Product Description

Econometric Analysisi, 6/e serves as a bridge between an introduction to the field of econometrics and the professional literature for  social scientists and other professionals in the field of social sciences, focusing on applied econometrics and theoretical background. This book provides a broad survey of the field of econometrics that allows the reader to move from here to practice in one or more specialized areas. At the same time, the reader will gain an appreciation of the common foundation of all the fields presented and use the tools they employ. This book gives space to a wide range of topics including basic econometrics, Classical, Bayesian, GMM, and Maximum likelihood, and gives special emphasis to new topics such a time series and panels. For social scientists and other professionals in the field who want a thorough introduction to applied econometrics that will prepare them for advanced study and practice in the field.

Product Details

• Amazon Sales Rank: #91230 in Books
• Published on: 2007-08-17
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 1216 pages

From the Publisher
This text introduces students to applied econometrics-including basic techniques in regression analysis and some of the rich variety of models that are used.

From the Back Cover
Key Benefit: This book introduces students to applied econometrics including basic techniques in regression analysis and some of the rich variety of models that are used. Key Topics: Includes self-contained summaries of the matrix algebra, statistical theory, and mathematical statistics used in the book. Covers Estimator, ML, GMM, and 2 step; Panel data, heteroscedasticity, qualitative responsive models, limited dependent variables, and emphasizes nonlinear models. Also discusses current topics in applied econometrics, such as GMM estimation methods, Lagrange multiplier tests, and time series analysis.

Excerpt. © Reprinted by permission. All rights reserved.

THE FIFTH EDITION OF ECONOMETRIC ANALYSIS

Econometric Analysis is intended for a one-year graduate course in econometrics for social scientists. The prerequisites for this course should include calculus, mathematical statistics, and an introduction to econometrics at the level of, say, Gujarati's Basic Econometrics (McGraw-Hill, 1995) or Wooldridge's Introductory Econometrics: A Modern Approach South-Western (2000). Self-contained (for our purposes) summaries of the matrix algebra, mathematical statistics, and statistical theory used later in the book are given in Appendices A through D. Appendix E contains a description of numerical methods that will be useful to practicing econometricians. The formal presentation of econometrics begins with discussion of a fundamental pillar, the linear multiple regression model, in Chapters 2 through 8. Chapters 9 through 15 present familiar extensions of the single linear equation model, including nonlinear regression, panel data models, the generalized regression model, and systems of equations. The linear model is usually not the sole technique used in most of the contemporary literature. In view of this, the (expanding) second half of this book is devoted to topics that will extend the linear regression model in many directions. Chapters 16 through 18 present the techniques and underlying theory of estimation in econometrics, including GMM and maximum likelihood estimation methods and simulation based techniques. We end in the last four chapters, 19 through 22, with discussions of current topics in applied econometrics, including time-series analysis and the analysis of discrete choice and limited dependent variable models.

This book has two objectives. The first is to introduce students to applied econometrics, including basic techniques in regression analysis and some of the rich variety of models that are used when the linear model proves inadequate or inappropriate. The second is to present students with sufficient theoretical background that they will recognize new variants of the models learned about here as merely natural extensions that fit within a common body of principles. Thus, I have spent what might seem to be a large amount of effort explaining the mechanics of GMM estimation, nonlinear least squares, and maximum likelihood estimation and GARCH models. To meet the second objective, this book also contains a fair amount of theoretical material, such as that on maximum likelihood estimation and on asymptotic results for regression models. Modern software has made complicated modeling very easy to do, and an understanding of the underlying theory is important.

I had several purposes in undertaking this revision. As in the past, readers continue to send me interesting ideas for my "next edition." It is impossible to use them all, of course. Because the five volumes of the Handbook of Econometrics and two of the Handbook of Applied Econometrics already run to over 4,000 pages, it is also unnecessary. Nonetheless, this revision is appropriate for several reasons. First, there are new and interesting developments in the field, particularly in the areas of microeconometrics (panel data, models for discrete choice) and, of course, in time series, which continues its rapid development. Second, I have taken the opportunity to continue fine-tuning the text as the experience and shared wisdom of my readers accumulates in my files. For this revision, that adjustment has entailed a substantial rearrangement of the material—the main purpose of that was to allow me to add the new material in a more compact and orderly way than I could have with the table of contents in the 4th edition. The 15terature in econometrics has continued to evolve, and my third objective is to grow with it. This purpose is inherently difficult to accomplish in a textbook. Most of the literature is written by professionals for other professionals, and this textbook is written for students who are in the early stages of their training. But I do hope to provide a bridge to that literature, both theoretical and applied.

This book is a broad survey of the field of econometrics. This field grows continually, and such an effort becomes increasingly difficult. (A partial list of journals devoted at least in part, if not completely, to econometrics now includes the Journal of Applied Econometrics, Journal of Econometrics, Econometric Theory, Econometric Reviews, Journal of Business and Economic Statistics, Empirical Economics, and Econometrica.) Still, my view has always been that the serious student of the field must start somewhere, and one can successfully seek that objective in a single textbook. This text attempts to survey, at an entry level, enough of the fields in econometrics that a student can comfortably move from here to practice or more advanced study in one or more specialized areas. At the same time, I have tried to present the material in sufficient generality that the reader is also able to appreciate the important common foundation of all these fields and to use the tools that they all employ.

There are now quite a few recently published texts in econometrics. Several have gathered in compact, elegant treatises, the increasingly advanced and advancing theoretical background of econometrics. Others, such as this book, focus more attention on applications of econometrics. One feature that distinguishes this work from its predecessors is its greater emphasis on nonlinear models. Davidson and MacKinnon (1993) is a noteworthy, but more advanced, exception. Computer software now in wide use has made estimation of nonlinear models as routine as estimation of linear ones, and the recent literature reflects that progression. My purpose is to provide a textbook treatment that is in fine with current practice. The book concludes with four lengthy chapters on time-series analysis, discrete choice models and limited dependent variable models. These nonlinear models are now the staples of the applied econometrics literature. This book also contains a fair amount of material that will extend beyond many first courses in econometrics, including, perhaps, the aforementioned chapters on limited dependent variables, the section in Chapter 22 on duration models, and some of the discussions of time series and panel data models. Once again, I have included these in the hope of providing a bridge to the professional literature in these areas.

I have had one overriding purpose that has motivated all five editions of this work. For the vast majority of readers of books such as this, whose ambition is to use, not develop econometrics, I believe that it is simply not sufficient to recite the theory of estimation, hypothesis testing and econometric analysis. Understanding the often subtle background theory is extremely important. But, at the end of the day, my purpose in writing this work, and for my continuing efforts to update it in this now fifth edition, is to show readers how to do econometric analysis. I unabashedly accept the unflattering assessment of a correspondent who once likened this book to a "user's guide to econometrics."

SOFTWARE AND DATA

There are many computer programs that are widely used for the computations described in this book. All were written by econometricians or statisticians, and in general, all are regularly updated to incorporate new developments in applied econometrics. A sampling of the most widely used packages and Internet home pages where you can find information about them are:

• E-Views—www.eviews.com (QMS, Irvine, Calif.)
• Gauss—www.aptech.com (Aptech Systems, Kent, Wash.)
• LIMDEP—www.limdep.com (Econometric Software, Plainview, N.Y)
• RATS—www.estima.com (Estima, Evanston, Ill.)
• SAS—www.sas.com (SAS, Cary, N.C.)
• Shazam—shazam.econ.ubc.ca (Ken White, UBC, Vancouver, B.C.)
• Stata—www.stata.com (Stata, College Station, Tex.)
• TSP—www.tspintl.com (TSP International, Stanford, Calif)

Programs vary in size, complexity, cost, the amount of programming required of the user, and so on. Journals such as The American Statistician, The Journal of Applied Econometrics, and The Journal of Economic Surveys regularly publish reviews of individual packages and comparative surveys of packages, usually with reference to particular functionality such as panel data analysis or forecasting.

With only a few exceptions, the computations described in this book can be carried out with any of these packages. We hesitate to link this text to any of them in particular. We have placed for general access a customized version of LIMDEP, which was also written by the author, on the website for this text, www.prenhall.com/greene. LIMDEP programs used for many of the computations are posted on the sites as well.

The data sets used in the examples are also on the website. Throughout the text, these data sets are referred to "TableFn.m," for example Table F4.1. The F refers to Appendix F at the back of the text, which contains descriptions of the data sets. The actual data are posted on the website with the other supplementary materials for the text. (The data sets are also replicated in the system format of most of the commonly used econometrics computer programs, including in addition to LIMDEP, SAS, TSP, SPSS, E-Views,Stata, so that you can easily import them into whatever program you might be using.)

I should also note, there are now thousands of interesting websites containing software, data sets, papers, and commentary on econometrics. It would be hopeless to attempt any kind of a survey here. But, I do note one which is particularly agreeably structured and well targeted for readers of this book, the data archive for the Journal of Applied Econometrics. This journ...

Customer Reviews

A good book for graduate students, useful as reference book
I bought this book in order to understand better my PhD courses. I must admit that after a few tries, I went back to Davidson and Mackinnon manual and to Hamilton's Time Series Bible. It could be seen as an intermediate level book, which is a main problem: undergraduates (except for the advanced ones) won't feel comfortable with the level of the book; applied econometrists will think perhaps that greene's book covers all the main topics but not profoundly enough (In the unit root chapter for example, the demonstration of the unit root test -Dickey-Fuller- is not present). As some of the other reviewers, I agree with the fact that, covering so many topics, the organization of the book could be improved. The mathematical tools explanation is a very clever idea; everybody lacking mathematical knowledge should read the first chapters. Some of my teachers appreciate (and I agree with them, without being an expert of that topic) particularly the panel regression chapter. I think this book fits better the graduate needs, especially those being, or wanting to be applied econometricians. If you are looking for an advanced theoretical manual, Greene's is not the best choice; if you are interested in having a -slightly more than- fairly good understanding of what is done currently in the field, then grab this book. But be aware, if you want to feel comfortably when reading it, you should be familiarized with the field. I recommend Johnston and Dinardo's Manual and Walter Ender's Manual (for time series only). Finally, it must be said that the fourth edition doesn't differ too much from the third one.

About the 4th ed.:
I've just bought the 4th edition. At my first glance it differs not much from the 3rd one, except: [1] a CD-ROM is attached; [2] typos have been corrected; [3] the WHOLE content is blue-printed instead of dark-printed, which I find uncomfortable (not used to) in reading it.

The rest is similar to its 3rd edition -- poor in organization, as I mentioned before. In my professor's and my views, its 2nd edition is much better.

Matrix and Vector BONANZA!
The comments noting Greene's notational prowess are certainly accurate, at least in my experience of the text. If you are hunting for THE book on econometrics, particularly cross-section and panel, then Greene's is the place to turn. One would be hard pressed to find much that Greene doesn't cover, except for advanced Time-Series Econometrics. (If you are looking for an outstanding Time-Series text that is very rigorous, pick up Hamilton's "Time-Series Analysis." But this is not for the faint-hearted. An easier, but much less complete text on Time-Series is Walter Enders' Applied Econometric Time-Series.)

A terrific textbook lineup for a 1st-2nd semester graduate course in econometrics is Greene's Econometric Analysis and Peter Kennedy's Guide to Econometrics.