Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/184877
Year of Publication: 
2018
Series/Report no.: 
Diskussionspapier No. 180
Publisher: 
Helmut-Schmidt-Universität - Universität der Bundeswehr Hamburg, Fächergruppe Volkswirtschaftslehre, Hamburg
Abstract: 
Market delineation is a fundamental tool in modern antitrust analysis. However, the definition of relevant markets can be very difficult in practice. This preliminary draft applies a new methodology combining a simple price correlation test with hierarchical clustering -a method known from machine learning- in order to analyze the competitive situation in the German retail gasoline market. Our analysis reveals two remarkable results: At first, there is a uniform pattern across stations of the same brand regarding their maximum daily prices which confirms the claim that prices are partly set centrally. But more importantly, price reactions are also influenced by regional or local market conditions as the price setting of gasoline stations is strongly affected by commuter routes.
Subjects: 
market definition
gasoline market
price tests
competition
k-means clustering
hierarchical clustering
JEL: 
D22
D40
D43
L10
Document Type: 
Working Paper

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