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Analysing shock transmission in a data-rich environment: A large BVAR for New Zealand

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Abstract

We analyse a large Bayesian Vector Autoregression (BVAR) containing almost one hundred New Zealand macroeconomic time series. Methods for allowing multiple blocks of equations with block-specific Bayesian priors are described, and forecasting results show that our model compares favourably to a range of other time series models. Examining the impulse responses to a monetary policy shock and to two less conventional shocks – net migration and the climate – we highlight the usefulness of the large BVAR in analysing shock transmission.

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  • Chris Bloor & Troy Matheson, 2008. "Analysing shock transmission in a data-rich environment: A large BVAR for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2008/09, Reserve Bank of New Zealand.
  • Handle: RePEc:nzb:nzbdps:2008/09
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    Cited by:

    1. Güneş Kamber & Chris McDonald & Nicholas Sander & Konstantinos Theodoridis, 2015. "A structural model for policy analysis and forecasting: NZSIM," Reserve Bank of New Zealand Discussion Paper Series DP2015/05, Reserve Bank of New Zealand.
    2. Gallic, Ewen & Vermandel, Gauthier, 2017. "Weather Shocks, Climate Change and Business Cycles," MPRA Paper 81230, University Library of Munich, Germany.
    3. Rangan Gupta & Marius Jurgilas & Alain Kabundi & Stephen M. Miller, 2011. "Monetary policy and housing sector dynamics in a large-scale Bayesian vector autoregressive model," International Journal of Strategic Property Management, Taylor & Francis Journals, vol. 16(1), pages 1-20, August.
    4. Eickmeier, Sandra & Ng, Tim, 2011. "Forecasting national activity using lots of international predictors: An application to New Zealand," International Journal of Forecasting, Elsevier, vol. 27(2), pages 496-511, April.
    5. Nicholas Sander, 2013. "Migration and the housing market," Reserve Bank of New Zealand Analytical Notes series AN2013/10, Reserve Bank of New Zealand.
    6. Rangan Gupta & Marius Jurgilas & Stephen M. Miller & Dylan van Wyk, 2010. "Financial Market Liberalization, Monetary Policy, and Housing Price Dynamics," Working Papers 201009, University of Pretoria, Department of Economics.
    7. Kamber, Gunes & McDonald, Chris & Sander, Nick & Theodoridis, Konstantinos, 2016. "Modelling the business cycle of a small open economy: The Reserve Bank of New Zealand's DSGE model," Economic Modelling, Elsevier, vol. 59(C), pages 546-569.
    8. Bloor, Chris & Matheson, Troy, 2011. "Real-time conditional forecasts with Bayesian VARs: An application to New Zealand," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 26-42, January.
    9. Rangan Gupta, 2012. "Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment," Working Papers 201214, University of Pretoria, Department of Economics.
    10. Dean Ford & Amy Wood, 2015. "El Niño and its impact on the New Zealand economy," Reserve Bank of New Zealand Analytical Notes series AN2015/07, Reserve Bank of New Zealand.
    11. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    12. Adina Popescu & Alina Carare, 2011. "Monetary Policy and Risk-Premium Shocks in Hungary; Results from a Large Bayesian VAR," IMF Working Papers 11/259, International Monetary Fund.
    13. Balcilar, Mehmet & Gupta, Rangan & Shah, Zahra B., 2011. "An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa," Economic Modelling, Elsevier, vol. 28(3), pages 891-899, May.
    14. John Muellbauer, 2010. "Household decisions, credit markets and the macroeconomy: implications for the design of central bank models," BIS Working Papers 306, Bank for International Settlements.
    15. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, Elsevier.
    16. Chris Bloor & Chris McDonald, 2013. "Estimating the impacts of restrictions on high LVR lending," Reserve Bank of New Zealand Analytical Notes series AN2013/05, Reserve Bank of New Zealand.
    17. Korobilis, Dimitris & Gilmartin, Michelle, 2010. "The dynamic effects of U.S. monetary policy on state unemployment," MPRA Paper 27596, University Library of Munich, Germany.
    18. Sarah Drought & Chris McDonald, 2011. "Forecasting house price inflation: a model combination approach," Reserve Bank of New Zealand Discussion Paper Series DP2011/07, Reserve Bank of New Zealand.
    19. Boris B. Demeshev & Oxana A. Malakhovskaya, 2015. "Forecasting Russian Macroeconomic Indicators with BVAR," HSE Working papers WP BRP 105/EC/2015, National Research University Higher School of Economics.
    20. Güneş Kamber & Chris McDonald & Gael Price, 2013. "Drying out: Investigating the economic effects of drought in New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2013/02, Reserve Bank of New Zealand.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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