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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-economicforecast 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 insighs 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
Date of revision:
Handle: RePEc:edn:esedps:64
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  1. 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.
  2. 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.
  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. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
  5. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  6. 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.
  7. repec:sae:niesru:v:156:y::i:1:p:55-62 is not listed on IDEAS
  8. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
  9. Don Harding & Adrian Pagan, 2000. "Disecting the Cycle: A Methodological Investigation," Econometric Society World Congress 2000 Contributed Papers 1164, Econometric Society.
  10. Pesaran, M. H. & Shin, Y. & Smith, R. J., 1997. "Structural Analysis of Vector Error Correction Models with Exogenous I(1) Variables," Cambridge Working Papers in Economics 9706, Faculty of Economics, University of Cambridge.
  11. 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.
  12. 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.
  13. 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.
  14. repec:sae:niesru:v:156:y::i:1:p:72-79 is not listed on IDEAS
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