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On the uncertainty and risks of macroeconomic forecasts: Combining judgements with sample and model information

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  • Paulo Esteves
  • Maximiano Pinheiro

Abstract

Institutions which publish macroeconomic forecasts usually do not rely on a single econometric model to mechanically generate their forecasts. The combination of judgements with information from different models complicates the problem of characterizing the predictive densities. This paper proposes a flexible (yet parametric) approach to estimate the joint and marginal densities of macroeconomic forecasting errors, combining judgements with sample and model information. We assume that the relevant variables have a multivariate normal skewed distribution, belonging to a class of distributions recently suggested by Ferreira and Steel (2007a, 2007b). Our method is less informal than the original procedure used by the Bank of England to generate its fan charts and it does not suffer from the practical limitations of other approaches available in literature.

Suggested Citation

  • Paulo Esteves & Maximiano Pinheiro, 2008. "On the uncertainty and risks of macroeconomic forecasts: Combining judgements with sample and model information," Working Papers w200821, Banco de Portugal, Economics and Research Department.
    • Handle: RePEc:ptu:wpaper:w200821
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    References listed on IDEAS

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    1. Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007. "Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers," Journal of Econometrics, Elsevier, vol. 137(2), pages 641-673, April.
    2. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
    3. Maximiano Pinheiro, 2003. "Uncertainty And Risk Analysis Of Macroeconomic Forecasts: Fan Charts Revisited," Working Papers w200319, Banco de Portugal, Economics and Research Department.
    4. Claudia Miani & Stefano Siviero, 2010. "A non-parametric model-based approach to uncertainty and risk analysis of macroeconomic forecast," Temi di discussione (Economic working papers) 758, Bank of Italy, Economic Research and International Relations Area.
    5. Blix, Mårten & Sellin, Peter, 2000. "A Bivariate Distribution for Inflation and Output Forecasts," Working Paper Series 102, Sveriges Riksbank (Central Bank of Sweden).
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    9. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
    10. Kenneth F. Wallis, 2004. "An Assessment of Bank of England and National Institute Inflation Forecast Uncertainties," National Institute Economic Review, National Institute of Economic and Social Research, vol. 189(1), pages 64-71, July.
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    12. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
    13. Mr. Prakash Kannan & Mr. Selim A Elekdag, 2009. "Incorporating Market Information into the Construction of the Fan Chart," IMF Working Papers 2009/178, International Monetary Fund.
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    Cited by:

    1. Malte Knüppel & Guido Schultefrankenfeld, 2012. "How Informative Are Central Bank Assessments of Macroeconomic Risks?," International Journal of Central Banking, International Journal of Central Banking, vol. 8(3), pages 87-139, September.
    2. Liao, Xin & Peng, Zuoxiang & Nadarajah, Saralees, 2013. "Asymptotic expansions for moments of skew-normal extremes," Statistics & Probability Letters, Elsevier, vol. 83(5), pages 1321-1329.
    3. Michal Franta & Jozef Baruník & Roman Horváth & Katerina Smídková, 2014. "Are Bayesian Fan Charts Useful? The Effect of Zero Lower Bound and Evaluation of Financial Stability Stress Tests," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 159-188, March.
    4. Michal Franta & Jozef Barunik & Roman Horvath & Katerina Smidkova, 2011. "Are Bayesian Fan Charts Useful for Central Banks? Uncertainty, Forecasting, and Financial Stability Stress Tests," Working Papers 2011/10, Czech National Bank.
    5. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
    6. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    7. Liao, Xin & Peng, Zuoxiang & Nadarajah, Saralees & Wang, Xiaoqian, 2014. "Rates of convergence of extremes from skew-normal samples," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 40-47.

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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