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Forecast Error Bounds By Stochastic Simulation

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  • Blake, Andrew P.

Abstract

What can the National Institute model tell us about the accuracy of forecasting inflation and growth? We make ‘point’ forecasts over the short to medium term, and assess the accuracy of those forecasts by examining past forecast errors (see Poulizac, Weale and Young, 1996). But the model itself can be used for the same purpose and can inform us better than historical exercises if a new policy regime has been adopted which is a major departure from past experience. In that case, the behaviour of the economy would be expected to be considerably different and so using a model which captures the structural effects of the changes may give a more accurate view of the likely behaviour of policy targets, policy instruments and other variables.

Suggested Citation

  • Blake, Andrew P., 1996. "Forecast Error Bounds By Stochastic Simulation," National Institute Economic Review, National Institute of Economic and Social Research, vol. 156, pages 72-79, May.
  • Handle: RePEc:cup:nierev:v:156:y:1996:i::p:72-79_6
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    Cited by:

    1. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
    2. Nicoletta Batini & Andrew Haldane, 1999. "Forward-Looking Rules for Monetary Policy," NBER Chapters, in: Monetary Policy Rules, pages 157-202, National Bureau of Economic Research, Inc.
    3. Hilary Metcalf, 2001. "Increasing inequality in Higher Education: the role of term-time working," National Institute of Economic and Social Research (NIESR) Discussion Papers 186, National Institute of Economic and Social Research.
    4. Gatt, William, 2014. "Communicating uncertainty - a fan chart for HICP projections," MPRA Paper 59603, University Library of Munich, Germany.
    5. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    6. Anthony Garratt & Kevin Lee & Mohammad Hashem Pesaran & Yongcheol Shin, 1998. "A structural cointegrating VAR approach to macroeconometric modelling," Edinburgh School of Economics Discussion Paper Series 8, Edinburgh School of Economics, University of Edinburgh.
    7. Garratt A. & Lee K. & Pesaran M.H. & Shin Y., 2003. "Forecast Uncertainties in Macroeconomic Modeling: An Application to the U.K. Economy," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 829-838, January.

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