Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/146005
Authors: 
Döhrn, Roland
Year of Publication: 
2014
Citation: 
[Journal:] Wirtschaftsdienst [ISSN:] 1613-978X [Publisher:] Springer [Place:] Heidelberg [Volume:] 94 [Year:] 2014 [Issue:] 7 [Pages:] 487-491
Abstract: 
Konjunkturprognosen werden sinnvollerweise auf der Grundlage saisonbereinigter Daten erstellt, damit jahreszeitlich übliche Schwankungen ausgeschaltet werden. Kommt es aber zu extremen Witterungslagen, wenn etwa ein Winter besonders heftig oder aber auch besonders mild ausfällt, dann spiegeln die saisonbereinigten Daten nicht mehr den üblichen Verlauf wider. Der Konjunkturanalytiker kann dann nicht erkennen, ob eine Veränderung konjunktur- oder witterungsbedingt war.
Abstract (Translated): 
Certainly, economic activity is influenced by weather conditions. In short term economic forecast, normal weather fluctuations over the year are covered by using seasonally adjusted figures. However, they are calculated by time series methods and do not take into account specific weather conditions such as unusually mild or cold winters. In particular in the first quarter of a year, it is often difficult to identify whether short term shifts in economic activity are due to cyclical reasons ore merely reflect specific weather conditions. The paper shows that this uncertainty leads to biased forecast. After mild winters forecasts of GDP and investment in construction tend to be over optimistic whereas they are too pessimistic after atypically cold winters.
JEL: 
C53
E37
E66
Persistent Identifier of the first edition: 
Document Type: 
Article

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