Model Reduction Methods for Vector Autoregressive Processes

Ralf Brüggemann - Collection Lecture Notes in Economics and Mathematical Systems

220 pages, parution le 11/02/2004

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Résumé

Vector Autoregressive (VAR) models have become one of the dominant tools for the empirical analysis of macroeconomic time series. Sometimes the flexibility of VAR models leads to overparameterized models, making accurate estimates of impulse responses and forecasts difficult. This book introduces a variety of data-based model reduction methods and provides a detailed investigation of different reduction strategies in the context of popular VAR modelling classes, including stationary, cointegrated and structural VAR models. VAR practitioners benefit from guidelines being developed for using model reduction in applied work. The use of different reduction techniques is illustrated by means of empirical models for US monetary policy shocks and a structural vector error correction model of the German labor market.

Written for:
Scientists, practitioners

Sommaire

Introduction
Model Reduction in VAR Models
Model Reduction in Cointegrated VAR Models
Model Reduction and Structural Analysis
Empirical Applications
Concluding Remarks and Outlook
Index of Notation
Bibliography.

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Ralf Brüggemann
Collection	Lecture Notes in Economics and Mathematical Systems
Parution	11/02/2004
Nb. de pages	220
Format	15,5 x 23,5
Couverture	Broché
Poids	370g
Intérieur	Noir et Blanc
EAN13	9783540206439