Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model for the Japanese Economy and Monetary Policy
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.
Year of publication: |
2009-05
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Authors: | Nakajima, Jouchi ; Kasuya, Munehisa ; Watanabe, Toshiaki |
Institutions: | Institute for Monetary and Economic Studies, Bank of Japan |
Subject: | Bayesian inference | Markov chain Monte Carlo | Monetary policy | State space model | Structural vector autoregressive model | Stochastic volatility | Time-varying parameter |
Saved in:
Extent: | application/pdf |
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Series: | |
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Number 09-E-13 |
Classification: | C11 - Bayesian Analysis ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; E52 - Monetary Policy (Targets, Instruments, and Effects) |
Source: |
Persistent link: https://ebvufind01.dmz1.zbw.eu/10004972461