Episode Details

Leniency programs are supposed to destabilize cartels by rewarding the first participant who comes forward. But that creates an intriguing game-theory puzzle.

If every cartel member knows that someone else could confess first, everyone has an incentive to move sooner. Backward induction seems to lead to an extreme prediction: confess immediately—and, therefore, never form the cartel.

Reality is different. Cartels still form.

This episode examines why. We distinguish cartel detection from deterrence, explain why successfully deterred cartels are largely invisible in the data, and connect leniency to the same problem explored in Episode 4: cartel members have to trust partners who have incentives to betray them.

Then we introduce AI. A profit-maximizing AI could consider competing, colluding, cheating, and seeking leniency as alternative strategies. And unlike a human executive, it has no inherent loyalty to its cartel partners.

Could AI make cartels more effective—or make the race to betray them even faster?

Read the full article and graphic analysis: https://blog.econworks.com/p/cartels-episode-5-the-race-to-confess?r=562wri

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