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Více o knize
This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields. Inhaltsverzeichnis 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 macroeconometric models; 7. A historical perspective on causal inference in macroeconometrics; 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; References; Index.
Nákup knihy
Structural Vector Autoregressive Analysis, Lutz Kilian, Helmut Lütkepohl
- Jazyk
- Rok vydání
- 2018
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- (pevná)
Doručení
Platební metody
Navrhnout úpravu
- Titul
- Structural Vector Autoregressive Analysis
- Jazyk
- anglicky
- Autoři
- Lutz Kilian, Helmut Lütkepohl
- Vydavatel
- Cambridge University Press
- Rok vydání
- 2018
- Vazba
- pevná
- Počet stran
- 756
- ISBN13
- 9781107196575
- Kategorie
- Podnikání a ekonomie
- Anotace
- This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields. Inhaltsverzeichnis 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 macroeconometric models; 7. A historical perspective on causal inference in macroeconometrics; 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; References; Index.