Can someone suggest some "basic" articles (non-mathematical explanation) on Vector Auto-Regression models? I have some text-books in econometrics like Damodar Gujarati, Greene, but these are not attractive (many times because of excessive focus on mathematics rather than on what exactly is happening).
U.F.R. Economie Appliquée, Maîtrise d’Economie Appliquée, Cours de Tronc Commun
Econométrie Appliquée, Séries Temporelles, Christophe HURLIN
Chapitre 5. Représentation VAR et Coinégration. Cours de C. Hurlin
http://www.bankofengland.co.uk/publications/Documents/other/beqm/1999/five.pdf
Helmut Lütkepohl's book is just wonderful!
Here's the reference:
Lütkepohl, H. ``New introduction to multiple time series analysis''. Berlin: Springer, 2005.
Regards,
Lucas.
You can see also http://pareto.uab.es/lgambetti/VAR_Representations.pdf
You'll find a good and easy explanation of VAR models in "Applied Econometrics" by Asteriou and Hall (Palgrave edition). They also offer an empirical example.
Dear, I suggest you to see Lutkepohl 2005 "New Introduction to Multiple Time Series Analysis". Best Regards.
if you prerer a more applied introduction, look for the VAR chapter in Luetkepohl and Kraetzig's "Applied Time Series Econometrics" (published in 2004).
Best
Norbert
I agree with everyone on Lutkepohl's books, but if I were you, I would check the paper from Hendy and Juselius (2001) "Explaining Cointegration Analysis: Part II", Energy Journal. It is a very good introduction --If you can also check the peper "Part I". Then if you have more time and want to do applied work see the "Applied Time Series Econometrics", it is a good guide.
Best,
Rodrigo
Two very easy to read books with real world economic problems are
Hill/Griffiths/Lim Principles of Econometrics
Brooks Chris Introductory Econometrics for Finance
Textbooks are typically un-opionionated. For some opinions on VAR see Peter Kennedy's book "A Guide to Econometrics" edition 4th or later.
Journ. Econ. Perspectives Vol. 15 No. 4 (December 2001)
Vector Autoregressions (pp. 101-115)
James Stock and Mark Watson
Phrase in abstract: This paper critically reviews the use of vector autoregressions (VARs) for four tasks: data description, forecasting, structural inference, and policy analysis. The paper begins with a review of VAR analysis, highlighting the differences between reduced-form VARs, recursive VARs and structural VARs. A three variable VAR that includes the unemployment rate, price inflation and the short term interest rate is used to show how VAR methods are used for the four tasks. The paper concludes that VARs have proven to be powerful and reliable tools for data description and forecasting, but have been less useful for structural inference and policy analysis.
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