. Put exercises, with solutions, with selected solutions, whatever, but exercises, including computational ones;
e. Some economics - this does not mean applications per se, but it means to explain where and why such techniques are necessary in the real world. ... Read more

Product Description

The book provides an up-to-date survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models. The book starts with a presentation of the benchmark Poisson regression model. Alternative models address unobserved heterogeneity, state dependence, selectivity, endogeneity, underreporting, and clustered sampling. Testing and estimation is discussed. Finally, applications are reviewed in various fields.

Customer Reviews (1)

Valuable Guidance to Count Data Analysis
Since publication in 1984 of two pathbreaking articles by HHG and GMT, many new econometric models and methods for count data have been developed and applied variously in cross-section, time series, and panel data situations. But there has been very few econometrics books guiding thosemodels and methods. That's why this book is valuable. It brings together adiverse body of literature that until now were available largely in pieces.The emphasis of the book is on methods for cross-section data. It shouldhave been more desirable to give same weight on explaining the modeling ofpanel count datawhich in recent years econometrics literature has moredevoted to. This book may be very useful for applied researchers because itpresents the main ideas underlying a variety of methods to overcome theproblems of the restrictive Poisson specification and proper interpretationof underlying stochastic process. ... Read more

Product Description
This short, concrete, and to-the-point book guides students through this vast field of conflicting opinions. The book begins from the premise that students benefit most from seeing a balanced treatment of all available views. For instance, this book provides coverage of both ad hoc and optimizing models. It also explores divisions such as flexible price versus sticky price models, rationality versus irrationality, and calibration versus statistical inference. By giving consideration to each of these 'mini debates;, this book shows how each approach has its good and bad points. ... Read more

Customer Reviews (1)

International Macroeconomics and Finance
This is a well written and short concreted book. I makes a good combination of both econometrics and theoretical methods for those who have a background on these topics. The book is suitable for graduate students. ... Read more

Product Description
This book is intended for use in a rigorous introductory Ph.D. level course in econometrics, or in a field course in econometric theory. It covers the measure -theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis.Therefore, this book is uniquely self-contained. ... Read more

Customer Reviews (1)

Definitely Serious Stuff for A Beginner
I have been searching for a real solid introduction to statistics for a long time. And this book is the most in-depth yet readable book so far. It covers advanced topics in statistics such as the F and t distribution formulas, the convergence theorems, the sigma-algebra, and knowledge in matrix, where there is a whole section on determinants!

If you are a serious student in Statistics, Econometrics or Quantitative Finance, I suggest you must have this book along with you as "what-is" reference, since most schools nowadays bypass these fundamental knowledge in courses and hinder your understanding of the whole structure. ... Read more

Product Description
Designed to promote students' understanding of econometrics and to build a more operational knowledge of economics through a meaningful combination of words, symbols and ideas. Each chapter commences in the way economists begin new empirical projects--with a question and an economic model--then proceeds to develop a statistical model, select an estimator and outline inference procedures. Contains a copious amount of problems, experimental exercises and case studies. ... Read more

Customer Reviews (6)

Great Book!
This is a far better Econometrics textbook than I have used in the past.It is far more intuitive to use, with much greater summary and explanation.Service from Amazon was as usual exceptional.

Excellent on intuition and good preparation for Greene
This book is very good at giving brand new students of econometrics the intuition behind concepts. At the same time, it does not ignore the mathematics (calculus and linear algebra) and thus it is a good preparation for Greene.
One thing I don't like about this book is notation. For example, the book refers to the mean as beta instead of mu. I do prefer Gujarati?s notation much better.
It would also be very nice to have an update of this great textbook since it was written in 1993.

Thank you,

The best undergraduate econometrics book
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 only weakness of the book is that it focusses almost exclusively on estimation under the assumption that error terms are identicallly and independently distributed (iid).However, all other undergraduate econometric textbooks (and a lot of graduate ones too!) display this preoccupation, so Griffiths et al are no worse than their rivals.

An update to this book would also be good, as it's nearly 10 years old now.

However, its good points far outweigh these weaknesses.

Good applied econometrics for undergraduates
This book is excellent for beginners in econometrics. It is particuarly useful for people not wanting to know all the mathematics ( algebra and matrix approach) behind econometrics. Students doing term papers find it very practical as they want to know how to go from theoretical econometricsto empirical econometrics.

The Perfect Bridge to Greene
This is a great beginner's textbook. Whereas some, like Greene, are going to be too hard for some beginners, and others like Gujarati are far too basic, this book strikes an excellent balance. It's best feature is all theworked examples is gives you, including the raw data used, allowing you toenter the data into a statistical package and make sure you get the sameresult. This is a great confidence builder! ... Read more

Product Description
The editors are pleased to offer the following papers to the reader in recognition and appreciation of the contributions to our literature made by Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. The basic themes of this part of Volume 20 of Advances in Econometrics are time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, the application of the technique of boosting in volatility forecasting, the use of different time scales in GARCH modelling, out-of-sample evaluation of the 'Fed Model' in stock price valuation, structural change as an alternative to long memory, the use of smooth transition auto-regressions in stochastic volatility modelling, the analysis of the "balanced-ness" of regressions analyzing Taylor-Type rules of the Fed Funds rate, a mixture-of-experts approach for the estimation of stochastic volatility, a modern assessment of Clive's first published paper on Sunspot activity, and a new class of models of tail-dependence in time series subject to jumps.

*This Series: Aids in the diffusion of new econometric techniques
* Emphasis is placed on expositional clarity and ease of assimilation for readers who are unfamiliar with a given topic of a volume
*Illustrates new concepts ... Read more

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Discusses the mechanisms by which securities are traded and economic models of asymmetric information, inventory control, and cost-minimizing trading strategies. ... Read more

Customer Reviews (3)

The market microstructure bible
This book should be on the shelf of anyone interested in market microstructure.

Being from 2007, it's much newer than Maureen O'Hara's Market Microstructure Theory, from 1998. And you can feel that when reading. I mean, Hasbrouck is more updated, citing very recent pieces of research.

Empirical Market Microstructure
Nearly fifteen years has passed since the publication of Maureen O'Hara classic but, if anything, the subject became even murkier. In my opinion, the discipline of market microstructure consists of disjointed models, none of which is directly testable and numerous empirical results poorly connected between each other.

The work of premier practitioner of the subject, Prof. Joel Hasbrouck (NYU), helps the reader to untangle this mess, if it is at all possible. In this respect, I will prefer it, thumbs up, to my own book "Microstructure and noise in financial markets." It is naturally skewed towards author's own results, hence, it is heavily econometric. But, unlike many original papers, math is elegant and easy to follow. Furthermore, the reference section contains incomplete but excellent bibliography, which allows the reader to follow disparate models sometimes included in the main text in sketchy details.

I would not recommend this book for the first acquaintance with the subject-- for this, dependent on whether you have theoretical or practical bent-- the books by M. O'Hara and L. Harris still remain indispensable. But the student in the field will find a lot of valuable material and insights, and writing my own book, I kept "Empirical Market Microstructure..." not far from my working table.

Knowing the Market
The book by Professor Hasbrouck "Empirical Market Microstructure" is an excellent additon to the recent literature on market microstructure. by focussing on empirical modelling of various aspects of market microstructure, the book fills a much needed gap between high end practionaers and academia. It complements the theoretical book by Professor O'Hara, and concisely presents a great deal of empirical work done by Prof. Hasbrouck himself in this field.

Ocassionally the book reads like a cook book and at times like a summary of the papers; for people who have read his earlier papers, the material sounds a bit repititive.

some more effort on highlighting the differences in empirical results between equity, FX and Fixed income markets, and reconcilling with theoretical ideas would have been far more informative.

... Read more

Product Description
In this book, Paul A. Ruud, a well known and respected scholar, makes sense of this complex field by presenting a careful intuitive understanding of the subject. He teaches the reader to think like an econometrician, not like a person simply learning how to get the "right" answers. ... Read more

Customer Reviews (5)

Another excellent econometric textbook
This is another good, modern textbook on parametric, cross-sectional econometrics (don't look for non/semi-parametric or time-series econometrics in here). It is, I think, in the same league as Wooldridge, which is however less technical and spends more time describing empirical applications. I think Ruud is a very nice addition to an econometric shelf. The notation is good, and the math/stat appendix is one of the best I have ever seen (the section on multivariate differentiation in particular is outstanding and very useful). Overall, if you want to have 3 *relatively* basic books on parametric cross-section econometrics, I think this is a good companion to Wooldridge and Cameron and Trivedi (a nice compendium of applied tools, which also includes some non-parametrics, for which the best introduction is likely Pagan and Ullah). If time-series is important to you, Hayashi is a good choice. As you may have guessed, I am not a big fan of Greene, which I do own but never look at.

The book is OK, but not good really
I gave it a one-star to balance those biased 5 stars. The first part of the book is pretty good, intuitively explains what an OLS regression is really like geometrically. The second part of the book is just horrible. The author just goes on and on and on without being able to clearly explain the theories. The book is used in my program for one year and then stopped. Now we use Yamashi's book, which is much better.

Simply the Best
I have just completed reading Professor Ruud's textbook from cover to cover.It is the clearest, most insightful graduate-level econometrics book I have read.Whereas many texts seem to be compendiums of theorems and proofs with little in the way of explanation, Ruud takes the time to explain things thoroughly.At over 800 pages, however, Ruud's book is never verbose.A good explanation takes time, but Ruud never takes more time than is needed. Yet, in addition to all concepts being thoroughly explained, they are introduced with practical examples, and--what is most amazing--the proofs are built up systematically in such a way that you can actually read though them and be enlightened rather than convinced.

Previous econometrics texts have a "Losing sight of the forest for the trees" sort of feel to them.Ruud's text, however, works like the old drill Seargent in the Kipling poem who explained his teaching method as "Firsts I tells 'em what I'ms goings to tells em; then I tells 'em; and then I tells 'em what's I tolds 'em."Ruud does this by first building up the fundamental concept of matrix projection.Then he demonstrates how that can be used to explain Ordinary Least Squares regression.Then he adds onto that all the common assumptions: independent, identically distributed errors; normality of the errors, etc.He builds things up one assumption at a time.And all the while he tellsyou what he's doing and why the content of each chapter matters and how it is related to what has come before and to what will come afterwards.

But, then--in a master stroke of pedagogy--he tears it all down.He starts taking away, one at a time, all the assumptions like normality that he just spent chapters building up and shows how econometricians deal with matters when they *do* in fact remove the standard assumptions.In this way he can introduce consistent estimators, non-linear regression, latent variables, and so on as what they were historically:practical solutions needed when the assumptions of theclassical model fail to hold.

By systematically showing which assumptions imply which results and then showing how to deal with things when a given assumption fails to hold, Ruud's book produces a better econometrician.Too often have previous books left previous readers unable to really understand the art of data analysis, which involves taking a data set, seeing what assumptions can be fairly made about it, and then analyzing it given those fairly made assumptions.

Professor Ruud deserves many plaudits for writing what will surely become the standard text for the next generation of graduate students.

Econometrics finally makes sense!
Econometrics seemed to me a technically demanding subject with results that are either magic (stated without derivation) or based on some arcane mathematical tricks. But after reading Ruud's textbook, econometrics finally makes sense. It provides a great exposition of graduate econometrics with all the main results and techniques clearly spelled out. Furthermore, it actually has derivations of the results. I also really like the emphasis on the geometry behind econometrics; it provides a systematic approach and the results even become intuitive.

So, if you want more than just a recipe book and actually understand econometrics, read this book!

Excellent text
This is the best text I have encountered for an advanced graduate text in econometrics.The style is less terse than Amemiya, but Ruud does not skimp on content.There are many (useful) details, particularly on somesubjects other authors assume (in my experience, incorrectly) the studentknows.Finally, the geometric approach Ruud frequently espouses issomewhat unique in econometric presentation, and one I find quite useful. ... Read more

Product Description
"Applied Econometrics for Health Economists" introduces readers to the appropriate econometric techniques for use with different forms of survey data, known collectively as microeconometrics. The book provides a complete illustration of the steps involved in doing microeconometric research. The only study to deal with practical analysis of qualitative and categorical variables, it also emphasises applied work, illustrating the use of relevant computer software applied to large-scale survey datasets. This is a comprehensive reference guide - it contains a glossary of terms, a technical appendix, software appendix, references, and suggestions for further reading. It is concise and easy to read - technical details are avoided in the main text and key terms are highlighted. It is essential reading for health economists as well as undergraduate and postgraduate students of health economics. "Given the extensive use of individual-level survey data in health economics, it is important to understand the econometric techniques available to applied researchers. Moreover, it is just as important to be aware of their limitations and pitfalls.The purpose of this book is to introduce readers to the appropriate econometric techniques for use with different forms of survey data - known collectively as microeconometrics." - Andrew Jones, in the Preface. ... Read more

Customer Reviews (8)

Simplifies econometrics!
A true masterpiece in the field of econometrics. It has placed within an updated context the scattered variables taught in econmetrics years ago, simplifying the use of tables and formulas.As one reviewer puts it succinctly, "The main reason behind the success of this textbook is its organization by sections of data(cross-sectional,time-series etc).Its examples simple but not mundane and the solutions to the exercises available upon registration". I couldnt agree more!

Woolridge-at last,a book with a structure that makes sense
I have come across many introductory econometrics books, both in my native language(Greek) and English;however,not one was as clearly structured and helpfully outlined as this excellent textbook!When you are not a math whiz and not too comfortable with abstract explanations of concepts such as heteroscedasticity,unbiasedness etc,and desperately in need of a step-by-step introductory approach,this is the book for you.Compared to Stock and Watson,this book renders the aforementioned one almost useless,as heavy as this word might sound! The main reason behind the success of this textbook is its organization by sections of data(cross-sectional,time-series etc).Its examples simple but not mundane and the solutions to the exercises available upon registration(Stock and Watson do not even offer students the opportunity to pay for access to solutions!!!).To cut a long story short,if you want a no-nonsense introductory econmetrics textbook or if you are desperate with other textbooks you have encountered until this moment,do not hesitate:this investment will most definitely pay you back and then some!!!

Petros,former economics student,Greece

Lets vote this one the most helpful review
I'm a student at osu majoring in actuarial science and economics (actuarial science is a math finance thing... i get this question a lot) and so I have read through several math, statistics and econ texts. This is by far the best one i have ever come across. This is my one and only review on amazon and i am only writing it because i feel so compelled to tell you guys about it and express my over exuberance for finding a good math book. The price is ridiculous and so i suggest you try to find a used copy or an international edition (which may or may not be legal). Anyhow hopefully the author occasionally checks his amazon reviews of his book and if he does i hope this inspires you to write more math books.

Great for Self Study
I bought this text so that I could understand/interpret results and methodology in empirical business research papers. Unlike most statistic-related books I've seen over the years, this text is actually clear and focuses on providing great explanations and examples rather than proofs and derivations. Thus, this book is a great choice for self study, and it's been a huge help thus far in my PhD program.

Graduate School
Recently completed a 10-week / 2-credit graduate-level course where we used this textbook for 80% of the course work.I believe they used up the entire Greek alphabet!I have read dozens of text books and this one is definitely above-average; it may be in the top quartile. ... Read more

Product Description
This book explains how to use R software to teach econometrics by providinginteresting examples, using actual data applied to important policy issues. Ithelps readers choose the best method from a wide array of tools and packagesavailable. The data used in the examples along with R program snippets,illustrate the economic theory and sophisticated statistical methods extendingthe usual regression. The R program snippets are not merely given as blackboxes, but include detailed comments which help the reader better understandthe software steps and use them as templates for possible extension andmodification.

Contents: Production Function and Regression Methods Using R; Univariate TimeSeries Analysis with R; Bivariate Time Series Analysis Including StochasticDiffusion and Cointegration; Utility Theory and Empirical Implications; VectorModels for Multivariate Problems; Simultaneous Equation Models; LimitedDependent Variable (GLM) Models; Dynamic Optimization and Empirical Analysisof Consumer Behavior; Single, Double and Maximum Entropy Bootstrap andInference; Generalized Least Squares, VARMA, and Estimating Functions;Box-Cox, Loess and Projection Pursuit Regression. ... Read more

Product Description
Tools to improve decision making in an imperfect world

This publication provides readers with a thorough understanding of Bayesian analysis that is grounded in the theory of inference and optimal decision making. Contemporary Bayesian Econometrics and Statistics provides readers with state-of-the-art simulation methods and models that are used to solve complex real-world problems. Armed with a strong foundation in both theory and practical problem-solving tools, readers discover how to optimize decision making when faced with problems that involve limited or imperfect data.

The book begins by examining the theoretical and mathematical foundations of Bayesian statistics to help readers understand how and why it is used in problem solving. The author then describes how modern simulation methods make Bayesian approaches practical using widely available mathematical applications software. In addition, the author details how models can be applied to specific problems, including:
* Linear models and policy choices
* Modeling with latent variables and missing data
* Time series models and prediction
* Comparison and evaluation of models


The publication has been developed and fine- tuned through a decade of classroom experience, and readers will find the author's approach very engaging and accessible. There are nearly 200 examples and exercises to help readers see how effective use of Bayesian statistics enables them to make optimal decisions. MATLAB? and R computer programs are integrated throughout the book. An accompanying Web site provides readers with computer code for many examples and datasets.

This publication is tailored for research professionals who use econometrics and similar statistical methods in their work. With its emphasis on practical problem solving and extensive use of examples and exercises, this is also an excellent textbook for graduate-level students in a broad range of fields, including economics, statistics, the social sciences, business, and public policy. ... Read more

Product Description

World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.

Product Description

Customer Reviews (4)

Probably the best math-econ book for anyone who wishes to pursue a Ph.D. in economics
As a junior economics professor, I have been through a number of math-econ books (which means quite a lot of torture in the learning history). CSZ (Corbae, Stinchcombe, and Zeman) ranks the top place on my recommendation list of math-econ books for anyone who wishes to pursue a Ph.D. in economics.

I can not agree with the authors more that "this books bridges the gap that has separated the teaching of basic mathematics for economics and the increasingly advanced mathematics demanded in economics research today." They have done a fantastic job in building up this bridge. During the learning of math econ, a common problem (insofar as I know) is that after you finish the class with a good grade, you still do not know how to apply those math tools in the research practice. A first group of math-econ books are just all abstract math (sometimes, there are pure math books), including tough and intimidating real analysis, functional analysis, etc.... Yes, you can really learn a lot of math (after many many sleepless nights like I did before), but...but, those math are not coupled with econ questions. Such a course might help you understand the technical papers, but might not teach you well how to construct econ models by yourself. A second group of math-econ books do not set a high-level of technical requirements. They might teach a lot of comparative statics and linear algebra, followed by very limited of real analysis. If you merely take a math-econ book in the second group, I guess you will not make sense of SLP (Stokey, Lucas and Prescott).

Now CSZ fills the gap between the two groups among math-econ books. Starting from the very beginning, real analysis with its econ application is introduced in a step-by-step, self-contained, and sometimes entertaining approach. If you have a solid undergraduate background in calculus and linear algebra (do not tell me you got a C in those courses!), you should be able to completely understand the beginning chapters which provides proofs of theorems, (remarkably!) examples, and inspiring exercises. Once you work out those exercises in the beginning chapters, more profound math stuffs in the later chapters should be

In an accessible approach, it introduces rigorous math that is demanded by advanced econ research. Interestingly this textbook does not even have a chapter called "comparative statics", "constrained optimization", etc., but it beautifully embeds those stuffs into the discussions of logic, set theory, etc. In a similar approach does CSZ provide a math foundation for econometrics after Chapter 6. CSZ's introduction to metric spaces in the second and third sections of the textbooks makes me very conformable (i.e. better equipped) when I go back to those graduate econometrics textbooks (especially, if you want to study Paul Ruud's Introduction to Classical Econometrical Theory). So, it is perhaps a must-read material before you touch those popular graduate econometrics textbooks, such as Greene, Hayashi, and Ruud.

It is probably the best companion (besides Nolan Miller's Micro Notes) to MWG's Microeconomic Theory. I recognize that CSZ adopted MWG as an important reference for this textbook.You do not really have to study CSZ before you start learning MWG, but if you are ambitious to work out all the C-level questions in MWG, you are better to grab a copy of CSZ on your desk as well.
I would say, CSZ (as an intro to math econ) is very much like Wooldrige's Intro econometrics, in a sense that both books teach you the theories AND how to apply the theories in your OWN research. They are both textbooks and research guides.

Finally, I wish the next edition of CSZ could provide some discussions/examples on uncertainty and public econ. But of course, no single volume can cover every corner in the economic theory and econometrics.

An excellent math econ book
I am not currently teaching Math Econ, but when I do again I intend to use this book.One problem with the typical first-year econ grad student is that they have little experience with theorem-proof mathematics; they are more familiar with applied mathematics, meaning that they set about to solve a given problem, than they are with the logical process of proving that problem has a solution.CSZ do a nice job of easing the student into this process, starting with the basics of mathematical logic.And they manage to cover the basics as well as some advanced topics.

My only quibble is that the book gives too little attention to dynamic programming and recursive competitive equilibria.These methods are now a standard part of any macroeconomist's toolkit, but students rarely get a mathematically careful presentation that is also appropriate as a textbook (SLP is more like a reference book, albeit one where the reader must provide their own proofs).CSZ of course cannot do everything in one book, even one that is 670 pages long, but I personally would have liked to see more on these topics.

As a whole, the book fills a clear need in the profession and recommend it to all incoming PhD econ students -- you should read the first couple of chapters before arriving at school in the fall.It will give you a leg up over your classmates (or catch you up) and make the transition to grad school a bit easier.

An impressive collection of tools from Mathematical Analysis applied to different fields of economics
Every undergraduate who wishes to pursue a PhD in economics is told to take a sequence of certain math classes, the hardest of which is usually real analysis. I took a real analysis course based on Rudin's blue book and found it a painful transition from my previous courses. I had to quickly get used to reading and writing proofs. It was unclear if and how these tools can be used in economics. This book is a great solution because it helps the reader to gently transition to writing proofs and is chock-full of applications at every step.

This book has three parts: The first 3 chapters introduce the reader to abstract math and proof writing techniques. The second part, chapters 4-8, teach standard material that is often covered in a 2-semester sequence on real analysis. This includes metric spaces, measure theory and probability, and Lp spaces. This also includes a chapter on convex analysis which is rarely covered in books on real analysis designed for math students. The last 3 chapters cover advanced material which is useful for readers interested in economic and econometric theory.

The thing that I liked most about this book is its impressive collection of applications to economics, here are some:

The first chapter on Logic discusses general equilibrium and proves the first fundamental theorem of welfare economics. In the second chapter on set theory they discuss lattices and apply these tools to introduce Monotone Comparative Statics (MCS) (which was a hot topic in the 90's and hasn't even been introduced into most microeconomics textbooks yet, not even in MasColell). They explain how MCS is a generalization of regular Comparative Statics based on the implicit function theorem, which requires strong assumptions about differentiability. The discussion of real numbers in chapter 3 is very thorough, so an econ student doesn't need to follow every detail but in case he gets curious about some property of the real numbers he can always refer back to it.

In chapter 4 they talk about the finite dimensional vector space of real numbers. This is a more gentle approach than I experienced when I learned analysis, because we jumped straight into general metric spaces. They apply these tools to Linear Dynamical Systems, Markov Chains, and most notably to Dynamic Programming. Chapter 5 covers finite-dimensional convex analysis, which includes all kinds of convex separation theorems and applies these tools to prove the second fundamental theorem of welfare economics. They also cover everything you ever wanted to know about constrained optimization, the implicit function theorem and Kuhn Tucker conditions in horrendous detail.The authors proceed to discuss general metric spaces and include more applications to dynamic programming generalizing many of the topics discussed in previous chapters.

Chapter 7, which is a bit more technical than the previous chapters, discusses measure theory and measure-theoretic probability. This includes applications to all kinds of useful limit theorems and 0-1 laws, and a cool application to quantile estimation on page 405 and state dependent preferences on page 445. Chapter 8 introduces Lp spaces with applications to Statistics and Econometrics including a theoretical discussion of parametric and non-parametric regression. This chapter also includes an application to Artificial Neural Networks.

I haven't spent much time on the final 3 chapters, though I look forward to studying Chapter 11 on expanded spaces (Nonstandard Analysis) whichBerkeley's Robert M. Anderson claims can be very useful in the future. In his manuscript on Nonstandard Analysis, Anderson writes "a very large number of papers could be significantly simplified using nonstandard arguments."

The applications make this the only book of its kind that I have seen. Efe Ok's text on Real Analysis assumes a stronger background than this text, and doesn't include such an eclectic collection of applications. Ok's text is more suitable for someone who wants to work in pure theory.

I would have liked to have seen additional material on general topological spaces covered earlier in the text so for example their discussion of open sets in Euclidean space can be seen as a special type of topological space.

I would strongly recommend this book to anyone who wants to see how mathematical analysis can be applied to economics.

easy to read; good exercise questions
I'm currently a economics graduate student. I was in Max's class when he used the manuscript of this textbook as the course material. This book definitely covers what an economics student will need during the infancy of research. I especially like the questions in the book. They help a lot in understanding. I highly recommend this book to any economics graduate student. ... Read more

Product Description
A comprehensive guide to financial econometrics

Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed.

Svetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale University’s School of Management. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm The Intertek Group. Teo Jasic, PhD, (Frankfurt, Germany) is a senior manager with a leading international management consultancy firm in Frankfurt. ... Read more

Product Description
This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic. ... Read more

Customer Reviews (3)

This was the econometrics bible but they never updated it
Judge, et al. was the standard reference in econometrics in the late 80s and early 90s.It's a terrific text because it has both theory and applications (with emphasis on the former, though).The best thing about it at the time of its publication was it was very complete, covering almost everything that was known in econometrics at the time.

Unfortunately, the book was never updated, and now nobody uses it; instead, people use the poorly written one by William Greene, which contributes to the poor education in grad-level econometrics these days.(Have you noticed that today's econometrics students, even the Ph.D. ones and even some assistant professors, don't even understand the relationship between R-squared and t-statistic?I get asked "why am I getting super-high t-statistics while my R^2 is so low?" all the time.If they had read Judge et al., they would have known the answer.)

Even though I loved this book in teh early 90s, I cannot recommend it as a reference book because it is pretty much out of date.Sure, most of the basic stuff (OLS, 2SLS, limited dependent, etc.) is the same, but people who buy a thick book like this want an up-to-date volume, and this book unfortunately does not fit the bill.It's so sad that such a comprehensive and well-written volume has totally languished into obscurity.

Precise and concise
Another review stated that Green was a clearer book than Judge et al.No way.This book starts and concludes thoughts without the constant refer to section blah blah blah found in Green.Also Judge et al. is accurate; something sorely missing in Green.Hamilton on the other hand focuses strictly on time series, and forecasting.If you want a solid reference for econometrics this is the most complete and well thought out book available.

outdated
I don't want to say too much about this book.I use it a lot.But I think what is in this book has been said so much more clearly elsewhere.I would rather attack econometrics using Greene's clarity or if I were interested in time-series, I would much rather have Hamilton.It is okay.It was a warhorse for its time.But unless you need it for a class, I think there are better references out there. ... Read more

Product Description
This is the fourth volume of the Handbook of Econometrics. The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics. Comprehensive surveys, written by experts, discuss recent developments at a level suitable for professional use by economists, econometricians, statisticians, and in advanced graduate econometrics courses. ... Read more