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Summary: Need to Know
Rating: 4
Nice book, personally dislike the subject matter but it did a good job of explaining the topic.
Summary: know your calculus
Rating: 3
Know your calculus well before buying this book: this book has rigorous use of theoretical proofs, albeit optional.
The information in this book is in concentrated format. It exists to cover the core of econometrics in the shortest time possible, supported by mathematical proofs.
This book will benefit a person who is well versed in mathematical economics and statistics, if you are such a person then this book will offer you a decent insight into econometrics.
For persons with no such talents this book will be intimidating to work through and I don't think you will gain much from it, it would only lead to frustration.
'Undergraduate Econometrics' is not as good as Gujaratis's book Basic Econometrics, so if you have a choice (and time) then get Gujarati instead - he offers better explanations and covers more ground.
Summary: Very good for learning
Rating: 5
This book is a shortened version of "Learning and Practising Econometrics (1993)", which itself is a shortened version of "The Theory and Practice of Econometrics (1982)".
Hill's "Undergraduate Econometrics" instills understanding by slowly going through derivations and principles, while at the same time motivating econometric analysis by referring to economic situations where it can be used. Much better than Gujarati (which tends to be a "cookery book" rather than giving an integrated treatment).
The book both motivates the student and takes them through the steps and methods they will need to adopt in further econometric studies, and always provides a good reference (often to one of the parent books mentioned above) when it omits proofs and other details.
The only weakness of the book reveals what is (to my mind) an unhealthy preoccupation with estimation issues, as opposed to those of data quality. As people like Granger have consistently pointed out, the real issues in 21st century econometrics have to do with what sort of data we have, and what methods are most appropriate in different situations. Despite this, Hill et al almost exclusively dwell on the identically and independently distributed (iid) specification. However, I should point out in the book's defence that this preoccupation is shared by most other introductory (and graduate) textbooks on econometrics.
The book's good points far outweigh these weaknesses. Finally, the second edition has some updates, and discusses such developments as time series econometrics. "Undergraduate Econometrics" should definitely be purchased by anyone wishing to learn about modern empirical methods.
Summary: Excellent intuition BUT A POOR BRIDGE TO THE DREADFUL GREENE
Rating: 4
This book is the best book to use for the very first course in econometrics. It takes you by the hand to teach you all you need in terms of the basics.
I only give it 4 stars for two reasons. First, while this book is non-mathematical (and I agree with that) it should have nonetheless appendices that make use of matrices and differential calculus.
Second, this book is extremely expensive.
This book can easily earn 5 stars if in the next edition it contains appendices that will create a bridge towards intermediate econometrics. A more reasonable price would also be welcomed.
Overall, this is the best book to use for a very first course in econometrics.
BUT BEWARE: THIS BOOK IS A POOR BRIDGE TO THE DREADFUL GREENE!!!!THE BEST BRIDGE IS "LEARNING AND PRACTICING ECONOMETRICS" BY THE SAME AUTHOURS OF "UNDERGRADUATE ECOMETRICS" I.E. HILL, GRIFFITHS, AND JUDGE.
By the way, for those that are looking for a good substitue to "Undergraduate Econometrics", you have "Basic Econometrics" by Gujarati.
Thank you,
Summary: carter makes me not-so-afraid of metrics...
Rating: 4
this is one of those econometrics (i'll call it "metrics" from now on to save on typing) books which you know has to cover alot of the slow, boring stuff which lecturers expect students to know by the time they take metrics options and hated by undergraduates. having said that, this book does it quite well. one thing i hate in metrics texts is dense mathematical proofs. especially proofs which assume the reader knows other proofs intimately. this book nicely avoids that, dropping in an adequate and useful amount of proofs, especially the Gauss-Markov Theorem and a proof of why OLS estimation outshines any other method in simple regression analysis. the book does this without being overwhelming - in my opinion, mathematics has to be appreciated through discussion and argument, which Hill et al do quite admirably. Also, metrics is about interpretation of results, not just calculating them, and this book keeps that in mind very well from beginning to end. The reason i gave this book 4 stars is simple. when i was doing my last minute cramming for exams, i was able to move through the book quickly and easily, whilst still appreciating the main points, the big picture, and also the subtleties of more advanced topics like GLS, moments-based estimation and distributed lags in a short space of time. the book also comes with useful end-of-chapter "should know" points and problems. the best thing about the problems is the "real-world" nature of the tasks, often drawing on real-life data and economic intuition. using that data and being able to become comfortable with computer techniques is the most vital thing to a beneficial study of metrics. i found gujarati's "basic econometrics" a nice companion to this book (but then again everyone likes gujarati to some extent), but mostly i was satisfied with this book as a stand-alone manual to second-year metrics studies, good for laying the foundations for studies in topics like maximum likelihood estimation and financial econometrics. oh, and it's small and not too heavy. good for carrying around to classes all day!
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