Book Description

Complex behavior can occur in any system made up of large numbers of interacting constituents, be they atoms in a solid, cells in a living organism, or consumers in a national economy. Analysis of this behavior often involves making important assumptions and approximations, the exact nature of which vary from subject to subject. Foundations of Complex-system Theoriesbegins with a description of the general features of complexity and then examines a range of important concepts, such as theories of composite systems, collective phenomena, emergent properties, and stochastic processes. Each topic is discussed with reference to the fields of statistical physics, evolutionary biology, and economics, thereby highlighting recurrent themes in the study of complex systems. This detailed yet nontechnical book will appeal to anyone who wants to know more about complex systems and their behavior. It will also be of great interest to specialists studying complexity in the physical, biological, and social sciences. ... Read more

Reviews (2)

a fascinating book -- recommended to philosophers
Philosophers of science need to read this book: the hands-on
account of how three sciences work is a healthy
corrective to the usual practice of writing philosophy of science
without actually knowing how the science is done.

A Professional work
This is an amazing work. Sunny Auyang has written an easily comprehenedible book on applications of complexity theories to economics, biology and physics. It is a professional writing to professionals in different fields.One needs college level maths and some physics to fully grasp it but she has made minimum use of mathematical symbols. Her writing flows, the examples are clear, some illuminate important issues in the applied fields, some are just homey bits that convey an idea insightfully. A lot of depth in her philosophical explorations of the complexity ideas. I consider this to be a must for any person studying or instructing in system thinking. ... Read more

Book Description

The theory of empirical processes provides valuable tools for the development of asymptotic theory in (nonparametric) statistical models, and makes it possible to give a unified treatment of various models. This book reveals the relation between the asymptotic behavior of M-estimators and the complexity of parameter space, using entropy as a measure of complexity, presenting tools and methods to analyze nonparametric, and in some cases, semiparametric methods. Graduate students and professionals in statistics, as well as those interested in applications, e.g. to econometrics, medical statistics, etc., will welcome this treatment. ... Read more

Book Description

A vast theoretical and empirical literature in corporate finance considers the interrelationships of corporate governance, takeovers, management turnover, corporate performance, corporate capital structure, and corporate ownership structure. Most of the studies look at two variables at a time. In this book Sanjai Bhagat and Richard Jefferis argue that from an econometric viewpoint, the proper way to study the relationship between any two of these variables is to set up a system of simultaneous equations that specifies the relationships among the six variables. The specification and estimation of such a system of simultaneous equations, however, is nontrivial.

The authors illustrate their argument with a discussion of the impact of corporate anti-takeover measures on takeovers and managerial job-tenure. During the past two decades, an overwhelming majority of publicly held U.S. corporations have adopted anti-takeover measures. The authors show that, contrary to expectation, defense measures are ineffective in preventing takeovers and the frequency of CEO departures is unrelated to takeover defenses. At firms with poison pill defenses, however, there is a statistically significant relationship between management turnover and company performance. ... Read more

Book Description

Analysis of Economic Data teaches methods of data analysis to students whose primary interest is not in econometrics, statistics or mathematics. It shows students how to apply econometric techniques in the context of real-world empirical problems. Key features include:

• Adopts a largely non-mathematical approach relying on verbal and graphical intuition
• Covers most of the tools and models used in modern econometrics research e.g. correlation, regression and extensions for time-series methods
• Contains extensive use of real data examples and involves readers in hands-on computer work
• A disk is packaged with the book containing all data sets included in the text

Reviews (1)

What a relief? Remarkable simplification of econometrics.
I believe, econometrics has evolved into an immensely useful theory though an equally complicated one. Prior grasp on knowledge of statistics and mathematics in general is critical. If you have tried it before, you may agree that drawing accurate inferences out of substantial economic data using statistical models could be a towering task in itself. Imagine yourself [if you are not one of those expert PhD's in economics or statistics] wanting to know why some economic indicaors behave the way they do. well! pick some books on econometrics and read. I will be surprized if you did not have to refer to some other text book to understand at least some of the topics in the book you chose to read. Gary Koop has written a remarkably simple book on the subject. You will not have to read any other text book to understand what Gary wrote. In fact, you will understand econometric models much better and then hopefully understand the meaning behind relationship of economic indicators. You will start thinking like an expert. What more joy is there for an eager and ordinary reader to chose and read a book on econometrics and actually understand it well? Try to find your lost needle in a heystack and remember the happiness you got when you found it. That is what I got from Gary's extraordinary book. Thank you Gary Koop. ... Read more

Book Description

Concisely written and up-to-date, this book provides a unified and comprehensive analysis of the full range of topics that comprise modern time series econometrics. While it does demand a good quantitative grounding, it does not require a high mathematical rigor or a deep knowledge of economics. One of the book's most attractive features is the close attention it pays throughout to economic models and phenomena. The authors provide a sound analysis of the statistical origins of topics such as seasonal adjustment, causality, exogeneity, cointegration, prediction, and forecasting. Their treatment of Box-Jenkins models and the Kalman filter represents a synthesis of the most recent theoretical and applied work in these areas. ... Read more

Reviews (4)

Some topics in time series
the book's goal are nested test, ARIMA models, and the book developos the clasical basic theory of seasonality and Kalman Filter but the book needs Intermediate mathematics and advanced statistics, the book is good as reference in topics of econometrics but if you needs learn time series the Hamilton's book is a good idea.

Don't Buy It
This is a crap book. Don't buy it. I have 3 books by this author, all published by CUP, and I swear I will never and ever buy his fourth book. This is the worst book I've every read. There are several common weak points of his books -- confusing symbols, lack of explanations on those necessary issues and lengthy B.S. on those simple issues. Numerous typing errors make the matter worse. This book spend a chapter talking about old fashion of moving averages, such as Spencer 7-point and 15-point. It almost goes into the field of graduation. What's the point? The chapters on ARIMA are also rubbish. My feeling is that the author lacks sense in statistics, all he saw are just mathematics. On the whole, this book is just on the wrong field, at the wrong time and with the wrong title.

Not a book for economists; particularly hard to understand
When you study an econometrics PhD. In France, you can't avoid reading books of Gourieroux: it's the national hero of econometrics. In fact, when you discover all the research he has done, you have to admit it's a brilliant person. But his books aren't particularly clear. They are made for mathematicians (the only students in my classroom that appreciate this book aren't economists; the rest of us, simple mortals, use more friendly books, such as Davidson and Mackinnon, Greene, Enders and Hamilton). What can I say? It's a very complete book: seasonality is deeply treated, ARIMA models are studied profoundly and, you can even find a spectral analysis chapter and another of the Kalman filter. But they are pretty hard to understand. The notation is complex, more than necessary. There are lots of equations and little explanations. If you are a mathematician, this book will satisfy your needs; it's rigorous and fairly complete (even if the selection of topics it's not the ideal one, I think); if you are not, you should better go to Hamilton's manual. If what you want is a cookbook of time series, then buy Enders.

excellent reference book
This book is a graduate level introduction to time series econometrics. By introduction I mean that it covers a large amount of material, from stationary ARMA models to cointegration, without going too deep into details, although it requires strong mathematical and statistical background. The aim of this book was to be a source of references for applied researches and a textbook for graduate level courses. So in this respect it's similar to Hamilton's "Time Series Analysis". I think that as a textbook Hamilton's book works better, because the derivation of many results in it is more detailed. On the other hand, Gourieroux and Monfort treatment of many topics is more advanced. Gourieroux and Monfort provide much more information, for example, on uses of frequency domain. They also included a chapter on fractional processes. ... Read more

Book Description

Written by two top statisticians with experience in teaching matrix methods for applications in statistics, econometrics and related areas, this book provides a comprehensive treatment of the latest techniques in matrix algebra. A well-balanced approach to discussing the mathematical theory and applications to problems in other areas is an attractive feature of the book. It can be used as a textbook in courses on matrix algebra for statisticians, econometricians and mathematicians as well. Some of the new developments of linear models are given in some detail using results of matrix algebra. ... Read more

Book Description

The objective of this book is to present this analytical framework and to illustrate how it can be used in the investigation of economic decisions under risk. In a sense, the economics of risk is a difficult subject: it involves understanding human decisions in the absence of perfect information. How do we make decisions when we do not know some of events affecting us? The complexities of our uncertain world and of how humans obtain and process information make this difficult. In spite of these difficulties, much progress has been made. First, probability theory is the corner stone of risk assessment. This allows us to measure risk in a fashion that can be communicated among decision makers or researchers. Second, risk preferences are now better understood. This provides useful insights into the economic rationality of decision making under uncertainty. Third, over the last decades, good insights have been developed about the value of information. This helps better understand the role of information in human decision making and this book provides a systematic treatment of these issues in the context of both private and public decisions under uncertainty.

* Balanced treatment of conceptual models and applied analysis
* Considers both private and public decisions under uncertainty
* Website presents application exercises in EXCEL ... Read more

Book Description

Reviews (1)

Excellent for Non-Quant Geek Economics Students
This book is a gentle introduction to the math used in microeconomics at advanced undergrad or graduate levels. The book assumes nothing or at least very little in the way of math preparation. The authors could point out more pitfalls, but these two mathematics professors write beautifully and simply about what is, for some of us, a complicated topic. They start with things as simple as Cartesian graphs and they move on through calculus, differential equations and various forms of linear and matrix algebra. The econ examples are excellent and concise, but are basic and not of theoretical interest. No one is going to learn Cournot monopoly theory or auction theory here, but you will learn how to read a book like Wolfstetter's Topics in Microeconomics without wishing you could throttle the excessively brief and cryptic author of that interesting text. One wishes in general that economists could write like the authors of this book, but they can't. Nowhere have I seen such obtuse notation and heartless math presentation as in microeconomic theory. But econ is micro, and even if a lot of microeconomists can't teach, write, or present math, they are the roadblock to understanding much of finance, applied game theory, and matters of technical management and public policy. This book covers continuous and static analysis tools, not probability or statistics in any detail. It is truly innovative among the books I have seen in treating mathematical economics. Micro theory is the flunk-out course for econ majors. This book could get most through. A patient non-quantitative person can learn it right out of the book without lectures or high anxiety. I suspect the seriously macho econ folks will hide the fact that they own it, but they would probably benefit too at least from topics where they stumble a bit or feel a slight discomfort. It would also be a worthwhile text for Ph.D. candidates who want to prepare for comprehensive exams either oral or written, or for people like economic sociologists who vaguely wish to be taken seriously. ... Read more

Book Description

This volume in the series Advanced Texts in Econometrics explains recent theoretical developments in the econometric modelling of relationships between different statistical series. Clive Granger and Timo Terasvirta illustrate ways of using dynamic, multivariate analysis techniques to provide models of nonlinear relationships between variables. They pay particular attention to the case of a single dependent variable modelled by a few explanatory variables and the lagged dependent variable in nonlinear form. They also discuss the division of nonlinear relationships into parametric and nonparametric models. The developments detailed in this book will be useful to econometricians who need to construct or use models of nonlinear, dynamic, multivariate relationships, such as an investment or production function. ... Read more

Reviews (2)

A must-have for any researcher and econometrics student
This book is highly influential. Many works on nonlinear modelling have cited this book. Written by one of the Noble econometricians, this book is surprisingly not hard to follow.
The explanations are clear and concise. Theories, modelling strategies, and empirical applications are covered in detailed. If you are a researcher or student wanted to learn state-of-the-art techniques in nonlinear modelling, this book is a good start.

More nonlinear than modelling
A good book by Clive Granger and Timo Teräsvirta, whose attention on nonlinearities in econometrics has been producing several interesting results especially as far as economic modelling is concerned. This text mainly deals with nonlinear time series and helps the reader understand the basic results of nonlinear stochastic equations. Several common nonlinear models are presented and dealt with, and an extention of the linear concept of integration is provided. The main problems in this book are the lack of a full dynamical system approach that makes some results rather difficult to be understood for the reader and therefore the loss of generality in the explanation of the concepts. It's anyway a good book that studies in a deep way bilinear and smooth transition autoregressive models from a theoretical point of view. I also found it extremely clear, which is a common characteristic of Granger's texts, and I would recommend it to all the econometricians who already have a good knowledge of nonlinear deterministic systems and want to understand stochastic nonlinear models better. ... Read more

Book Description

Introduction to Econometrics,2/e offers a step-by-step introductory guide to the core areas of econometrics. Accessible to readers with limited mathematical backgrounds, the book provides an analytical and an intuitive understanding of the classical linear regression model. 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 cointegration. ... Read more

Reviews (3)

One of a kind!!!!
My Amazon.co.uk review:

Whether or not you are an undergraduate at the LSE taking the introductory course on Econometrics (the author of the book is the lecturer of that course at the LSE), this book will be of interest to you if you'd like an introduction to Econometrics. It takes you from a very basic understanding of statistics right through to how to deal with non-stationary time series. In between it covers topics such as simple and multiple regression, problems with multicollinearity and misspecifications (e.g. omitted variable bias), heteroscedasticity, proxy variables and instrumental variables, simultaenous equation bias and time series. The book also gives you a basic understanding of how to use logit and probit analysis when fitting binary choice models. After having read the book you should be able to understand violations of Gauss-Markov conditions and know how to deal with them.
Dougherty has succeeded to make this book easy to understand for any undergraduate seeking knowledge in this topic. I find the detailed worked examples especially helpful for when it comes to solving practical problems for which the book mainly considers the use of Stata and EView. The book also has a lot of exercises that help enhance the student's understanding of the topics. Additionally, Dougherty has compiled a course guide that among other things also goes through some of the exercises in the book. The course guide can be found on his webpage at the LSE in addition to all slide shows corresponding to the chapters of the book. Together with these additional course materials, the book makes the topics very easy to understand and cope with for students and should help them do well in their courses on Econometrics. This is really one of a kind and an extremely useful basis for further studies in 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 real understanding of the subject. ... Read more

Book Description

This book presents statistical methods for analysis of the duration of events.The primary focus is on models for single-spell data, events in which individual agents are observed for a single duration.Some attention is also given to multiple-spell data.The first part of the book covers model specification, including both structural and reduced form models and models with and without neglected heterogeneity.The book next deals with likelihood based inference about such models, with sections on full and semiparametric specification.A final section treats graphical and numerical methods of specification testing.This is the first published exposition of current econometric methods for the study of duration data. ... Read more

Reviews (1)

The Econometric Analysis of Transition Data
I want to make a tesis of duration models and this book is the appropriated ... Read more

Book Description

In this edition which has been reprinted with corrections, Nerlove and his co-authors illustrate techniques of spectral analysis and methods based on parametric models in the analysis of economic time series. The book provides a means and a method for incorporating economic intuition and theory in the formulation of time-series models useful in forecasting, in the formulation and estimation of distributed lag models, and in other applications, such as seasonal adjustment. Analysis of Economic Time Series is a useful primary text for graduate students and an attractive reference for researchers.

Key Features
* Presents a self-contained treatment of Fourier Analysis and complex variables, as well as Spectral Analysis of time series
* Includes a detailed treatment of unobserved-components (UC) models and their time-series properties by means of covariance-generating transforms
* Provides the formulation and maximum-likelihood estimation of ARMA and UC models in both time and frequency domains
Integrates several topics in time-series analysis:
* The formulation and estimation of distributed-lag models of dynamic economic behavior
* The application of the techniques of spectral analysis in the study of behavior of economic time series
* Unobserved-components models for economic time series and the closely related problem of seasonal adjustment
* The complimentarities between time-domain and frequency-domain approaches to the analysis of economic time series
* Historical contributions extending from the time of Charles Babbage and the Edinburgh Review to the present
* Treats spectral analysis and Box-Jenkins models for an intuitive but rigorous point of view
* Shows how these two types of analysis may be synthesized so that they complement one another
* Describes a new type of model, based on a superposition of Box-Jenkins models, that captures the essential idea of the unobserved-components models long used in the analysis of economic time series
* Applies multiple time-series techniques to the estimation of a novel dynamic model of the US cattle industry ... Read more

Reviews (2)

Great Introduction...
Here is a practical comment for the typical economics graduate student: Buy this book if you want to start using Mathematica!

What does a typical economics graduate student need? First, s/he needs to review her/his knowledge of mathematics. Second, s/he needs to learn how to use the tool (math) to solve an economic problem. Cliff J. Huang and Philip S. Crooke's book is helpful in both respects. While they are introducing the basic language of Mathematica they review most of the undergraduate math. And they teach with a hands-on approach--that is, you solve almost every problem using Mathematica.

Mathematica is a great tool for economics graduate students, it helps you out in understanding the basic intuitions behind mathematical concepts--because you do not have to solve complex problems (Mathematica solves them for you), you just have to understand them. Of course, students are advised to consult their professors to choose the right computer software or programming language. Mathematica can do a lot, but some other software might be much more practical for your PhD thesis project...

[Also consider Differential Equations: An Introduction with Mathematica by Clay C. Ross]

Exceptionally valuable contribution to graduate economics
This book covers mathematical methods topics that would ordinarily constitute the core of a one semester course at the first year graduate level in economics. The book could also be used at the advanced undergraduate level. It is the first book to fully integrate Wolfram Research's Mathematica software into a study of mathematical methods for economists. The authors' stated objective in this integration is to relieve students, via use of computer software, of the rather tedious computations typically associated with mathematics for economists coursework so that attention can be focused on underlying principles. To further this objective, a Mathematica notebook, MathEcon, comprised of functions commonly implemented in mathematics for economists courses accompanies the book.

The book features fifteen chapters including coverage of topics in linear algebra, quadratic forms, vector calculus, functional properties, mathematical programming, and differential and difference equations. The first two chapters provide an introduction to Mathematica and a review of calculus. Chapters are divided into sections and subsections and all chapters include exercises at the conclusion of each subsection. Many, though not all, of the exercises involve use of the Mathematica software. Numerous examples are included in all chapters and the use of Mathematica to illustrate concepts and problem solving is prevalent throughout the book. In this regard, the numeric, symbolic, and, in particular, graphic capabilites of Mathematica are used extensively to explain concepts and example problem solutions.

This book can only be regarded as an exceptionally valuable contribution to graduate education in economics. The choice and coverage of topics is appropriate for the mathematics for economists course. Mathematical concepts are presented with uncommon clarity. For example, the chapter on eigensystems is perhaps the best treatment of this topic in the mathematics for economists literature. The many examples contained in the book provide for enhanced comprehension of related concepts and would by themselves elevate this book above the field as an educational device. Exercises are generally well suited for reinforcement of material covered in the chapter subsections. The thoughtful integration of related computer capabilities and provision of the MathEcon package fully achieve the authors' stated objective. This book is an obvious first choice as a textbook in mathematics for economists courses. ... Read more

Book 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

Reviews (4)

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 tells you what he's doing and why the content of each chapter matters and how it is related to what has come before and to what will come afterwards.

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

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

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

Econometrics finally makes sense!
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 some subjects other authors assume (in my experience, incorrectly) the student knows. Finally, the geometric approach Ruud frequently espouses is somewhat unique in econometric presentation, and one I find quite useful. ... Read more

Book Description

This book is an ideal introduction for beginning students of econometrics that assumes only basic familiarity with matrix algebra and calculus. It features practical questions which can be answered using econometric methods and models. Focusing on a limited number of the most basic and widely used methods, the book reviews the basics of econometrics before concluding with a number of recent empirical case studies. The volume is an intuitive illustration of what econometricians do when faced with practical questions. ... Read more

Reviews (3)

Of little value
I used to know a bit of econometrics and hoped this would jog my memory and give some practical pointers. I found it almost useless for my purposes. It reads almost like a really detailed glossary of terms.

An unique gem of a book
I'm really surprised that there haven't been more knowledgable reviews of this book before now. I'm also surprised that there isn't a lot of buzz out there about *A Concise Introduction to Econometrics.* This is an unique gem of a book for anyone who is interested in econometrics but does not have a PhD in economics.

What is this book about? This is one of the few books that lives up to its title.

It is concise (the heart of the book is about 100 pages) and is reminiscent of Oxford UP's 'A Very Short Introduction' series.

It deals with econometrics - the statistical analysis of economic data. The book provides a brief but informative remedial section on basic statistics necessary to understand the heart of the book, regression analysis (both cross-sectional and time-series). The book dissects some case studies -- examples from actual, real-life econometric studies (as opposed to made up 'toy' examples used in much more dense books) -- with a special emphasis on topics relevant to finance (financial econometrics) and marketing.

Finally, it lives up to its byline "An Intuitive Guide." It really does deliver a (relatively) intuitive guide to a highly mathematical subject. Even though the book recommends familiarity with calculus and linear algebra, it can easily be read and understood by an intelligent person with a more limited mathematical background (high-school algebra is probably all you need, but you do need mathematical 'maturity' and patience). The emphasis is on understanding the underlying reasoning and not on calculation or formal proofs. It even deals with advanced topics like ARCH/GARCH in this relatively intuitive way.

Who is this book for? I think that the audience for this book are beginning students of econometrics or regression analysis outside of economics. This would obviously include undergrads in economics, finance, etc. and non-quant MBA students. But what many people don't realize is the extent to which econometrics has gained in importance in seemingly unrelated fields. Many law schools, lawyers, and legal scholars make use of econometrics and they could benefit from a book like this. Those people in public policy (academics or in practice), public health, and non-econ social sciences could also benefit from this book. The book is written on a level that intelligent law and policy students should be able to get a lot of knowledge about a topic they would normally be intimidated by.

Another audience for this book are people who have to deal with econometrics on a PRACTICAL level. One of the things that many people who studied econometrics in school find when they have to use it in the real world (on-the-job) is that the formal academic training both OVER-prepared them and UNDER-prepared them for the real world uses of econometrics in finance and marketing (the two areas of emphasis in this book). At least in non-academic settings (and in research assistant work in academe), you don't really need to formally derive a proof or have memorized the content of Greene's econometrics textbook. In fact, a lot of the gibberish one learns in a formal setting will confuse you and often times not clarify how you would model a situation you confront and what kind of data (and how to get it) you need to properly answer the problems you're tackling.

Philip Hans Franses, the author of this book, actually relays to the readers that he is very cogniscent of these types of issues. In fact that was his main motivation for writing this book. He comes from a marketing and financial econometrics background so he is very familiar with on-the-job issues relevant to making practical use of econometrics.

I contrast all of the above with a book like Peter Kennedy's famous guide to econometrics. I don't want to knock or disparage that book, because (for what it is intended to do) it does a great job. But Kennedy's book is designed as a way for economics students (especially graduate and advanced undergrad) and PhD economists to have a reference and general overview of a variety of topics in academic econometrics. That isn't to say that it is not useful -- it would be especially useful for financial engineers dealing with advanced issues in financial econometrics. But, in spite of its strengths for those taking formal econometrics courses or in need of a academically oriented refresher or intro, it does not do what Franses' book does: A practically oriented and brief light-on-the-math introduction to econometrics especially useful for legal and policy scholars and for econonomics, finance, MBA, etc. students that find even Kennedy's book to be over their heads.

I don't know of any other book of its kind out there in the marketplace. If you're even vaguely intrigued, I suggest you buy this relatively inexpensive book. Frankly, it's a lot better than books ten times its price and size.

Learn the basics of econometrics
This book is about the wierd subject of econometrics. Econometrics iis a subject that uses math, economics, and statistics. They take an economic question and use data that some what relates to that to try to predict what is going to happen. If this interests you you might like this book. I have never read anything about econometrics before and this book helped to explain it. Sometimes the book would get really complicated and get really hard to follow. The key points in the book are in italics and the practical questions are in bold. These are really helpful. If you read this book make sure you understand how to read functions and how to work with them. You will also have to be able to follow multi-variable equations. You also need a basic understanding of integrals and what they do. If you can understand all of this math and are interested in learning about math in economics you might like this book. The final chapter was helpful becuase it looks at actual questions that have been answered with econometrics. This should it in action. Overall I think this book was informative, but really confusing. ... Read more

Book Description