Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/280937 
Year of Publication: 
2023
Series/Report no.: 
DICE Discussion Paper No. 410
Publisher: 
Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), Düsseldorf
Abstract: 
This paper investigates the collusive and competitive effects of algorithmic price recommendations on market outcomes. These recommendations are often non-binding and common in many markets, especially on online platforms. We develop a theoretical framework and derive two algorithms that recommend collusive pricing strategies. Utilizing a laboratory experiment, we find that sellers condition their prices on the recommendation of the algorithms. The algorithm with a soft punishment strategy lowers market prices and has a pro-competitive effect. The algorithm that recommends a subgame perfect equilibrium strategy increases the range of market outcomes, including more collusive ones. Variations in economic preferences lead to heterogeneous treatment effects and explain the results.
Subjects: 
Collusion
Experiment
Human-Machine Interaction
Bertrand Oligopoly
JEL: 
C92
D43
L13
L41
ISBN: 
978-3-86304-409-1
Document Type: 
Working Paper

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