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A simple method for joint evaluation of skill in directional forecasts of multiple variables

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  • Thitithep Sitthiyot
  • Kanyarat Holasut

Abstract

Forecasts for key macroeconomic variables are almost always made simultaneously by the same organizations, presented together, and used together in policy analyses and decision-makings. It is therefore important to know whether the forecasters are skillful enough to forecast the future values of those variables. Here a method for joint evaluation of skill in directional forecasts of multiple variables is introduced. The method is simple to use and does not rely on complicated assumptions required by the conventional statistical methods for measuring accuracy of directional forecast. The data on GDP growth and inflation forecasts of three organizations from Thailand, namely, the Bank of Thailand, the Fiscal Policy Office, and the Office of the National Economic and Social Development Council as well as the actual data on GDP growth and inflation of Thailand between 2001 and 2021 are employed in order to demonstrate how the method could be used to evaluate the skills of forecasters in practice. The overall results indicate that these three organizations are somewhat skillful in forecasting the direction-of-changes of GDP growth and inflation when no band and a band of +/- 1 standard deviation of the forecasted outcome are considered. However, when a band of +/- 0.5% of the forecasted outcome is introduced, the skills in forecasting the direction-of-changes of GDP growth and inflation of these three organizations are, at best, little better than intelligent guess work.

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  • Thitithep Sitthiyot & Kanyarat Holasut, 2024. "A simple method for joint evaluation of skill in directional forecasts of multiple variables," Papers 2402.01142, arXiv.org.
  • Handle: RePEc:arx:papers:2402.01142
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    References listed on IDEAS

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    1. Tara Sinclair & H. O. Stekler & L. Kitzinger, 2010. "Directional forecasts of GDP and inflation: a joint evaluation with an application to Federal Reserve predictions," Applied Economics, Taylor & Francis Journals, vol. 42(18), pages 2289-2297.
    2. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    3. William Briggs & David Ruppert, 2005. "Assessing the Skill of Yes/No Predictions," Biometrics, The International Biometric Society, vol. 61(3), pages 799-807, September.
    4. Thitithep Sitthiyot & Kanyarat Holasut, 2022. "On the Evaluation of Skill in Binary Forecast," Papers 2209.04686, arXiv.org.
    5. Thitithep Sitthiyot & Kanyarat Holasut, 2020. "A simple method for measuring inequality," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
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