Contaminacion Del Agua

Gujarati: Basic Econometrics, Fourth Edition

Front Matter

Preface

© The McGraw−Hill Companies, 2004

PREFACE

BACKGROUND AND PURPOSE

As in the previous three editions, the primary objective of the fourth edition of Basic Econometrics is to provide an elementary but comprehensive introduction to econometrics without resorting to matrix algebra, calculus, or statistics beyond theelementary level. In this edition I have attempted to incorporate some of the developments in the theory and practice of econometrics that have taken place since the publication of the third edition in 1995. With the availability of sophisticated and user-friendly statistical packages, such as Eviews, Limdep, Microfit, Minitab, PcGive, SAS, Shazam, and Stata, it is now possible to discuss severaleconometric techniques that could not be included in the previous editions of the book. I have taken full advantage of these statistical packages in illustrating several examples and exercises in this edition. I was pleasantly surprised to find that my book is used not only by economics and business students but also by students and researchers in several other disciplines, such as politics,international relations, agriculture, and health sciences. Students in these disciplines will find the expanded discussion of several topics very useful.
THE FOURTH EDITION

The major changes in this edition are as follows: 1. In the introductory chapter, after discussing the steps involved in traditional econometric methodology, I discuss the very important question of how one chooses among competingeconometric models. 2. In Chapter 1, I discuss very briefly the measurement scale of economic variables. It is important to know whether the variables are ratio
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Gujarati: Basic Econometrics, Fourth Edition

Front Matter

Preface

© The McGraw−Hill Companies, 2004

xxvi

PREFACE

scale, interval scale, ordinal scale, or nominal scale, for that will determine the econometrictechnique that is appropriate in a given situation. 3. The appendices to Chapter 3 now include the large-sample properties of OLS estimators, particularly the property of consistency. 4. The appendix to Chapter 5 now brings into one place the properties and interrelationships among the four important probability distributions that are heavily used in this book, namely, the normal, t, chi square, and F.5. Chapter 6, on functional forms of regression models, now includes a discussion of regression on standardized variables. 6. To make the book more accessible to the nonspecialist, I have moved the discussion of the matrix approach to linear regression from old Chapter 9 to Appendix C. Appendix C is slightly expanded to include some advanced material for the benefit of the more mathematicallyinclined students. The new Chapter 9 now discusses dummy variable regression models. 7. Chapter 10, on multicollinearity, includes an extended discussion of the famous Longley data, which shed considerable light on the nature and scope of multicollinearity. 8. Chapter 11, on heteroscedasticity, now includes in the appendix an intuitive discussion of White’s robust standard errors. 9. Chapter 12, onautocorrelation, now includes a discussion of the Newey–West method of correcting the OLS standard errors to take into account likely autocorrelation in the error term. The corrected standard errors are known as HAC standard errors. This chapter also discusses briefly the topic of forecasting with autocorrelated error terms. 10. Chapter 13, on econometric modeling, replaces old Chapters 13 and 14.This chapter has several new topics that the applied researcher will find particularly useful. They include a compact discussion of model selection criteria, such as the Akaike information criterion, the Schwarz information criterion, Mallows’s Cp criterion, and forecast chi square. The chapter also discusses topics such as outliers, leverage, influence, recursive least squares, and Chow’s prediction...