Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/225084
Authors: 
Müller, Karsten
Year of Publication: 
2020
Series/Report no.: 
Working Papers of the Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour" 23
Abstract: 
Based on German business cycle forecast reports covering 10 German institutions for the period 1993-2017, the paper analyses the information content of German forecasters' narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices.
Subjects: 
Textual analysis
Sentiment
Macroeconomic forecasting
Forecast evaluation
Germany
JEL: 
C53
E32
E37
E66
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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