New Introduction to Multiple Time Series Analysis

This book provides a fairly elementary view of the vast subject of time series analysis. It easy to read and the author provides lots of basic calculations. Typically, such books stay away from the cutting edge topics but not this one. It is quite complete. I highly recommend it to anyone that knows a few basic things about time series and wants to take it much further.

I think "New introduction to multiple time series analysis" is not an introduction level book. You must have a high level inference knowledge. Beyond this, you must be familiar with a high level knowhow in algebra and a very good level of a calculus course. Some numerical methods are explored in the book too. Essentialy it deals with multiple time series models. If you are a beginer on the subject an introductory course in univariate time series will be strongly needed.

Very well-written and well-structured, this is a must IMO for anyone who is serious about time series analysis.

It's a great book! It is as simple as it could be, and very complete at the same time, so it is great. I am a PhD student and I strongly recommend this book for people interested in VAR and VEC models...

I love this book - it provides an excellent introduction to the core of multiple time series. I especially like the discussions on cointegration and granger causality, which have proven to be extremely useful in practice. I would recommend it to anyone.

It's a great compilation of principal techniques of multiple time series models and inference. In addtion a very useful matrix properties and formulas list in appendix.

With a lot of demonstration and simples examples!!! Well written and complete! Recomended for every one who's study time series.

It's great as expected.

This is definitely a graduate level text and should not be considerd by any stretch as a book for those without a good grounding in linear univarite time series methods. Nor, would it be possible to cover the main chapters 1-12 in a semester - chapters 1-8 maybe!Nevertheless it is an excellent book, probably the best book covering VAR and VECM models. The early chapters of the book cover the VAR model really well including causality, parameter estimation and impulse response. Then there are excellent chapters on the VECM model and cointegration and estimation, though a lot of other stuff such as martingale differences and brownian motion are added to the mix to complicate the picture.Chapter 10 is somewhat weak as most real world VAR models will probably be VARX models. More information could be given on linking estimated GLS and 2 and 3 stage LS - this leaves a gap with the traditional approach where it must be assumed that endogenous variables are the basis of all VARX models.In this regard chapters 10 and 18 need more work as the Kalman filter could be used a lot more effectively to estimate more parsimonous models than the VECM structure.

Goooooood!!

Fantastic book, very comprehensive.

I'm sure it's a fine book if you're a doctoral student in economics, but too much for me. I also favour more applied texts that show worked data analysis, but this book leans more toward proofs.

Sin duda, uno de los libros más completos que hay sobre el tema. Muy bueno a nivel teórico. Requiere de una base algebraica y econométrica sólida, pero el apéndice facilita mucha las cosas para quien lo pueda necesitar. Los gráficos, ejemplos y ejercicios propuestos resultan de gran utilidad.