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Nowcasting German GDP: Foreign factors, financial markets, and model averaging

Author

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  • Andreini, Paolo
  • Hasenzagl, Thomas
  • Reichlin, Lucrezia
  • Senftleben-König, Charlotte
  • Strohsal, Till

Abstract

This paper develops a nowcasting model for the German economy. The model outperforms a number of alternatives and produces forecasts not only for GDP but also for other key variables. We show that the inclusion of a foreign factor improves the model’s performance, while financial variables do not. Additionally, a comprehensive model averaging exercise reveals that factor extraction in a single model delivers slightly better results than averaging across models. Finally, we estimate a “news” index for the German economy in order to assess the overall performance of the model beyond forecast errors in GDP. The index is constructed as a weighted average of the nowcast errors related to each variable included in the model.

Suggested Citation

  • Andreini, Paolo & Hasenzagl, Thomas & Reichlin, Lucrezia & Senftleben-König, Charlotte & Strohsal, Till, 2023. "Nowcasting German GDP: Foreign factors, financial markets, and model averaging," International Journal of Forecasting, Elsevier, vol. 39(1), pages 298-313.
    • Handle: RePEc:eee:intfor:v:39:y:2023:i:1:p:298-313
    DOI: 10.1016/j.ijforecast.2021.11.009
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    References listed on IDEAS

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    3. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).

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