TY  - JOUR
A1  - Andres, Maximilian
A1  - Bruttel, Lisa
A1  - Friedrichsen, Jana
T1  - How communication makes the difference between a cartel and tacit collusion
BT  - a machine learning approach
JF  - European economic review
N2  - 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.
KW  - cartel
KW  - collusion
KW  - communication
KW  - machine learning
KW  - experiment
Y1  - 2023
U6  - https://doi.org/10.1016/j.euroecorev.2022.104331
SN  - 0014-2921
SN  - 1873-572X
VL  - 152
SP  - 1
EP  - 18
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - RPRT
A1  - Andres, Maximilian
A1  - Bruttel, Lisa Verena
A1  - Friedrichsen, Jana
T1  - Choosing between explicit cartel formation and tacit collusion – An experiment
T2  - CEPA Discussion Papers
N2  - Numerous studies investigate which sanctioning institutions prevent cartel formation but little is known as to how these sanctions work. We contribute to understanding the inner workings of cartels by studying experimentally the effect of sanctioning institutions on firms’ communication. Using machine learning to organize the chat communication into topics, we find that firms are significantly less likely to communicate explicitly about price fixing when sanctioning institutions are present. At the same time, average prices are lower when communication is less explicit. A mediation analysis suggests that sanctions are effective in hindering cartel formation not only because they introduce a risk of being fined but also by reducing the prevalence of explicit price communication.
T3  - CEPA Discussion Papers - 19 
KW  - cartel
KW  - collusion
KW  - communication
KW  - machine learning
KW  - experiment
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-473885
SN  - 2628-653X
IS  - 19
ER  - 
TY  - RPRT
A1  - Andres, Maximilian
A1  - Bruttel, Lisa Verena
A1  - Friedrichsen, Jana
T1  - How communication makes the difference between a cartel and tacit collusion
BT  - a machine learning approach
T2  - CEPA Discussion Papers
N2  - 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.
T3  - CEPA Discussion Papers - 53 
KW  - cartel
KW  - collusion
KW  - communication
KW  - machine learning
KW  - experiment
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-562234
SN  - 2628-653X
ER  -