Topics in Structural VAR Econometrics

1. Front Matter

   Pages I-XI

   PDF

2. Introduction

   • Carlo Giannini

   Pages 1-9

3. Identification Analysis and F.I.M.L. Estimation for the K-Model

   • Carlo Giannini

   Pages 10-22

4. Identification Analysis and F.I.M.L. Estimation for the C-Model

   • Carlo Giannini

   Pages 23-31

5. Identification Analysis and F.I.M.L. Estimation for the AB-Model

   • Carlo Giannini

   Pages 32-43

6. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling

   • Carlo Giannini

   Pages 44-57

7. Long-run A-priori Information. Deterministic Components. Cointegration

   • Carlo Giannini

   Pages 58-70

8. The Working of an AB-Model

   • Carlo Giannini

   Pages 71-82

9. Back Matter

   Pages 83-136

   PDF

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.

• Bootstrapping
• Likelihood
• Simulation
• Statistik
• Vector Autoregressive Models
• autoregressive Modelle
• econometrics
• integration
• mathematical statistics
• modeling
• statistics
• value-at-risk
• Ökonometrie

• Department of Economics, University of Ancona, Ancona, Italy

  Carlo Giannini

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