Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/223420
Authors: 
Foltas, Alexander
Year of Publication: 
2020
Series/Report no.: 
Working Papers of the Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour" No. 19
Abstract: 
I use textual data to model German professional macroeconomic forecasters' information sets and use machine-learning techniques to analyze the efficiency of forecasts. To this end, I extract information from forecast reports using a combination of topic models and word embeddings. I then use this information and traditional macroeconomic predictors to study the efficiency of investment forecasts.
Subjects: 
Forecast Efficiency
Investment
Random Forest
Topic Modeling
JEL: 
C53
E27
E22
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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