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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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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
Date of revision:
Handle: RePEc:edn:esedps:64
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  1. 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 355-78, June.
  2. Carmen Fernandez & Eduardo Ley & Mark F J Steel, 1998. "Benchmark priors for Bayesian model averaging," ESE Discussion Papers 66, Edinburgh School of Economics, University of Edinburgh.
  3. Anthony Garratt & Kevin Lee & Mohammad Hashem Pesaran & Yongcheol Shin, 1998. "A structural cointegrating VAR approach to macroeconometric modelling," ESE Discussion Papers 8, Edinburgh School of Economics, University of Edinburgh.
  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. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
  6. repec:sae:niesru:v:156:y::i:1:p:72-79 is not listed on IDEAS
  7. Garratt, A. & Lee, K. & Pesaran, M. H. & Shin, Y., 1998. "A Long-run Structural Macro-econometric Model of the UK," Cambridge Working Papers in Economics 9812, Faculty of Economics, University of Cambridge.
  8. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  9. Mohammad Hashem Pesaran & Richard J Smith & Yongcheol Shin, 1999. "Structural analysis of vector error correction models with exogenous I(1) variables," ESE Discussion Papers 38, Edinburgh School of Economics, University of Edinburgh.
  10. repec:sae:niesru:v:156:y::i:1:p:55-62 is not listed on IDEAS
  11. 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 388-99, October.
  12. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
  13. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
  14. 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.
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