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Forecasting Chinese inflation and output: A Bayesian vector autoregressive approach

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  • Huang, Y-F.
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    Abstract

    This study compares several Bayesian vector autoregressive (VAR) models for forecasting price inflation and output growth in China. The results indicate that models with shrinkage and model selection priors, that restrict some VAR coefficients to be close to zero, perform better than models with Normal prior.

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    File URL: http://mpra.ub.uni-muenchen.de/41933/
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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 41933.

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    Date of creation: Oct 2012
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    Handle: RePEc:pra:mprapa:41933

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    Keywords: BVAR; factor model; shrinkage priors;

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    1. Korobilis, Dimitris, 2011. "Hierarchical shrinkage priors for dynamic regressions with many predictors," MPRA Paper 30380, University Library of Munich, Germany.
    2. Gary M. Koop, 2013. "Forecasting with Medium and Large Bayesian VARS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 177-203, 03.
    3. Dimitris Korobilis, 2013. "Var Forecasting Using Bayesian Variable Selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 204-230, 03.
    4. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    5. Mehrotra , Aaron & Sánchez-Fung, José R., 2008. "Forecasting Inflation in China," BOFIT Discussion Papers 2/2008, Bank of Finland, Institute for Economies in Transition.
    6. Korobilis, Dimitris, 2008. "Forecasting in vector autoregressions with many predictors," MPRA Paper 21122, University Library of Munich, Germany.
    7. Dimitris Korobilis, 2009. "Assessing the Transmission of Monetary Policy Shocks Using Dynamic Factor Models," Working Paper Series 35_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
    8. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    9. Philipp Maier, 2011. "Mixed Frequency Forecasts for Chinese GDP," Working Papers 11-11, Bank of Canada.
    10. Marcellino, Massimiliano & Stock, James H & Watson, Mark W, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," CEPR Discussion Papers 4976, C.E.P.R. Discussion Papers.
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