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This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.
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This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 756
- Erscheinungstermin: 6. Februar 2018
- Englisch
- Abmessung: 235mm x 157mm x 45mm
- Gewicht: 1228g
- ISBN-13: 9781107196575
- ISBN-10: 1107196574
- Artikelnr.: 49562034
- Verlag: Cambridge University Press
- Seitenzahl: 756
- Erscheinungstermin: 6. Februar 2018
- Englisch
- Abmessung: 235mm x 157mm x 45mm
- Gewicht: 1228g
- ISBN-13: 9781107196575
- ISBN-10: 1107196574
- Artikelnr.: 49562034
Lutz Kilian is Professor of Economics at the University of Michigan, Ann Arbor. Between 2001 and 2003 he served as an adviser to the European Central Bank in Frankfurt am Main, Germany. Professor Kilian has been a research visitor at the Federal Reserve Board, the Bank of Canada, the European Central Bank, and the International Monetary Fund. His work has appeared in Econometrica, the American Economic Review, and the Journal of Political Economy. He has served as associate editor of the Journal of Business and Economic Statistics, among other journals.
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.
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.
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.
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.