IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v42y2012i3p639-665.html
   My bibliography  Save this article

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

Author

Listed:
  • Maximiano Pinheiro

  • Paulo Esteves

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Maximiano Pinheiro & Paulo Esteves, 2012. "On the uncertainty and risks of macroeconomic forecasts: combining judgements with sample and model information," Empirical Economics, Springer, vol. 42(3), pages 639-665, June.
    • Handle: RePEc:spr:empeco:v:42:y:2012:i:3:p:639-665
    DOI: 10.1007/s00181-010-0447-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-010-0447-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00181-010-0447-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    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. repec:sae:niesru:v:167:y::i:1:p:106-112 is not listed on IDEAS
    3. 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.
    4. Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).
    5. 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.
    6. 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.
    7. Maximiano Pinheiro, 2003. "Uncertainty And Risk Analysis Of Macroeconomic Forecasts: Fan Charts Revisited," Working Papers w200319, Banco de Portugal, Economics and Research Department.
    8. Calzolari, Giorgio & Panattoni, Lorenzo, 1990. "Mode predictors in nonlinear systems with identities," International Journal of Forecasting, Elsevier, vol. 6(3), pages 317-326, October.
    9. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
    10. 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.
    11. Blix, Mårten & Sellin, Peter, 2000. "A Bivariate Distribution for Inflation and Output Forecasts," Working Paper Series 102, Sveriges Riksbank (Central Bank of Sweden).
    12. 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.
    13. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    14. Kenneth F. Wallis, 1999. "Asymmetric density forecasts of inflation and the Bank of England's fan chart," National Institute Economic Review, National Institute of Economic and Social Research, vol. 167(1), pages 106-112, January.
    15. Knüppel, Malte & Tödter, Karl-Heinz, 2007. "Quantifying risk and uncertainty in macroeconomic forecasts," Discussion Paper Series 1: Economic Studies 2007,25, Deutsche Bundesbank.
    16. Adelchi Azzalini & Antonella Capitanio, 2003. "Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t‐distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 367-389, May.
    17. Kenneth F. Wallis, 1999. "Asymmetric density forecasts of inflation and the Bank of England's fan chart," National Institute Economic Review, National Institute of Economic and Social Research, vol. 167(1), pages 106-112, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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, Research and Statistics Department.
    2. Busetti, Fabio & Caivano, Michele & Delle Monache, Davide & Pacella, Claudia, 2021. "The time-varying risk of Italian GDP," Economic Modelling, Elsevier, vol. 101(C).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Knüppel, Malte & Schultefrankenfeld, Guido, 2019. "Assessing the uncertainty in central banks’ inflation outlooks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1748-1769.
    2. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    3. Goodhart, C. A. E. & Pradhan, Manoj, 2023. "A snapshot of Central Bank (two year) forecasting: a mixed picture," LSE Research Online Documents on Economics 118680, London School of Economics and Political Science, LSE Library.
    4. Hua, Zhongsheng & Zhang, Bin, 2008. "Improving density forecast by modeling asymmetric features: An application to S&P500 returns," European Journal of Operational Research, Elsevier, vol. 185(2), pages 716-725, March.
    5. Dowd, Kevin, 2007. "Too good to be true? The (In)credibility of the UK inflation fan charts," Journal of Macroeconomics, Elsevier, vol. 29(1), pages 91-102, March.
    6. Goodhart Charles A.E., 2005. "The Monetary Policy Committee's Reaction Function: An Exercise in Estimation," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-42, August.
    7. Knüppel, Malte & Schultefrankenfeld, Guido, 2008. "How informative are macroeconomic risk forecasts? An examination of the Bank of England's inflation forecasts," Discussion Paper Series 1: Economic Studies 2008,14, Deutsche Bundesbank.
    8. Panagiotelis, Anastasios & Smith, Michael, 2010. "Bayesian skew selection for multivariate models," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1824-1839, July.
    9. Ali Al‐Nowaihi & Livio Stracca, 2003. "Behavioural Central Bank Loss Functions, Skewed Risks and Certainty Equivalence," Manchester School, University of Manchester, vol. 71(s1), pages 21-38, September.
    10. James Mitchell & Martin Weale, 2023. "Censored density forecasts: Production and evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 714-734, August.
    11. Dong Jin Lee, 2009. "Testing Parameter Stability in Quantile Models: An Application to the U.S. Inflation Process," Working papers 2009-26, University of Connecticut, Department of Economics.
    12. Seohyun Lee, 2025. "Measuring Interdependence of Inflation Uncertainty," Computational Economics, Springer;Society for Computational Economics, vol. 65(5), pages 2707-2741, May.
    13. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    14. Maximiano Pinheiro, 2012. "Marginal Distributions of Random Vectors Generated by Affine Transformations of Independent Two-Piece Normal Variables," Journal of Probability and Statistics, Hindawi, vol. 2012, pages 1-10, April.
    15. 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.
    16. Schultefrankenfeld Guido, 2013. "Forecast uncertainty and the Bank of England’s interest rate decisions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 1-20, February.
    17. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2024. "From Fixed‐Event to Fixed‐Horizon Density Forecasts: Obtaining Measures of Multihorizon Uncertainty from Survey Density Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(7), pages 1675-1704, October.
    18. Rossi, Barbara & Ganics, Gergely & Sekhposyan, Tatevik, 2020. "From Fixed-event to Fixed-horizon Density Forecasts: Obtaining Measures of Multi-horizon Uncertainty from Survey Density Foreca," CEPR Discussion Papers 14267, C.E.P.R. Discussion Papers.
    19. Lee, Seohyun, 2017. "Three essays on uncertainty: real and financial effects of uncertainty shocks," MPRA Paper 83617, University Library of Munich, Germany.
    20. Kevin Dowd, 2004. "The Swedish Inflation Fan Charts: An Evaluation of the Riksbank?s Inflation Density Forecasts," Occasional Papers 10, Industrial Economics Division, revised 11 Jan 2004.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:42:y:2012:i:3:p:639-665. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.