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Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications

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  • Jouchi Nakajima

    (Economist, Institute for Monetary and Economic Studies, Bank of Japan. Currently in the Personnel and Corporate Affairs Department (studying at Duke University) (E-mail: jouchi.nakajima@stat.duke.edu))

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    Abstract

    This paper aims to provide a comprehensive overview of the estimation methodology for the time-varying parameter structural vector autoregression (TVP-VAR) with stochastic volatility, in both methodology and empirical applications. The TVP-VAR model, combined with stochastic volatility, enables us to capture possible changes in underlying structure of the economy in a flexible and robust manner. In this respect, as shown in simulation exercises in the paper, the incorporation of stochastic volatility into the TVP estimation significantly improves estimation performance. The Markov chain Monte Carlo method is employed for the estimation of the TVP-VAR models with stochastic volatility. As an example of empirical application, the TVP-VAR model with stochastic volatility is estimated using the Japanese data with significant structural changes in the dynamic relationship between the macroeconomic variables.

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    File URL: http://www.imes.boj.or.jp/research/papers/me29-6.pdf
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    Bibliographic Info

    Article provided by Institute for Monetary and Economic Studies, Bank of Japan in its journal Monetary and Economic Studies.

    Volume (Year): 29 (2011)
    Issue (Month): (November)
    Pages: 107-142

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    Handle: RePEc:ime:imemes:v:29:y:2011:p:107-142

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    Related research

    Keywords: Bayesian inference; Markov chain Monte Carlo; Monetary policy; State space model; Structural vector autoregression; Stochastic volatility; Time-varying parameter;

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    Cited by:
    1. Jouchi Nakajima & Munehisa Kasuya & Toshiaki Watanabe, 2009. "Bayesian Analysis of Time-Varying Parameter Vector Autoregressive Model for the Japanese Economy and Monetary Policy," IMES Discussion Paper Series 09-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
    2. Masazumi Hattori & Andreas Schrimpf & Vladyslav Sushko, 2013. "The response of tail risk perceptions to unconventional monetary policy," BIS Working Papers 425, Bank for International Settlements.
    3. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    4. Kriwoluzky, Alexander & Kliem, Martin & Sarferaz, Samad, 2013. "On the low-frequency relationship between public deficits and inflation," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80000, Verein für Socialpolitik / German Economic Association.

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