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

Author

Listed:
  • Anthony Garratt
  • Kevin Lee
  • M Hashem Peseran
  • Yongcheol Shin

Abstract

This paper argues that probability forecasts convey information on the uncertainties that surround macro-economic 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 macro- econometric model, are presented. We 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.

Suggested Citation

  • Anthony Garratt & Kevin Lee & M Hashem Peseran & Yongcheol Shin, 2000. "Forecast Uncertainties in Macroeconometric Models: An Application to the UK Economy," Discussion Papers in Economics 00/4, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:00/4
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    File URL: https://www.le.ac.uk/economics/research/RePEc/lec/leecon/econ00-4.pdf
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    Cited by:

    1. Mónica Borunda & Katya Rodríguez-Vázquez & Raul Garduno-Ramirez & Javier de la Cruz-Soto & Javier Antunez-Estrada & Oscar A. Jaramillo, 2020. "Long-Term Estimation of Wind Power by Probabilistic Forecast Using Genetic Programming," Energies, MDPI, vol. 13(8), pages 1-24, April.
    2. Ron Bird & Richard Gerlach, 2006. "A Bayesian Model Averaging Approach to Enhance Value Investment," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 5(2), pages 111-127, August.
    3. Tursoy, Turgut, 2018. "Risk management process in banking industry," MPRA Paper 86427, University Library of Munich, Germany.

    More about this item

    Keywords

    Probability Forecasting; Long Run Structural VARs; Macroeconomic Modelling; Probability Forecasts of Inflation; Interest Rates and Output Growth;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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