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Forecasting the Icelandic business cycle using vector autoregressive models

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  • Bruno Eklund
Abstract
This paper considers the modelling and forecasting of the Icelandic business cycle. The method of selecting monthly variables, coincident and leading, that mimic the cyclical behavior of the quarterly GDP is described. The general business cycle is then modelled by a vector autoregressive, VAR, model. The cyclical behavior of the business cycle is summarized by a composite coincident index, which is based on the root mean squared forecast error over a pseudo out of sample. By applying a bootstrap forecasting procedure, using the estimated VAR model, point and interval forecasts of the composite coincident index are estimated.

Suggested Citation

  • Bruno Eklund, 2007. "Forecasting the Icelandic business cycle using vector autoregressive models," Economics wp36, Department of Economics, Central bank of Iceland.
    • Handle: RePEc:ice:wpaper:wp36
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    Cited by:

    1. Lebotsa Daniel Metsileng & Ntebogang Dinah Moroke & Johannes Tshepiso Tsoku, 2018. "Modelling the BRICS Exchange Rates Using the Vector Autoregressive (VAR) Model," Journal of Economics and Behavioral Studies, AMH International, vol. 10(5), pages 220-229.
    2. Fresoli, Diego & Ruiz, Esther & Pascual, Lorenzo, 2015. "Bootstrap multi-step forecasts of non-Gaussian VAR models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 834-848.

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