Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/201837
Authors: 
Engelke, Carola
Heinisch, Katja
Schult, Christoph
Year of Publication: 
2019
Series/Report no.: 
IWH Discussion Papers No. 18/2019
Abstract: 
This paper examines the extent to which errors in economic forecasts are driven by initial assumptions that prove to be incorrect ex post. Therefore, we construct a new data set comprising an unbalanced panel of annual forecasts from different institutions forecasting German GDP and the underlying assumptions. We explicitly control for different forecast horizons to proxy the information available at the release date. Over 75% of squared errors of the GDP forecast comove with the squared errors in their underlying assumptions. The root mean squared forecast error for GDP in our regression sample of 1.52% could be reduced to 1.13% by setting all assumption errors to zero. This implies that the accuracy of the assumptions is of great importance and that forecasters should reveal the framework of their assumptions in order to obtain useful policy recommendations based on economic forecasts.
Subjects: 
forecasts
accuracy
forecast errors
external assumptions
forecast efficiency
forecast horizon
JEL: 
C53
E02
E32
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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