Markov-Switching Vector Autoregressions Modelling, Statistical Inference, and Application to Business Cycle Analysis
This book contributes to re cent developments on the statistical analysis of multiple time series in the presence of regime shifts. Markov-switching models have become popular for modelling non-linearities and regime shifts, mainly, in univariate eco nomic time series. This study is intended to pro...
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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg
Springer Berlin Heidelberg
1997, 1997
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| Edition: | 1st ed. 1997 |
| Series: | Lecture Notes in Economics and Mathematical Systems
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| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- Prologue
- 1 The Markov-Switching Vector Autoregressive Model
- 2 The State-Space Representation
- 3 VARMA-Representation of MSI-VAR and MSM-VAR Processes
- 4 Forecasting MS-VAR Processes
- 5 The BLHK Filter
- 6 Maximum Likelihood Estimation
- 7 Model Selection and Model Checking
- 8 Multi-Move Gibbs Sampling
- 9 Comparative Analysis of Parameter Estimation in Particular MS-VAR Models
- 10 Extensions of the Basic MS-VAR Model
- 11 Markov-Switching Models of the German Business Cycle
- 12 Markov-Switching Models of Global and International Business Cycles
- 13 Cointegration Analysis of VAR Models with Markovian Shifts in Regime
- Epilogue
- References
- Tables
- Figures
- List of Notation