Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/285380 
Authors: 
Year of Publication: 
2024
Series/Report no.: 
Hohenheim Discussion Papers in Business, Economics and Social Sciences No. 01-2024
Publisher: 
Universität Hohenheim, Fakultät Wirtschafts- und Sozialwissenschaften, Stuttgart
Abstract: 
The paper uses a machine learning technique to build up a screen for collusive behavior. Such tools can be applied by competition authorities but also by companies to screen the behavior of their suppliers. The method is applied to the German retail gasoline market to detect anomalous behavior in the price setting of the filling stations. Therefore, the algorithm identifies anomalies in the data-generating process. The results show that various anomalies can be detected with this method. These anomalies in the price setting behavior are then discussed with respect to their implications for the competitiveness of the market.
Subjects: 
Machine Learning
Cartel Screens
Fuel Retail Market
JEL: 
C53
K21
L44
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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