Structural Vector Autoregressive Analysis (Themes in Modern Econometrics)

He has published professional articles in Econometrica, the Journal of Econometrics, the Journal of Business and Economic Statistics, Econometric Theory, and the Journal of Applied Econometrics. He is the author of New Introduction to Multiple Time Series Analysis (2010). . Between 2001 and 2003 he served as an adviser to the European Central Bank in Frankfurt am Main, Germany. His work has appeared in Econometrica, the American Economic Review, and the Journal of Political Economy. He

The authors do an excellent job of assembling and lucidly explaining it all. These are key to understanding much of recent research. This book thus devotes considerable space to the issue of identification, including sign restrictions, to Bayesian methods, to Factor Vector Autoregressions and to non-fundamental shocks. The authors masterfully blend theoretical foundations, guidance for practitioners, and detailed empirical applications. This is a must-read for anyone working with SVARs.' Frank Schorfheide, University of Pennsylvania . 'The book by Kilian and Lütkepohl will become the new benchmark textbook for teaching structural vector autoregressive analysis. This book provides a thorough and long-overdue digest of a literature that has been thriving for over 35 years and seen a lot of exciting developments in the past decade. This book is destined to become a classic.' Harald Uhlig, University o

The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. Empirical examples are provided for illustration.. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. It provides guidance to empirical researchers as to the most appropriate mod