How communication makes the difference between a cartel and tacit collusion: A machine learning approach

被引:2
|
作者
Andres, Maximilian [1 ]
Bruttel, Lisa [1 ]
Friedrichsen, Jana [2 ,3 ,4 ,5 ]
机构
[1] Univ Potsdam, Potsdam, Germany
[2] Christian Albrechts Univ Kiel, Kiel, Germany
[3] Humboldt Univ, Berlin, Germany
[4] WZB Berlin Social Sci Ctr, Berlin, Germany
[5] DIW Berlin, Berlin, Germany
关键词
Cartel; Collusion; Communication; Machine learning; Experiment; CONSPIRACIES; POLICIES; TEXT;
D O I
10.1016/j.euroecorev.2022.104331
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely to use indirect messages when sanctioning institutions are present. This effect of sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach and sustain without an explicit agreement. Indirect messages have no, or even a negative, effect on prices.
引用
收藏
页数:18
相关论文
共 50 条