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

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.

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File URL: http://www.econ.ed.ac.uk/papers/id64_esedps.pdf
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Paper provided by Edinburgh School of Economics, University of Edinburgh in its series ESE Discussion Papers with number 64.

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Length: 39
Date of creation: Dec 2001
Handle: RePEc:edn:esedps:64
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  1. 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, 04.
  2. Pesaran, M. Hashem & Shin, Yongcheol & Smith, Richard J., 2000. "Structural analysis of vector error correction models with exogenous I(1) variables," Journal of Econometrics, Elsevier, vol. 97(2), pages 293-343, August.
  3. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
  4. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
  5. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
  6. 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.
  7. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
  8. Harbo, Ingrid, et al, 1998. "Asymptotic Inference on Cointegrating Rank in Partial Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 388-399, October.
  9. repec:sae:niesru:v:156:y::i:1:p:55-62 is not listed on IDEAS
  10. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
  11. repec:sae:niesru:v:156:y::i:1:p:72-79 is not listed on IDEAS
  12. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  13. Nobay, A. R. & Peel, D. A., 2000. "Optimal monetary policy with a nonlinear Phillips curve," Economics Letters, Elsevier, vol. 67(2), pages 159-164, May.
  14. Garratt, Anthony & Lee, Kevin C & Pesaran, M. Hashem & Shin, Yongcheol, 1998. "A Structural Cointegrating VAR Approach to Macroeconometric Modelling," Cambridge Working Papers in Economics 9823, Faculty of Economics, University of Cambridge.
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