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Assessing gross domestic product and inflation probability forecasts derived from Bank of England fan charts

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  • John W. Galbraith
  • Simon van Norden

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Suggested Citation

  • John W. Galbraith & Simon van Norden, 2012. "Assessing gross domestic product and inflation probability forecasts derived from Bank of England fan charts," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(3), pages 713-727, July.
  • Handle: RePEc:bla:jorssa:v:175:y:2012:i:3:p:713-727
    DOI: j.1467-985X.2011.01012.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-985X.2011.01012.x
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    Citations

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    Cited by:

    1. Gergely Ganics & Barbara Rossi & Tatevik Sekhposyan, 2019. "From fixed-event to fixed-horizon density forecasts: obtaining measures of multi-horizon uncertainty from survey density forecasts," Working Papers 1947, Banco de España.
    2. McDonald, Christopher & Thamotheram, Craig & Vahey, Shaun P. & Wakerly, Elizabeth C., 2015. "Assessing the Economic Value of Probabilistic Forecasts in the Presence of an Inflation Target," EMF Research Papers 09, Economic Modelling and Forecasting Group.
    3. Simon van Norden, 2015. "Estimates of Québec’s Growth Uncertainty," CIRANO Project Reports 2015rp-01, CIRANO.
    4. Carlos Díaz, 2018. "Extracting information shocks from the Bank of England inflation density forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 316-326, April.
    5. Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
    6. Elena Andreou & Andros Kourtellos, 2018. "Scoring rules for simple forecasting models: The case of Cyprus GDP and its sectors," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 12(1), pages 59-73, June.
    7. Lahiri, Kajal & Peng, Huaming & Zhao, Yongchen, 2015. "Testing the value of probability forecasts for calibrated combining," International Journal of Forecasting, Elsevier, vol. 31(1), pages 113-129.
    8. Galvao, Ana Beatriz & Mitchell, James, 2020. "Real-Time Perceptions of Historical GDP Data Uncertainty," EMF Research Papers 35, Economic Modelling and Forecasting Group.
    9. Garratt, Anthony & Mitchell, James & Vahey, Shaun P., 2014. "Probability Forecasting for Inflation Warnings from the Federal Reserve," EMF Research Papers 07, Economic Modelling and Forecasting Group.
    10. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
    11. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    12. Schreiber, Sven & Soldatenkova, Natalia, 2016. "Anticipating business-cycle turning points in real time using density forecasts from a VAR," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 166-187.
    13. Galbraith, John W. & van Norden, Simon, 2019. "Asymmetry in unemployment rate forecast errors," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1613-1626.
    14. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Too many skew normal distributions? The practitioner’s perspective," Discussion Papers in Economics 13/07, Division of Economics, School of Business, University of Leicester.

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