Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model with the Ordering of Variables for the Japanese Economy and Monetary Policy
AbstractThis paper applies the time-varying parameter vector autoregressive model to the Japanese economy. The both parameters and volatilities, which are assumed to follow a random-walk process, are estimated using a Bayesian method with MCMC. The recursive structure is assumed for identification and the reversible jump MCMC is used for the ordering of variables. The empirical result reveals the time-varying structure of the Japanese economy and monetary policy during the period from 1981 to 2008 and provides evidence that the order of variables may change by the introduction of zero interest rate policy.
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Bibliographic InfoPaper provided by Institute of Economic Research, Hitotsubashi University in its series Global COE Hi-Stat Discussion Paper Series with number gd11-196.
Date of creation: Jul 2011
Date of revision:
Bayesian inference; Monetary policy; Reversible jump Markov chain Monte Carlo; Stochastic volatility; Time-varying parameter VAR;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-08-09 (All new papers)
- NEP-CBA-2011-08-09 (Central Banking)
- NEP-ECM-2011-08-09 (Econometrics)
- NEP-ETS-2011-08-09 (Econometric Time Series)
- NEP-MON-2011-08-09 (Monetary Economics)
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