Econometric Theory and Methods International Edition Paperback – 26 Dec 2008
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"This is the best textbook of econometric theory to have emerged in a long while; and it deserves to find a place on the bookshelf of every instructor. It is bound to find favour with the students." Stephen Pollock, Queen Mary College, University of London --This text refers to the Hardcover edition.
About the Author
RUSSELL DAVIDSON holds the Canada Research Chair in Econometrics at McGill University in Montreal. He also teaches at GREQAM in Marseille and previously taught for many years at Queen's University. He has a Ph.D. in Physics from the University of Glasgow and a Ph.D. in Economics from the University
of British Columbia. Professor Davidson is a Fellow of the Econometric Society and the author of many scientific papers. He is the coauthor of Estimation and Inference in Econometrics (OUP, 1993).
JAMES G. MACKINNON is the Sir Edward Peacock Professor of Econometrics and Head of the Department at Queen's University in Kingston, Ontario, Canada, where he has taught since obtaining his Ph.D. from Princeton University in 1975. He is a Fellow of the Econometric Society and of the Royal Society of
Canada and a past President of the Canadian Economics Association (2001-2002). Professor MacKinnon has written more than seventy journal articles and book chapters, and he is the coauthor of Estimation and Inference in Econometrics (OUP, 1993).
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Top Customer Reviews
Honestly I'm mad at the Oxford Univ. Press (OUP). This book had the makings to be the great bible of the econometrics subject.
The book has a decent amount of typos, some more severe than others, but that's to be expected when you write a book on this subject with 700 pages... You can compare with the Green's book. The latter has much more. The problem is that some lazy people at OUP decided to disregard the corrections the author have been making this last years. So, you get all the typos, since the first printing, when one would expect to get a revised edition. OUP please be more professional.
P.S: Make sure you don't by the 2009 printing of this edition. It's the same as the 1st printing of regular edition. It has taken me more than 3hr just to correct almost half of all the typos that are presented in the authors' site. OUP please go f@q yourselves. What @ssh( )les...
P.S.: Still doing some typo corrections. However, it's the first time I see a correction of a typo from a previous correction of a previous typo. Honestly, the authors could have done a better job... Losing my mind with these corrections. Also, I've never seen a typo list with so many euphemisms...
When I first bought the book I was expecting an exposition at the level of Hayashi's Econometrics. Unfortunately, it lacks many details. The book is too verbose as if trying to compensate for some mathematical 'details' which are hidden away. This is very annoying.Read more ›
The BEST text for intermediate level Econometrics (final year undergrad/ Masters).
Clearly explains difficult concepts and intuitions.
Most Helpful Customer Reviews on Amazon.com (beta)
Throughout the book Davidson and MacKinnon focus on developing intuition rather than on mechanical calculation. In particular, their geometric approach to ordinary least squares estimation is a must read. By focussing on the geometry and making clever use of the Frisch-Waugh-Lovell theorem, they make the properties of OLS very intuitive. Many of the standard results usually proved by opaque matrix algebra in other books, become clear and easy to prove in this framework.
The book also has the advantage of covering topics like GMM estimation, the bootstrap and numerical methods that cannot be found in older textbooks.
Yet, I have three quibbles with this book.
The first, minor one, is that its treatment of time series methods is too short, and unlike the rest of the book tries to trade off depth for breadth.
The second, bigger problem with this book is that it is entirely about econometric 'theory'. It teaches you how to find estimators and test statistics with good properties for particular models. But it does not train the student at all in the applied/methodological aspects of econometrics: given that I have a vague question about economic phenomena in mind, and given a bunch of data, how do I proceed? What questions can be meaningfully asked, how to choose between alternative models, how to present and interpret results, are questions that are given a short shrift in this book. Even data-based exercises are few and seem to have been reluctantly included.
The third problem with this book is that it completely ignores the Bayesian approach to econometrics. Though this is in line with the general frequentist dominance of the econometrics profession, I feel that without at least an introduction to the Bayesian approach, the training of an econometrician will remain one-sided.
The first two shortcomings of this book can be addressed by complementing it with Hayashi's Econometrics. Many interesting papers on methodology can be found in the book Modelling Economic Series edited by Granger.
Only with this book and Johnston & Dinardo's, read and enjoy, then you will understand econometrics absolute confidently.
Don't wast your money on other books!
However, there're still things you may take away from this book. For example, they present the classical regression model in the framework of matrix project, subspaces, etc., which is not usually treated this way in other texts. This approach makes many tedious matrix manipulation easier.
In my opinion, if you are looking for your first metrics book beyond the undergrad level, definately go for Hayashi first. This is simply the BEST book in terms of learning. For some more depth and alternative pespective, then consider this one.