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Evaluation of economic forecasts for Austria

Author

Listed:
  • Ines Fortin

    (Institute for Advanced Studies (Institut für Höhere Studien, IHS))

  • Sebastian P. Koch

    (Institute for Advanced Studies (Institut für Höhere Studien, IHS))

  • Klaus Weyerstrass

    (Institute for Advanced Studies (Institut für Höhere Studien, IHS))

Abstract

In this paper, we evaluate macroeconomic forecasts for Austria and analyze the effects of external assumptions on forecast errors. We consider the growth rates of real GDP and the demand components as well as the inflation rate and the unemployment rate. The analyses are based on univariate measures like RMSE and Theil’s inequality coefficient and also on the Mahalanobis distance, a multivariate measure that takes the variances of and the correlations between the variables into account. We compare forecasts generated by the two leading Austrian economic research institutes, the Institute for Advanced Studies (IHS) and the Austrian Institute of Economic Research (WIFO), and additionally consider the forecasts produced by the European Commission. The results indicate that there are no systematic differences between the forecasts of the two Austrian institutes, neither for the traditional measures nor for the Mahalanobis distance. Generally, forecasts become more accurate with a decreasing forecast horizon, as expected; they are unbiased for forecast horizons of less than a year considering traditional measures and for the shortest forecast horizon considering the Mahalanobis distance. Finally, we find that mistakes in external assumptions, in particular regarding EU GDP and the oil price, translate into forecast errors for GDP and inflation.

Suggested Citation

  • Ines Fortin & Sebastian P. Koch & Klaus Weyerstrass, 2020. "Evaluation of economic forecasts for Austria," Empirical Economics, Springer, vol. 58(1), pages 107-137, January.
    • Handle: RePEc:spr:empeco:v:58:y:2020:i:1:d:10.1007_s00181-019-01814-1
    DOI: 10.1007/s00181-019-01814-1
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    3. Yolanda S. Stander, 2023. "The Governance and Disclosure of IFRS 9 Economic Scenarios," JRFM, MDPI, vol. 16(1), pages 1-27, January.

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    More about this item

    Keywords

    Forecast evaluation; MAE; RMSE; Theil’s U2; Mean directional accuracy; Mahalanobis distance; External assumptions; Small open economy; Austria;
    All these 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
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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