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The use of statistical forecasting models at the Reserve Bank of New Zealand

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  • Chris Bloor

    (Reserve Bank of New Zealand)

Abstract

Economic forecasts, in particular the forecasts for inflation, are an important part of the monetary policy formulation process at the Reserve Bank. The forecasts from a range of statistical models provide an important cross check for the forecasts produced by the main policy model that supports the policy deliberation process. This article describes the suite of statistical models used at the Reserve Bank and how these models fit into the forecasting process.

Suggested Citation

  • Chris Bloor, 2009. "The use of statistical forecasting models at the Reserve Bank of New Zealand," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 21-26, June.
    • Handle: RePEc:nzb:nzbbul:june2009:3
    as

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    File URL: http://www.rbnz.govt.nz/-/media/ReserveBank/Files/Publications/Bulletins/2009/2009jun72-2bloor.pdf
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    References listed on IDEAS

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    1. Hilde C. Bjørnland & Karsten Gerdrup & Anne Sofie Jore & Christie Smith & Leif Anders Thorsrud, 2012. "Does Forecast Combination Improve Norges Bank Inflation Forecasts?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(2), pages 163-179, April.
    2. 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.
    3. Kapetanios, George & Labhard, Vincent & Price, Simon, 2008. "Forecast combination and the Bank of England's suite of statistical forecasting models," Economic Modelling, Elsevier, vol. 25(4), pages 772-792, July.
    4. Kirdan Lees, 2009. "Overview of a recent Reserve Bank workshop: nowcasting with model combination," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 31-33, March.
    5. Kirdan Lees, 2009. "Introducing KITT: The Reserve Bank of New Zealand new DSGE model for forecasting and policy design," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 5-20, June.
    6. Domenico Giannone & Troy D. Matheson, 2007. "A New Core Inflation Indicator for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 145-180, December.
    7. Rachel Holden, 2006. "Measuring core inflation," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 69, pages 1-7, December.
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    Cited by:

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    2. Frantisek Brazdik & Michal Franta, 2017. "A BVAR Model for Forecasting of Czech Inflation," Working Papers 2017/7, Czech National Bank.
    3. Öğünç, Fethi & Akdoğan, Kurmaş & Başer, Selen & Chadwick, Meltem Gülenay & Ertuğ, Dilara & Hülagü, Timur & Kösem, Sevim & Özmen, Mustafa Utku & Tekatlı, Necati, 2013. "Short-term inflation forecasting models for Turkey and a forecast combination analysis," Economic Modelling, Elsevier, vol. 33(C), pages 312-325.
    4. Leo Krippner & Leif Anders Thorsrud, 2009. "Forecasting New Zealand's economic growth using yield curve information," Reserve Bank of New Zealand Discussion Paper Series DP2009/18, Reserve Bank of New Zealand.
    5. Richardson, Adam & van Florenstein Mulder, Thomas & Vehbi, Tuğrul, 2021. "Nowcasting GDP using machine-learning algorithms: A real-time assessment," International Journal of Forecasting, Elsevier, vol. 37(2), pages 941-948.
    6. Chris McDonald & Leif Anders Thorsrud, 2011. "Evaluating density forecasts: model combination strategies versus the RBNZ," Reserve Bank of New Zealand Discussion Paper Series DP2011/03, Reserve Bank of New Zealand.

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