Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model for the Japanese Economy and Monetary Policy

Jouchi Nakajima, Munehisa Kasuya and Toshiaki Watanabe

Global COE Hi-Stat Discussion Paper Series from Institute of Economic Research, Hitotsubashi University

Abstract: 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 (search for similar items in EconPapers)
Date: 2009-05
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-mac, nep-mon and nep-ore
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Citations: View citations in EconPapers (18)

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Related works:
Journal Article: Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy (2011)
Working Paper: Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model for the Japanese Economy and Monetary Policy (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:hst:ghsdps:gd09-072

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