Lutz KilianCambridge University Press, 11/23/2017EAN 9781316647332, ISBN10: 1316647331Paperback, 754 pages, 22.9 x 15.2 x 4.8 cmLanguage: EnglishStructural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. 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. Empirical examples are provided for illustration.1. Introduction2. Vector autoregressive models3. Vector error correction models4. Structural VAR tools5. Bayesian VAR analysis6. The relationship between VAR models and other macroeconometric models7. A historical perspective on causal inference in macroeconometrics8. Identification by short-run restrictions9. Estimation subject to short-run restrictions10. Identification by long-run restrictions11. Estimation subject to long-run restrictions12. Inference in models identified by short-run or long-run restrictions13. Identification by sign restrictions14. Identification by heteroskedasticity or non-gaussianity15. Identification based on extraneous data16. Structural VAR analysis in a data-rich environment17. Nonfundamental shocks18. Nonlinear structural VAR models19. Practical issues related to trends, seasonality, and structural changeReferencesIndex.
