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 | | Econometric Models and Economic Forecasts by Robert S Pindyck, Daniel L Rubinfeld ISBN-10: 0079132928 ISBN-10: 0-07-913292-8 ISBN-13: 9780079132925 ISBN-13: 978-0-07-913292-5 Hardcover 1997-07-01 McGraw-Hill/Irwin Find Lowest Price |
Editorials | ||
Product Description First course in Econometrics in Economics Departments at better schools, also Economic/Business Forecasting. Statistics prerequisite but no calculus. Slightly higher level and more comprehensive than Gujarati (M-H, 1996) . P-R covers more time series and forecasting. P-R coverage is notch below Johnston-DiNardo (M-H, 97) and requires no matrix algebra. Includes data disk. | ||
Reviews | ||
muddy reading The notation can be hard to follow if you don't have a grasp or natural incline for statistical regression. Steps are hard to come by in some problems because too many steps are skipped for a beginner. It is almost necessary to have at least a basic statistics background before reading this. Even though I had a background and had read ahead, I had to depend on my professor to truly understand the material at all. If your professor has an accent or goes quite fast, and if you don't have classmates you can work with, using this book alone will be more than painful. I would suggest a supplement such as "Using Econometrics: A Practical Guide (4th Edition should suffice) [Hardcover] by Studenmund" if you are just beginning to learn about regression. | ||
Deceivingly more information than you think - half way between introductory and advanced In sum: This book is half-way in between an introductory text (i.e. Wooldridge - Introductory Econometrics) and an advanced graduate textbook (Greene - Econometric Analysis). Wooldridge's introductory textbook is certainly better suited for a first class in econometrics. Pindyck and Rubinfeld provide an excellent complement however, particularly for mid-level graduate students. Appendices show the matrix form derivations of most estimators, and provides a treatment of the GMM estimator, neither of which you will find in an purely introductory course. Really the appendices are where the more advanced treatments are offered to the interested reader. Sections on forcasting and time series models in this book are greatly superior than what is offered in introductory texts (which usually is no presentation at all). Pindyck and Rubinfeld do not waste a word in this textbook. There's a discussion on pretty much all the estimators, although some of these are short (one paragraph and no equations for the ordered probit - but you can't have it all!). If you know nothing about econometrics then this is not the book for you. I was forced to buy it in my introductory econometrics class and had no idea what was going on. Then I had a competent instructor and lots of Wooldridge reading. This book helped me through Master's level econometrics and makes for good subway reading, but will definitely be shy of what you need for a PhD in economics. For PhD you will need Greene OR [Hamilton (1994) AND Wooldridge's Cross Section and Panel Data book]. | ||
Good beginners' book This is a beginners' book, and for those, I would recommend its use, but only in addition to using it with Gujarati's. Pindyck's book is very simple and well explained. Its advantage over other books is that it is concerned with forecasting, something that other basic books do not do. It is a little bit more advanced than Gujarati's but lays between that one and Maddala's book. | ||
Great equations, bad explanations The subject of econometrics is difficult for the beginner. I have yet to encounter a text that does a great job at explaining both the concepts and the math required to be proficient in this field. I completed three courses, two undergraduate and one graduate level, for which this book was the required text. Like most of my classmates I was never able to fully comprehend the concepts behind the numbers using this text alone. Now that I have a better grasp of econometrics I will vehemently suggest that this text provides a poor verbal description of what a student is actually doing when analyzing data. I found myself reading the chapters 2 or 3 times and still felt unsure of what was going on. Where this book is strong is in its presentation of equations. I highly recommend supplementing this text with Peter Kennedy's, "A Guide to Econometrics," which gives excellent verbal explanations but de-emphasizes the math. These two texts together make a great study for a difficult subject. | ||
It's not that bad I'm giving this book 5 stars largely to balance out the somewhat unfair reviews that were given. For what it is -- an econometrics textbook that tries to present overview of neginning to intermediate econometrics and forecasting WITHOUT a lot of linear algebra -- it's a pretty good book. While it has its rough spots, the book has many good features. One of the really good features of this book is presenting the material with an emphasis on model building ... a very important emphasis that is too often ignored in other econometrics texts. In an ideal world, this book deserves at least an average of 4 stars and would deserve more if the readers made things more readable and better incorporated advances in econometrics since previous editions. | ||