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Nowcasting German GDP

Author

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  • Andreini, Paolo
  • Charlotte Senftleben-König, Charlotte
  • Hasenzagl, Thomas
  • Reichlin, Lucrezia
  • 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 foreign variables 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 constructed as a weighted average of the nowcast errors related to each variable included in the model.

Suggested Citation

  • Andreini, Paolo & Charlotte Senftleben-König, Charlotte & Hasenzagl, Thomas & Reichlin, Lucrezia & Strohsal, Till, 2020. "Nowcasting German GDP," CEPR Discussion Papers 14323, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:14323
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
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    6. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
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    14. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    15. Daniela Bragoli & Luca Metelli & Michele Modugno, 2015. "The importance of updating: Evidence from a Brazilian nowcasting model," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2015(1), pages 5-22.
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    17. repec:hal:journl:peer-00844811 is not listed on IDEAS
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    2. Rubio-Domingo, G. & Linares, P., 2021. "The future investment costs of offshore wind: An estimation based on auction results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    3. Keßler, Daniela & Zerres, Thomas, 2020. "Rechtsrahmen der Geldwäschebekämpfung," Working Papers for Marketing & Management 48, Offenburg University, Department of Media and Information.
    4. Wyrwich, Michael & Steinberg, Philip J. & Noseleit, Florian & de Faria, Pedro, 2022. "Is open innovation imprinted on new ventures? The cooperation-inhibiting legacy of authoritarian regimes," Research Policy, Elsevier, vol. 51(1).
    5. Konstantin Kuck & Karsten Schweikert, 2021. "Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 861-882, August.
    6. Schulhof, Vera & van Vuuren, Detlef & Kirchherr, Julian, 2022. "The Belt and Road Initiative (BRI): What Will it Look Like in the Future?," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

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