Time-Varying Vector Autoregressive Model - A Survey with the Application to the Japanese Macroeconomic Data -
The time-varying vector autoregressive (VAR) model has recently attracted attention as a time series model for the analysis of macroeconomic variables and developed in various directions. This article explains this model and surveys the recent development of its structure and empirical applications. Since this model is usually estimated using a Bayesian method via the Markov chain Monte Carlo (MCMC), we explain this estimation method in detail. We also provide empirical results based on the Japanese macroeconomic data and show the superior forecasting performance of the time-varying VAR model.
|Date of creation:||Apr 2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.ier.hit-u.ac.jp/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:hst:ghsdps:gd12-232. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tatsuji Makino)
If references are entirely missing, you can add them using this form.