PDF Ebook Time Series Analysis, by James Douglas Hamilton
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Time Series Analysis, by James Douglas Hamilton
PDF Ebook Time Series Analysis, by James Douglas Hamilton
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The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.
The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.
- Sales Rank: #53579 in Books
- Brand: Brand: Princeton University Press
- Published on: 1994-01-11
- Original language: English
- Number of items: 1
- Dimensions: 10.08" h x 2.17" w x 6.98" l, 3.75 pounds
- Binding: Hardcover
- 820 pages
- Used Book in Good Condition
Review
"A carefully prepared and well written book. . . . Without doubt, it can be recommended as a very valuable encyclopedia and textbook for a reader who is looking for a mainly theoretical textbook which combines traditional time series analysis with a review of recent research areas."--Journal of Economics
From the Inside Flap
"I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students."--John H. Cochrane, University of Chicago
From the Back Cover
"I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students."--John H. Cochrane, University of Chicago
Most helpful customer reviews
57 of 59 people found the following review helpful.
time series for econometricians especially
By Michael R. Chernick
This is a large text in time series analysis that is designed for graduate students as the author acknowledges in his preface. It deals primarily with the theory and the tools rather than providing practical applications. It does not require a Ph.D. but does require a fair amount of mathematical sophistication that comes from advanced courses in probability and statistics. There are many good books at this level. This one has some unique features. It covers the traditional ARIMA models that can be found in most texts and uses the operator notation that Box and Jenkins introduced. It adds vector autoregressions which is fairly recent material. Spectral analysis (the frequency domain approach)is also covered and asymptotic theory is presented. Linear systems (more common to econometric time series than in the standard statistical books) is covered. Topics not commonly covered in competitor texts include nonstationary cases (both univariate and multivariate)with unit roots to the characteristic equation, Bayesian approaches, heteroscedastic models including the ARCH models and the topic of cointegration originally developed by Clive Granger. The book is loaded with references to the literature and is slanted towards methods useful in econometrics. Other good books at this level include Brockwell and Davis (1987), Fuller (1976), Anderson (1971), Harvey (1981) and Shumway and Stoffer (2000). Good texts solely in the frequency domain include Bloomfeld (1976), Priestley (1981), Koopmans (1974) and Brillinger (1981). Box, Jenkins and Reinsel (1994) provides practical applications using the Box-Jenkins time domain approach.
6 of 6 people found the following review helpful.
A good reference book
By A Customer
I bought it as a reference book since it contains a lot of materials. It lacks details on some new materials, such as, GARCH model. It also has less real life example explaining the use of the methodology as the usual statistics books do. This makes difficult for reader to judge the usefulness of the material he is not familiar with.
6 of 6 people found the following review helpful.
Absolutely Excellent (for what it is)
By J. Baird
Hamilton is often dubbed, "too hard to understand." That may be true, but actually it seems to be much more reasonable and readable than other econometrics texts I have attempted to read.
I would definitely not start out into econometrics with this book though. You probably will not be able to appreciate how good this book is until you have tried to read something as atrocious as Greene.
As is typical with almost every upper level econometrics book, it assumes you have a wide mathematical and statistical knowledge base that you may or may not have. I would not recommend it as a beginning graduate econometrics book but it is a great reintroduction to time series methods. I will say that I haven't found a single book yet in intermediate econometrics that I felt was written clearly or concisely.
Still, overall, this has been by far the best among the worst and I would highly recommend reading it to anyone who is beginning to study time series econometrics in some detail.
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