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DFROG: Dutch Forecasting Model for Real Time Output Growth

DFROG is a dynamic factor model used to make short-term forecasts for quarterly GDP growth in the Netherlands. 

The model uses 70 monthly series of statistical agencies (e.g. surveys, production and sales figures, labor market and housing indicators, prices), financial market indicators (e.g. interest rates, stock prices) and series measuring the sentiment in Dutch financial news (see van Dijk and de Winter, 2023) to make a forecast for the previous, current and next quarter. The forecasts are updated at least six times a year after the release of new quarterly GDP figures and at the start of the bi-annual DNB forecasts. The forecast will be made available to the public periodically. The choice for the current model is based on previous research on the optimal model type and specification. See van Dijk et al. (2024) for a technical description of the current version of DFROG (October 2024). It turns out that the dynamic factor model is a very competitive short-term forecasting method. See Jansen, Jin and de Winter (2016) for a comparison of the dynamic factor model with other popular nowcasting methods, and Jansen and de Winter (2018) for a comparison of the forecasting accuracy of the short-term forecasts of dynamic factor models versus professional analysts. See Koopman, Hindrayanto and de Winter (2016) for a recent contribution on the optimal model specification of a dynamic factor model. 

  • Dijk, van, D.W, Rooijen, van, M. and J.M. de Winter, 2024. DFROG: The nowcasting model for GDP growth of De Nederlandsche Bank, mimeo, (link). 
  • Dijk, van, D.W and J.M. de Winter, 2023. Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press, DNB Working Paper nr. 766 (link). 
  • Hindrayanto, I., Koopman, S.J. and J.M. de Winter, 2016. Forecasting and nowcasting economic growth in the euro area using factor models, International Journal of Forecasting, 32(4), 1284-1305 (link).
  • Jansen, W.J.J., Jin, X. and J.M. de Winter, 2016. Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts, International Journal of Forecasting, 32(2), 411-436 (link). 
  • Jansen, W.J.J. and J.M. de Winter, 2018. Combining ModelBased NearTerm GDP Forecasts and Judgmental Forecasts: A RealTime Exercise for the G7 Countries, Oxford Bulletin of Economics and Statistics, 80(6), 1213-1242 (link).