Introductory Econometrics: A Modern Approach [With Access Code]

Wooldridge's explanations are clear and useful. After a semester hacking my way through the dense brush of matrices in Greene's book, I realized I needed some help. Now I go to Wooldridge's treatment first, to make sure I understand the main concepts. Then I go to Greene for the detail, if I need to.

Wooldridge has managed to write a great and intuitive introduction into econometrics. The book doesn't require any prerequisites despite basic high school math and statistics. Matrix algebra is only used in some of the appendices, which is a bit sad, as the introduction of it in the text, and the usage during the text, would have been a major advantage when reading more advanced books on econometrics. Despite that, the book is really fascinating. Written in a simple yet rather rigorous style, accessible and self-explanatory. The examples aren't always economic, which is a small lack, but in a way Wooldridge does what he is promising to do: He introduces the reader into the methods of modern econometrics, from a very solid and thorough coverage of OLS to more advanced methods such as panel data analysis, time series (basics, unit roots, co-integration) or ILS and 2SLS (simultaneous equation models). In my opinion, the book can be used for two one-semester courses. The availability of data sets for the computer exercises is useful for both students as well as instructors. Apart from its lack of matrix algebra, this book presents a consistent, solid, but easily understandable introduction into econometric methods so that even survey articles from e.g. the Handbook of International Economics using econometrics are rather easily readable. Kennedy's 'A Guide to Econometrics' makes a good companion, for further studies, Greene's econometric bible ('Econometric Analysis') is probably the most recommendable book.

This book requires little more knowledge than secondary school statistics to start enjoying it. This book, better than any other book I know, enables people to study introductory econometrics by themselves. Even so, it covers a lot of ground (SEM, paneldata and times series analysis). Throughout the author focuses on intuition rather than providing mathematical proofs. The author knows his readership, and never falls into the trap of using technical econometric language or matrix notation. This quality makes this book the best econometrics book for economists.This quality also, however, makes the book less suitable for people who want to master econometrics at a much higher level, as it bridges the gap with economics, but not with the more technical and more advanced books. If this is only your introduction, and you're not going to be able to stay away from the proofs in matrix algebra in the future, then consider A Guide to Modern Econometrics of Marno Verbeek. It is a bit more technical and uses both normal and matrix notation, but shares the attraction of clear examples and intuitive explanation. These two books together should be able to remove texts like Greene and Judge from the study list for economics students new to econometrics.

This book provides excellent intuition about what assumptions we are making and why, and what questions we are trying to find out and how. It establishes the necessary link between real-world data and how to make sense out of it. It is a must-have for people who are interested in econometric analysis. I thank the author for bridging the gap that many econometric textbooks lack.

I own quite a lot of books on econometrics. But this one is I think one of the best. Not in technical detail, but in the clear intuitive explanations. If you want to study a subject by yourself, first read up the subject in this book. Only then move on to the mathematical details in others. Besides the clear presentation of subjects, the excellent real world examples are a great help to gain an understanding. Last but not least, the text put more emphasis on cross-section and panel-data than is usual. Unless youre only interested in macro-econometric modelling this is an approach I warmly endorse. Is there no point of critique? A minor one: the appendices might be shortened, but I imagine others will find them helpfull.