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The Swedish Inflation Fan Charts: An Evaluation of the Riksbank?s Inflation Density Forecasts

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Abstract

This paper evaluates the inflation density forecasts published by the Swedish central bank, the Sveriges Riksbank. Realized inflation outcomes are mapped to their forecasted percentiles, which are then transformed to be standard normal under the null that the forecasting model is good. Results suggest that the Riksbank?s inflation density forecasts have a skewness problem, and their longer term forecasts have a kurtosis problem as well.

Suggested Citation

  • 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.
    • Handle: RePEc:nub:occpap:10
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    1. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
    2. Michael P. Clements, 2004. "Evaluating the Bank of England Density Forecasts of Inflation," Economic Journal, Royal Economic Society, vol. 114(498), pages 844-866, October.
    3. Wallis, Kenneth F., 2003. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," International Journal of Forecasting, Elsevier, vol. 19(2), pages 165-175.
    4. 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.
    5. 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.
    6. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Alquier Pierre & Li Xiaoyin & Wintenberger Olivier, 2014. "Prediction of time series by statistical learning: general losses and fast rates," Dependence Modeling, De Gruyter, vol. 1(2013), pages 65-93, January.
    2. Karolina Tura-Gawron, 2016. "What Is The Central Bank Effectively Targeting In Practice? Svensson’S Concept Of Inflation Forecast Targeting And Measures Of Inflation Projections-The Experiences Of Selected European Countries," GUT FME Working Paper Series A 38, Faculty of Management and Economics, Gdansk University of Technology, revised Jul 2016.
    3. Karolina Tura-Gawron, 2016. "Credibility Of Central Banks Inflation Forecasts," GUT FME Working Paper Series A 37, Faculty of Management and Economics, Gdansk University of Technology.
    4. Tura-Gawron, Karolina, 2019. "Consumers’ approach to the credibility of the inflation forecasts published by central banks: A new methodological solution," Journal of Macroeconomics, Elsevier, vol. 62(C).

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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