Structural vector autoregressive analysis

Cambridge University Press

2017

xx, 735 p.

Themes in modern econometrics

1. Introduction 2. Vector autoregressive models 3. Vector error correction models 4. Structural VAR tools 5. Bayesian VAR analysis 6. The relationship between VAR models and other macroeconomic models 7. A historical perspective on causal inference in macroeconomics 8. Identification by short-run restrictions 9. Estimation subject to short-run restrictions 10. Identification by long-run restrictions 11. Estimation subject to long-run restrictions 12. Inference in models identified by short-run or long-run restrictions 13. Identification by sign restrictions 14. Identification by heteroskedasticity or non-Gaussianity 15. Identification based on extraneous data 16. Structural VAR analysis in a data-rich environment 17. Nonfundamental shocks 18. Nonlinear structural VAR models 19. Practical issues related to trends, seasonality, and structural change

9781108164818

"Structural 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 and methods of estimating and evaluating structural VAR models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers.

Английский