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) method, 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.
