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How accurate are the Swedish forecasters on GDB-Growth, CPI-inflation and unemployment? (1993 - 2001)

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  • Bharat Barot

Abstract

This study evaluates the performance of the eight most important Swedish domestic forecasters of real GDP-growth, CPI-inflation and unemployment for the sample period 1993-2001. The evaluation is based on the following measures: mean absolute error, the root mean square error, bias and finally directional accuracy. The forecasts are even compared to naive random walk and random walk with drift models. The results indicate that the current forecasts compared to the year ahead forecasts decline over the forecasting horizons as more information becomes available. The results with respect to the directional accuracy indicate that we are equally good/bad in predicting the directional accuracy for all three macro aggregates. According to the comparisons with the naive random walk model six out of seven Swedish CPI-inflation forecasters were outperformed by the naive random walk model. Tests of bias indicate that the Swedish forecasters underestimate GDP-growth and overestimate CPI-inflation and the unemployment rate for the sample period. All the Swedish forecasters have been successful in predicting the downward trend in CPI-inflation and the unemployment rate. The performance of the Swedish domestic forecasters is better using preliminary GDP-growth outcomes than final. The performance for the current year forecasts is better than the year ahead forecasts for all three macro economic variables. Revisions are positively biased.

Suggested Citation

  • Bharat Barot, 2004. "How accurate are the Swedish forecasters on GDB-Growth, CPI-inflation and unemployment? (1993 - 2001)," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 47(2), pages 249-278.
  • Handle: RePEc:bxr:bxrceb:y:2004:v:47:i:2:p:249-278
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    References listed on IDEAS

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    1. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, "undated". "Evaluating Density Forecasts," CARESS Working Papres 97-18, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
    2. Clements, Michael P. & Hendry, David F., 1997. "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, Elsevier, vol. 13(3), pages 341-355, September.
    3. Francis X. Diebold & Anthony S. Tay & Kenneth F. Wallis, 1997. "Evaluating Density Forecasts of Inflation: The Survey of Professional Forecasters," NBER Working Papers 6228, National Bureau of Economic Research, Inc.
    4. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    5. Christina D. Romer & David H. Romer, 1996. "Federal Reserve Private Information and the Behavior of Interest Rates," NBER Working Papers 5692, National Bureau of Economic Research, Inc.
    6. N/A, 1969. "How Well Does the National Institute Forecast ?," National Institute Economic Review, National Institute of Economic and Social Research, vol. 50(1), pages 40-52, November.
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    More about this item

    Keywords

    Mean absolute error; root mean square error; directional accuracy; bias; revisions; final respective preliminary outcomes; Theil index; naïve forecasts;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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