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Topics in Structural VAR Econometrics [electronic resource] / by Carlo Giannini.

By: Contributor(s): Material type: TextTextSeries: Lecture Notes in Economics and Mathematical Systems ; 381Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1992Edition: 1st ed. 1992Description: XI, 136 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783662027578
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 330.1
LOC classification:
  • HB1-846.8
Online resources:
Contents:
1. Introduction -- 2. Identification Analysis and F.I.M.L. Estimation for the K-Model -- 3. Identification Analysis and F.I.M.L. Estimation for the C-Model -- 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model -- 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling -- 6. Long-run A-priori Information. Deterministic Components. Cointegration -- 7. The Working of an AB-Model -- Annex 1: The Notions of Reduced Form and Structure in Structural VAR Modeling -- Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models -- Appendix A -- Appendix B -- Appendix C (by Antonio Lanzarotti and Mario Seghelini) -- Appendix D (by Antonio Lanzarotti and Mario Seghelini) -- References.
In: Springer Nature eBookSummary: 1. Introduction 1 2. Identification Analysis and F.I.M.L. Estimation for the K-Mode1 10 3. Identification Analysis and F.I.ML. Estimation for the C-Model 23 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model 32 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling 44 5 .a Impulse Response Analysis 44 5.b Variance Decomposition (by Antonio Lanzarotti) 51 6. Long-run A-priori Information. Deterministic Components. Cointegration 58 6.a Long-run A-priori Information 58 6.b Deterministic Components 62 6.c Cointegration 65 7. The Working of an AB-Model 71 Annex 1: The Notions ofReduced Form and Structure in Structural VAR Modeling 83 Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models 87 Appendix A 93 Appendix B 96 Appendix C (by Antonio Lanzarotti and Mario Seghelini) 99 Appendix D (by Antonio Lanzarotti and Mario Seghelini) 109 References 128 Foreword In recent years a growing interest in the structural VAR approach (SVAR) has followed the path-breaking works by Blanchard and Watson (1986), Bemanke (1986) and Sims (1986), especially in U.S. applied macroeconometric literature. The approach can be used in two different, partially overlapping directions: the interpretation ofbusiness cycle fluctuations of a small number of significantmacroeconomic variables and the identification of the effects of different policies.
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Item type Home library Collection Call number Status Date due Barcode Item holds
E-Book E-Book Biblioteca Digital Colección SPRINGER 330.1 (Browse shelf(Opens below)) Not For Loan
Total holds: 0

1. Introduction -- 2. Identification Analysis and F.I.M.L. Estimation for the K-Model -- 3. Identification Analysis and F.I.M.L. Estimation for the C-Model -- 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model -- 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling -- 6. Long-run A-priori Information. Deterministic Components. Cointegration -- 7. The Working of an AB-Model -- Annex 1: The Notions of Reduced Form and Structure in Structural VAR Modeling -- Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models -- Appendix A -- Appendix B -- Appendix C (by Antonio Lanzarotti and Mario Seghelini) -- Appendix D (by Antonio Lanzarotti and Mario Seghelini) -- References.

1. Introduction 1 2. Identification Analysis and F.I.M.L. Estimation for the K-Mode1 10 3. Identification Analysis and F.I.ML. Estimation for the C-Model 23 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model 32 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling 44 5 .a Impulse Response Analysis 44 5.b Variance Decomposition (by Antonio Lanzarotti) 51 6. Long-run A-priori Information. Deterministic Components. Cointegration 58 6.a Long-run A-priori Information 58 6.b Deterministic Components 62 6.c Cointegration 65 7. The Working of an AB-Model 71 Annex 1: The Notions ofReduced Form and Structure in Structural VAR Modeling 83 Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models 87 Appendix A 93 Appendix B 96 Appendix C (by Antonio Lanzarotti and Mario Seghelini) 99 Appendix D (by Antonio Lanzarotti and Mario Seghelini) 109 References 128 Foreword In recent years a growing interest in the structural VAR approach (SVAR) has followed the path-breaking works by Blanchard and Watson (1986), Bemanke (1986) and Sims (1986), especially in U.S. applied macroeconometric literature. The approach can be used in two different, partially overlapping directions: the interpretation ofbusiness cycle fluctuations of a small number of significantmacroeconomic variables and the identification of the effects of different policies.

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