A Guide to Econometrics has established itself as a preferred text for teachers and students throughout the world. It provides an overview of the subject and an intuitive feel for its concepts and techniques without the notation and technical detail that characterize most econometrics textbooks. The fifth edition has two major additions, a chapter on panel data and an innovative chapter on applied econometrics. Existing chapters have been revised and updated extensively, particularly the specification chapter (to coordinate with the applied econometrics chapter), the qualitative dependent variables chapter (to better explain the difference between multinomial and conditional logit), the limited dependent variables chapter (to provide a better interpretation of Tobit estimation), and the time series chapter (to incorporate the vector autoregression discussion from the simultaneous equations chapter and to explain more fully estimation of vector error correction models). Several new exercises have been added, some of which form new sections on bootstrapping and on applied econometrics. This edition is for sale in all of the Americas, the West Indies, and U.S. dependencies only.
One of the best, and easy to use summary in statistics to check assumptions and ensure correct analysis. Statistics are more abused than used, which renders this book a superior reference against common-day abuses.
A very good treatment of what Econometrics is, in plain English. Use a good undergrad book, this and book like Goldberger to supplement your undoubtedly unreadable PhD level textbook.
A book such as this serves no purpose in this day and age when one can easily get terse summaries of different statistical and econometric techniques from Wikipedia. This book has an awful lot of words but very few examples of how to apply many of techniques in practice, so often it doesn't really help when you have a confusion that you're trying to clear up. If William Greene's Econometric Analysis is too mathematical, at least it has good examples of how to apply that math and sometimes the math can yield good intuition.
This book certainly doesn't claim to be the most rigorous text and so I don't judge it as such, but it also provide very little value if what you seek is intuition. Better to skip it and find another book.
Gotta say, for a subject that I really struggle with, this was a great read. The author does a good job explaining things conceptually. This will be something I buy and keep for a reference!