This paper analyzes the time-varying parameter vector autoregressive (TVP-VAR) model for the Japanese economy and monetary policy. The time-varying parameters are estimated via the Markov chain Monte Carlo method and the posterior estimates of parameters reveal the time-varying structure of the Japanese economy and monetary policy during the period from 1981 to 2008. The marginal likelihoods of the TVP-VAR model and other VAR models are also estimated. The estimated marginal likelihoods indicate that the TVP-VAR model best fits the Japanese economic data.
Keywords: Bayesian inference; Markov chain Monte Carlo; Monetary policy; State space model; Structural vector autoregressive model; Stochastic volatility; Time-varying parameter
Views expressed in the paper are those of the authors and do not necessarily reflect those of the Bank of Japan or Institute for Monetary and Economic Studies.