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Forecast Uncertainties in Macroeconomics Modelling: An Application to the UK Economy

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Abstract

This paper argues that probability forecasts convey information on the uncertainties that surround macro-economic forecast in straightforward manner which is preferable to other alternatives, including the use of confidence intervals. Point and probability forecasts obtained using a small macro-economic model are presented and evaluated using recursive forecasts generated from the model over the period 1999-2000. Out of sample probability forecasts of inflation and output growth are also provided over the period 2001-2003, and their implications discussed in relation to the Bank of England's inflation target and the need to avoid recessions, both as separate events and jointly. It is also shown how the probability forecasts can be used to provide insights on the inter-relationship of output growth and inflation at different horizons.

Suggested Citation

  • Athony Garratt & Kevin Lee & Mohammad Hashem Pesaran & Yongcheol Shin, 2001. "Forecast Uncertainties in Macroeconomics Modelling: An Application to the UK Economy," ESE Discussion Papers 64, Edinburgh School of Economics, University of Edinburgh.
  • Handle: RePEc:edn:esedps:64
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    File URL: http://www.econ.ed.ac.uk/papers/id64_esedps.pdf
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    9. Fair, Ray C, 1980. "Estimating the Expected Predictive Accuracy of Econometric Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 355-378, June.
    10. Anthony Garratt & Kevin Lee & M. Hashem Pesaran & Yongcheol Shin, 2003. "A Long run structural macroeconometric model of the UK," Economic Journal, Royal Economic Society, vol. 113(487), pages 412-455, April.
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    Citations

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    Cited by:

    1. Kevin Lee & Nilss Olekalns & Kalvinder Shields, 2008. "Nowcasting, Business Cycle Dating and the Interpretation of New Information when Real Time Data are Available," Discussion Papers in Economics 08/17, Department of Economics, University of Leicester.
    2. StevenN. Durlauf & Andros Kourtellos & ChihMing Tan, 2008. "Are Any Growth Theories Robust?," Economic Journal, Royal Economic Society, vol. 118(527), pages 329-346, March.
    3. Valentina Iafolla & Massimiliano Mazzanti & Francesco Nicolli, 2010. "Are You SURE You Want to Waste Policy Chances? Waste Generation, Landfill Diversion and Environmental Policy Effectiveness in the EU15," Working Papers 2010.77, Fondazione Eni Enrico Mattei.
    4. Andrea Bastianin & Matteo Manera & Anil Markandya & Elisa Scarpa, 2011. "Oil Price Forecast Evaluation with Flexible Loss Functions," Working Papers 2011.91, Fondazione Eni Enrico Mattei.
    5. Valentina Iafolla & Massimiliano Mazzanti & Francesco Nicolli, 2010. "Rifiuti generati, rifiuti in discarica ed efficacia delle politiche ambientali in Europa," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 0(2), pages 103-135.
    6. Vanina Forget, 2012. "Doing well and doing good: a multi-dimensional puzzle," Working Papers hal-00672037, HAL.
    7. Durmus Ozdemir & Mustafa Kemal Gündoğdu, 2012. "Structural Macro econometric Model of Turkey; Impact of Structural Characteristics on Macroeconomic Indicators," EcoMod2012 3886, EcoMod.
    8. Diks, Cees & Panchenko, Valentyn & van Dijk, Dick, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Journal of Econometrics, Elsevier, vol. 163(2), pages 215-230, August.

    More about this item

    Keywords

    probability forecasting; long run structural VARs; macroeconometric modelling; forecast evaluation; probability forecasts of inflation; output growth;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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