OBJECTIVE OF THE BOOK

As in the previous editions, the primary objective of the fourth edition of Essentials of Econometrics is to provide a user-friendly introduction to econometric theory and techniques. The intended audience is undergraduate economics majors, undergraduate business administration majors, MBA students, and others in social and behavioral sciences where econometrics techniques, especially the techniques of linear regression analysis, are used. The book is designed to help students understand econometric techniques through extensive examples, careful explanations, and a wide variety of problem material. In each of the editions, I have tried to incorporate major developments in the field in an intuitive and informative way without resort to matrix algebra, calculus, or statistics beyond the introductory level. The fourth edition continues that tradition.

Although I am in the eighth decade of my life, I have not lost my love for econometrics and I strive to keep up with the major developments in the field. To assist me in this endeavor, I am now happy to have Dr. Dawn Porter, Assistant Professor of Statistics, at the Marshall School of Business at the University of Southern California in Los Angeles, as my co-author. Both of us have been deeply involved in bringing the fourth edition of Essentials of Econometrics to fruition.

MAJOR FEATURES OF THE FOURTH EDITION

Before discussing the specific changes in the various chapters, the following features of the new edition are worth noting:

1. In order to streamline topics and jump right into information about linear regression techniques, we have moved the background statistics material from the second through fifth chapters into the appendix. This allows for easy reference to more introductory material for those who need it without disturbing the main content of the text.
2. Practically all the data used in the illustrative examples in the previous edition have been updated.
3. 3. Several new examples have been added.
4. In several chapters, we have included extended concluding examples that illustrate the various points made in the text.
5. Concrete computer printouts of several examples are included in the book. Most of these results are based on EVIEWS (version 6) and STATA (version 10), and MINITAB (version 15).
6. Several new diagrams and graphs are included in various chapters.
7. Several new data-based exercises are included in the various chapters.
8. Small-sized data are included in the book, but large sample data are posted on the book's web site, thereby minimizing the size of the text. The web site will also publish all the data used in the book.

SPECIFIC CHANGES

Some of chapter-specific changes are as follows:

Chapter 1: A revised and expanded list of websites for economic data has been included.

Chapters 2 and 3: An interesting new data example concerning the relationship between family income and student performance on the S.A.T. is utilized to introduce the two-variable regression model.

Chapter 4: We have included a brief explanation of nonstochastic versus stochastic predictors. An additional example is included regarding educational expenditures among several countries adds to the explanation of regression hypothesis testing.

Chapter 5: The Math S.A.T. example is revisited to illustrate various functional forms. Section 5.10 has been added to handle the topic of regression on standardized variables. Also, several new data exercises have been included.

Chapter 6: An added example concerning acceptance rates among top business schools is included help to illustrate the usefulness of dummy variable regression models. Several new data exercises are also added.

Chapter 8: Again, we have added several new, updated data exercises dealing with the issue of multicollinearity.

Chapter 9: To illustrate the concept of heteroscedasticity, a new example relating wages to education levels and years of experience has been included, as well as more real data exercises.

Chapter 10: It now has a new section concerning the Newey-West standard error correction method using a data example. An additional new appendix has also been included at the end of the chapter to cover the Breusch-Godfrey test of autocorrelation.

Chapter 12: An expanded treatment of logistic regression is included in this chapter with new examples to illustrate results.

Besides these specific changes, errors and misprints in the previous editions have been corrected. Also, discussion of several topics in the various chapters has been streamlined.

Appendices A–D: As noted above, these appendices were formerly contained in chapters 2–5 of the main text. By placing them in the back, they can more easily serve as reference sections to the main text. Data examples have been updated and new exercises have been added.

MATHEMATICAL REQUIREMENTS

In presenting the various topics, we have used very little matrix algebra or calculus. We firmly believe that econometrics can be taught to the beginner in an intuitive manner, without a heavy does of matrix algebra or calculus. Also, we have not given any proofs unless they are easily understood. We do not feel that the nonspecialist needs to be burdened with detailed proofs. Of course, the instructor can supply the necessary proofs as the situation demands. Some of the proofs are available in our Basic Econometrics (McGraw-Hill, 5th ed., 2009).

SUPPLEMENTS AID THE PROBLEM SOLVING APPROACH

The comprehensive website contains the following supplementary material to assist both instructors and students:
-Data from the text, as well as additional large set data referenced in the book
-A Solutions Manual providing answers to all of the questions and problems throughout the text
-A digital image library containing all of the graphs and tables from the book

For more information, please visit the Online Learning Center at www.mhhe.com/GujaratiEss4e.

COMPUTERS AND ECONOMETRICS

It cannot be overemphasized that what has made econometrics accessible to the beginner is the availability of several user-friendly computer statistical packages. The illustrative problems in this book are solved using statistical software packages, such as Eviews, Excel, MINITAB, and STATA. Student versions of some of these packages are readily available. The data posted on the website is in Excel format and can also be read easily by many standard statistical packages such as LIMDEP, RATS, SAS, and SPSS.

In Appendix E we show the outputs of EViews, Excel, MINITAB, and STATA, using a common dataset. Each of these software packages has some unique features although some of the statistical routines are quite similar.

IN CLOSING

To sum up, in writing Essentials of Econometrics, our primary objective has been to introduce the wonderful world of econometrics to the beginner in a relaxed but informative style. We hope the knowledge gained from this book will prove to be of lasting value in the reader's future academic or professional career and that the reader's knowledge learned in this book can be further widened by reading some advanced and specialized books in econometrics. Some of these books can be found in the selected bibliography given at the end of the book.

ACKNOWLEDGEMENTS

Our foremost thanks are to the following reviewers who made very valuable suggestions to improve the quality of the book.

We are very grateful to Douglas Reiner, our editor at McGraw-Hill, for helping us through this edition of the book. We are also grateful to Noelle Fox, editorial coordinator at McGraw-Hill, for working with us through all of our setbacks. We also need to acknowledge the great copy editing by Manjot Singh Dodi, especially since this type of textbook incorporates so many technical formulas and symbols.