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A Bayesian analysis of normalized VAR models

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  • Sun, Dongchu
  • Ni, Shawn

Abstract

Identified vector autoregressive (VAR) models have become widely used on time series data in recent years, but finite sample inference for such models remains a challenge. In this study, we propose a conjugate prior for Bayesian analysis of normalized VAR models. Under the prior, the marginal posterior of VAR parameters involved in identification can be either derived in closed form or simulated through Gibbs sampling. The method developed in the study is applied to a VAR of macroeconomic data.

Suggested Citation

  • Sun, Dongchu & Ni, Shawn, 2014. "A Bayesian analysis of normalized VAR models," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 247-259.
    • Handle: RePEc:eee:jmvana:v:124:y:2014:i:c:p:247-259
    DOI: 10.1016/j.jmva.2013.11.004
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    References listed on IDEAS

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    1. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 10(Win), pages 2-16.
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    6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    7. Hamilton, James D, 1988. "A Neoclassical Model of Unemployment and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 96(3), pages 593-617, June.
    8. Gordon, David B & Leeper, Eric M, 1994. "The Dynamic Impacts of Monetary Policy: An Exercise in Tentative Identification," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1228-1247, December.
    9. Lutz Kilian, 1999. "Finite-Sample Properties of Percentile and Percentile-t Bootstrap Confidence Intervals for Impulse Responses," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 652-660, November.
    10. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
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