Nowcasting GDP through the lens of economic states

Kris Boud (kris.boudt@ugent.be), Arno De Block (arno.de.block@vub.be), Geert Langenus (geert.langenus@nbb.be) and Peter Reusens (peter.reusens@nbb.be)
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Kris Boud: Department of Economics, Universiteit Gent, Belgium, Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel, Belgium, School of Business and Economics, Vrije Universiteit Amsterdam, The Netherlands
Arno De Block: Faculty of Social Sciences and Solvay Business School, Vrije Universiteit Brussel
Geert Langenus: Economics and Research Department, National Bank of Belgium
Peter Reusens: Economics and Research Department, National Bank of Belgium

No 445, Working Paper Research from National Bank of Belgium

Abstract: Common sense tells that historical data are more informative for the estimation of today’s nowcasting models when observed in a similar economic state as today. We operationalise this intuition by proposing a state-based weighted estimation procedure of GDP nowcasting models, in which observations are weighted based on the similarity with the current economic state. For this end, we also construct new state variables for measuring the similarity of economic time periods using news data, in addition to traditional variables. We find that the state-based weighting of observations leads to economically significant nowcasting gains for predicting GDP growth in Belgium as compared to traditional unweighted approaches.

Keywords: GDP growth; Media news; Nowcasting; Sentometrics; State variables (search for similar items in EconPapers)
JEL-codes: C32 C51 C53 C55 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2023-12
New Economics Papers: this item is included in nep-eur
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Persistent link: https://EconPapers.repec.org/RePEc:nbb:reswpp:202312-445

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