Hostname: page-component-848d4c4894-2xdlg Total loading time: 0 Render date: 2024-07-05T02:12:17.068Z Has data issue: false hasContentIssue false
  • English
  • Français

The GDP fan charts: an empirical evaluation

Published online by Cambridge University Press:  26 March 2020

Kevin Dowd
Kevin Dowd*
Affiliation:
Centre for Risk and Insurance Studies, Nottingham University Business School
*
e-mail: Kevin.Dowd@Nottingham.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper evaluates the probability density forecasts reflected in the Bank of England's real GDP growth fan charts. Evaluation is carried out using tests that allow for data dependence and using two GDP growth estimates. Results suggest there are problems with the shorter horizon forecasts, but conclusions about the performance of longer-term forecasts depend to some extent on the GDP estimates used in the assessment.

Keywords

GDP forecastingdensity forecastingfan chartsC4N1
Type
Articles
Information
National Institute Economic Review , Volume 203 , January 2008 , pp. 59 - 67
Copyright
Copyright © 2008 National Institute of Economic and Social Research

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The author would like to thank two anonymous referees, Ken Wellis, and Martin Weale, for helpful feedback, and the ESRC for support under grant RES-000-27-0014. The usual caveat applies.

References

Akritidis, L. (2003), ‘Revisions to quarterly GDP growth and expenditure components’, Economic Trends, December, pp. 69–85.Google Scholar
Berkowitz, J. (2001), ‘Testing density forecasts, with applications to risk management’, Journal of Business and Economic Statistics, 19, pp. 465–74.CrossRefGoogle Scholar
Castle, J. and Ellis, C. (2002), ‘Building a real-time database for GDP(E)’, Bank of England Quarterly Bulletin, Spring, pp. 42–9.Google Scholar
Clements, M.P. (2004), ‘Evaluating the Bank of England density forecasts of inflation’, Economic Journal, 114, pp. 855–77.CrossRefGoogle Scholar
Cogley, T., Morozov, S. and Sargent, T.J. (2005), ‘Bayesian fan charts for UK inflation: forecasting and sources of uncertainty in an evolving monetary system’, Journal of Economic Dynamics and Control, 29, pp. 1893–1925CrossRefGoogle Scholar
Corradi, V. and Swanson, N.S. (2006), ‘Predictive density evaluation’, Chapter 5 in Elliott, G., Granger, C.W.J. and Timmermann, A. (eds), Handbook of Economic Forecasting, Volume I, Amsterdam, Elsevier, pp. 197–284.CrossRefGoogle Scholar
Dowd, K. (2004), ‘The inflation ‘fan charts’: an evaluation’, Greek Economic Review, 23, pp. 99–111.Google Scholar
Dowd, K. (2007a), ‘Too good to be true? The (in)credibility of the UK inflation fan charts’, Journal of Macroeconomics, 29, pp. 91–102. (a)CrossRefGoogle Scholar
Dowd, K. (2007b), ‘Validating multiple-period density forecasting models’, Journal of Forecasting, 26, pp. 251–70.CrossRefGoogle Scholar
Dowd, K. (2007c), ‘Backtesting the RPIX inflation fan charts’, Journal of Risk Model Validation, 1 (3), pp. 1–19.CrossRefGoogle Scholar
Elder, R., Kapetanios, G., Taylor, T. and Yates, T. (2005), ‘Assessing the MPC's fan charts’, Bank of England Quarterly Bulletin, Autumn, pp. 326–48.Google Scholar
John, S. (1982), ‘The three-parameter two-piece normal family of distributions and its fitting’, Communications in Statistics - Theory and Methods 11, pp. 879–85.CrossRefGoogle Scholar
Tsay, R.S. (2005), Analysis of Financial Time Series, Second edition, Hoboken, NJ, Wiley.CrossRefGoogle Scholar
Wallis, K.F. (2003), ‘Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts’, International Journal of Forecasting, 19, pp. 165–75.CrossRefGoogle Scholar
Wallis, K.F. (2004), ‘An assessment of Bank of England and National Institute inflation forecast uncertainties’, National Institute Economic Review, 189, July, pp. 64–71.CrossRefGoogle Scholar