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

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Author Info
Garrat, A.
Lee, K.
Pesaran, M.H.
Shin, Y.

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Abstract

This paper argues that probability forecasts convey information on the uncertainties that surround macroeconomic forecasts in a manner which is straightforward and which is preferable to other alternatives, including the use of confidence intervals. Probability forecasts relating to UK output growth and inflation, obtained using a small macroeconometric model, are presented. The authors discuss in detail the probability that inflation will fall within the Bank of England's target range and that recession will be avoided, both as separate single events and jointly. The probability forecasts are also used to provide insights on the interrelatedness of output growth and inflation outcomes at different horizons.

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Publisher Info
Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0004.

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Date of creation: May 2000
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Handle: RePEc:cam:camdae:0004

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Related research
Keywords: Probability forecasting; Long-run structural VARs; Macroeconometric modelling; Probability forecasts of inflation; Interest rates and output growth;

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. 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. [Downloadable!] (restricted)
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  2. A. Robert Nobay & David A. Peel, 1998. "Optimal Monetary Policy in a Model of Asymmetric Central Bank Preferences," FMG Discussion Papers dp306, Financial Markets Group. [Downloadable!] (restricted)
  3. Jeremy Berkowitz, 1999. "Evaluating the forecasts of risk models," Finance and Economics Discussion Series 1999-11, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  4. 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. [Downloadable!] (restricted)
    Other versions:
  5. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," NBER Technical Working Papers 0215, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  6. repec:att:wimass:199417 is not listed on IDEAS
  7. Pesaran,H.M. & Shin,Y., 1995. "Long-Run Structural Modelling," Cambridge Working Papers in Economics 9419, Faculty of Economics, University of Cambridge.
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  8. 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. [Downloadable!] (restricted)
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  9. C. W.J. Granger & M. Hashem Pesaran, 1996. "A Decision Theoretic Approach to Forecast Evaluation," University of California at San Diego, Economics Working Paper Series 96-23, Department of Economics, UC San Diego.
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  10. Ray C. Fair, 1991. "Estimating Event Probabilities from Macroeconomic Models Using Stochastic Simulation," NBER Technical Working Papers 0111, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March. [Downloadable!] (restricted)
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  12. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November. [Downloadable!] (restricted)
  13. Granger, C.W.J. & Pesaran, M. H., 1999. "Economic and Statistical Measures of Forecast Accuracy," Cambridge Working Papers in Economics 9910, Faculty of Economics, University of Cambridge. [Downloadable!]
  14. A Garratt & K Lee & M H Pesaran & Yongcheol Shin, 1999. "A structural cointegrating VAR approach to macroeconometric modelling," ESE Discussion Papers 8, Edinburgh School of Economics, University of Edinburgh. [Downloadable!]
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  15. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September. [Downloadable!] (restricted)
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