Model Reduction Methods for Vector Autoregressive Processes /
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...
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2004.
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| Series: | Lecture notes in economics and mathematical systems ;
536. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | 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. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (x, 218 pages 64 illustrations) |
| ISBN: | 9783642170294 (electronic bk.) 3642170293 (electronic bk.) |
| ISSN: | 0075-8442 ; |