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Autor:innen: 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
Working Papers of the Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour" No. 45
Verlag: 
Humboldt University Berlin, Berlin
Zusammenfassung: 
I contribute to previous research on the efficient integration of forecasters' narratives into business cycle forecasts. Using a Bidirectional Encoder Representations from Transformers (BERT) model, I quantify 19,300 paragraphs from German business cycle reports (1998-2021) and classify the signs of institutes' consumption forecast errors. The correlation is strong for 12.8% of paragraphs with a predicted class probability of 85% or higher. Reviewing 150 of such high-probability paragraphs reveals recurring narratives. Underestimations of consumption growth often mention rising employment, increasing wages and transfer payments, low inflation, decreasing taxes, crisis-related fiscal support, and reduced relevance of marginal employment. Conversely, overestimated consumption forecasts present opposing narratives. Forecasters appear to particularly underestimate these factors when they disproportionately affect low-income households.
Schlagwörter: 
Macroeconomic forecasting
Evaluating forecasts
Business cycles
Consumption forecasting
Natural language processing
Language Modeling
Machine learning
Judgemental forecasting
JEL: 
E21
C53
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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