I am a masters student studying economics. The program that I am attending is extremely quantitative with a heavy focus on econometrics. I am looking for a text on time series analysis. I really want something applied but rigorous enough to be considered for an introductory PhD course. I want a text that will be useful in the long run...a reference that I will continue to use later in my career as either an economic consultant or PhD student. Thanks for the help.
I recommend two texts.
- James D. Hamilton, Time Series Analysis, a classic textbook that covers all the theory you need, including fashionable state-space models. It doesn't have any source codes, but I wouldn't call it just theoretic. It has examples. This text is always cited, and it's good to have it handy.
- Shumway, Stoffer, Time Series Analysis and Its Applications: With R Examples - this was our test in statistics PhD level time-series. It has good amount of theory. It's not shallow by any means, but it's focused on applications, comes with R package astsa available in CRAN! You get all the example data and source codes, and powerful functions. The guy who taught us was Bayesian, so this book is very Bayesian friendly without going nuts. It covers all the modern stuff in linear modeling. This is my favorite book on the subject.
Note, Stoffer et al. has a sequel for nonlinear analysis. I haven't read this book yet, can't comment on its merits.
There's one more text: Greene, Econometric Analysis, 7th Edition. It's a standard text in econometrics. It has quite a bit of theory for time series too. One advantage of this text is that all examples are from economics, and that time series chapters can be seen in the context of the body of knowledge of econometrics together with cross-sectional and panel analysis. It can be beneficial in some cases to look at time series this way. It also has many examples, but they're not code examples. If you're specifically interested in time-series, I would not pick this text.