• Medientyp: E-Artikel
  • Titel: Testing Investment Forecast Efficiency with Forecasting Narratives
  • Beteiligte: Foltas, Alexander
  • Erschienen: Walter de Gruyter GmbH, 2022
  • Erschienen in: Jahrbücher für Nationalökonomie und Statistik
  • Sprache: Englisch
  • DOI: 10.1515/jbnst-2020-0027
  • ISSN: 0021-4027; 2366-049X
  • Schlagwörter: Economics and Econometrics ; Social Sciences (miscellaneous) ; General Business, Management and Accounting
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  • Beschreibung: <jats:title>Abstract</jats:title> <jats:p>I analyze the narratives that accompany business cycle forecasting reports of three German institutes using topic models. To this end, I gather multiple similar topics into different economic subject categories, allowing me to map shifting prioritizations within and between these subjects. Subsequently, I examine whether forecasting narratives contain additional information not captured by traditional indicators and include them in a random forest-based investment-forecast efficiency analysis. I find multiple correlations between narratives and forecast errors and conclude that forecasters inefficiently incorporate qualitative information in these cases. I raise the idea that further investigations with more precise identification of forecasting narratives could improve qualitative information processing or lead to scientific guidelines for forecast adjustments.</jats:p>