Model Reduction Methods for Vector Autoregressive Processes (Lecture Notes in Economics and Mathematical Systems Vol.536) (2004. X, 218 p. w. 105 ill.)

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Model Reduction Methods for Vector Autoregressive Processes (Lecture Notes in Economics and Mathematical Systems Vol.536) (2004. X, 218 p. w. 105 ill.)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 218 p.
  • 商品コード 9783540206439

Description


(Text)
1. 1 Objective of the Study Vector autoregressive (VAR) models have become one of the dominant research tools in the analysis of macroeconomic time series during the last two decades. The great success of this modeling class started with Sims' (1980) critique of the traditional simultaneous equation models (SEM). Sims criticized the use of 'too many incredible restrictions' based on 'supposed a priori knowledge' in large scale macroeconometric models which were popular at that time. Therefore, he advo cated largely unrestricted reduced form multivariate time series models, unrestricted VAR models in particular. Ever since his influential paper these models have been employed extensively to characterize the underlying dynamics in systems of time series. In particular, tools to summarize the dynamic interaction between the system variables, such as impulse response analysis or forecast error variance decompo sitions, have been developed over the years. The econometrics of VAR models and related quantities is now well established and has found its way into various textbooks including inter alia Llitkepohl (1991), Hamilton (1994), Enders (1995), Hendry (1995) and Greene (2002). The unrestricted VAR model provides a general and very flexible framework that proved to be useful to summarize the data characteristics of economic time series. Unfortunately, the flexibility of these models causes severe problems: In an unrestricted VAR model, each variable is expressed as a linear function of lagged values of itself and all other variables in the system.
(Table of content)
1 Introduction.- 1.1 Objective of the Study.- 1.2 Outline of the Study.- 2 Model Reduction in VAR Models.- 2.1 The VAR Modeling Framework.- 2.2 Specification of Subset VAR Models.- 2.2.1 System Versus Single Equation Strategies.- 2.2.2 System Strategies.- 2.2.3 Single Equation Strategies for Subset Modeling.- 2.2.4 Multiple Search Paths Strategies.- 2.2.5 Summarizing Remarks.- 2.3 Monte Carlo Comparison.- 2.3.1 Evaluation of Subset Methods.- 2.3.2 The Monte Carlo Design.- 2.3.3 Monte Carlo Results.- 2.4 Summary.- 3 Model Reduction in Cointegrated VAR Models.- 3.1 The Cointegrated VAR Modeling Framework.- 3.2 Modeling Cointegrated VAR Processes.- 3.3 Data Based Model Reduction.- 3.3.1 Specification of Subset VECMs.- 3.3.2 Testing for Weak Exogeneity.- 3.4 Evaluation of Model Reduction Method.- 3.4.1 Monte Carlo Comparison of Subset Methods.- 3.4.2 Small Sample Properties of Weak Exogeneity Tests.- 3.5 Summary.- 3.A DOP Parameters and Properties.- 4 Model Reduction and Structural Analysis.- 4.1 The Structural VAR Modeling Framework.- 4.2 Estimation of Structural VAR Models.- 4.2.1 Estimation with Unrestricted Reduced Form Parameters.- 4.2.2 Estimation with Restricted Reduced Form Parameters.- 4.2.3 Estimation of Just-identified Models.- 4.2.4 Estimation at Work - An Illustrative Example.- 4.3 Monte Carlo Experiments.- 4.3.1 Model Reduction and the Properties of SVAR Estimates.- 4.3.2 Model Reduction and Impulse Response Point Estimates.- 4.3.3 Model Reduction and Interval Estimates of Impulse Responses.- 4.4 Summary.- 4.A Time Series Plots.- 4.B DGP Parameters.- 5 Empirical Applications.- 5.1 The Effects of Monetary Policy Shocks.- 5.1.1 Introduction.- 5.1.2 Identification of Monetary Policy Shocks.- 5.1.3 The Empirical Model Specification.- 5.1.4 Specifying Subset VAR Models.- 5.1.5 Impulse Response Analysis.- 5.1.6 Conclusion.- 5.2 Sources of German Unemployment.- 5.2.1 Introduction.- 5.2.2 Econometric Methodology.- 5.2.3 A Small Labor Market Model.- 5.2.4 Cointegration Analysis of the German Labor Market.- 5.2.5 Structural Analysis.- 5.2.6 Conclusion.- 5.3 Summary.- 5.A Data Sources.- 5.B Two Cointegrating Vectors.- 5.C VECM Estimates.- 6 Concluding Remarks and Outlook.- 6.1 Summary.- 6.2 Extensions.- Index of Notation.- List of Figures.- List of Tables.

Table of Contents

    Introduction                                   1  (5)
Objective of the Study 1 (2)
Outline of the Study 3 (2)
Model Reduction in VAR Models 5 (54)
The VAR Modeling Framework 5 (4)
Specification of Subset VAR Models 9 (16)
System Versus Single Equation Strategies 12 (1)
System Strategies 13 (3)
Single Equation Strategies for Subset 16 (6)
Modeling
Multiple Search Paths Strategies 22 (3)
Summarizing Remarks 25 (1)
Monte Carlo Comparison 25 (31)
Evaluation of Subset Methods 25 (6)
The Monte Carlo Design 31 (6)
Monte Carlo Results 37 (19)
Summary 56 (3)
Model Reduction in Cointegrated VAR Models 59 (46)
The Cointegrated VAR Modeling Framework 59 (3)
Modeling Cointegrated VAR Processes 62 (3)
Data Based Model Reduction 65 (8)
Specification of Subset VECMs 65 (3)
Testing for Weak Exogeneity 68 (5)
Evaluation of Model Reduction Methods 73 (14)
Monte Carlo Comparison of Subset Methods 73 (10)
Small Sample Properties of Weak 83 (4)
Exogeneity Tests
Summary 87 (15)
DGP Parameters and Properties 102(3)
Model Reduction and Structural Analysis 105(42)
The Structural VAR Modeling Framework 105(5)
Estimation of Structural VAR Models 110(14)
Estimation with Unrestricted Reduced 110(4)
Form Parameters
Estimation with Restricted Reduced Form 114(2)
Parameters
Estimation of Just-identified Models 116(3)
Estimation at Work - An Illustrative 119(5)
Example
Monte Carlo Experiments 124(17)
Model Reduction and the Properties of 125(5)
SVAR Estimates
Model Reduction and Impulse Response 130(2)
Point Estimates
Model Reduction and Interval Estimates 132(9)
of Impulse Responses
Summary 141(3)
Time Series Plots 144(1)
DGP Parameters 145(2)
Empirical Applications 147(50)
The Effects of Monetary Policy Shocks 147(20)
Introduction 147(1)
Identification of Monetary Policy Shocks 148(2)
The Empirical Model Specification 150(2)
Specifying Subset VAR Models 152(5)
Impulse Response Analysis 157(4)
Conclusion 161(6)
Sources of German Unemployment 167(18)
Introduction 167(1)
Econometric Methodology 168(2)
A Small Labor Market Model 170(1)
Cointegration Analysis of the German 171(5)
Labor Market
Structural Analysis 176(8)
Conclusion 184(1)
Summary 185(6)
Data Sources 191(1)
Two Cointegrating Vectors 191(3)
VECM Estimates 194(3)
Concluding Remarks and Outlook 197(6)
Summary 197(3)
Extensions 200(3)
Index of Notation 203(2)
Bibliography 205(8)
List of Figures 213(4)
List of Tables 217