Bayesian Persuasion Posterior Splitting
Split a prior into honest posterior beliefs and see how a sender can change decisions while preserving the average belief.
Free theory articleSplit a prior into honest posterior beliefs and see how a sender can change decisions while preserving the average belief.
Concept & interpretation
In Bayesian Persuasion models, a sender commits to an information structure to influence a receiver's actions. The sender cannot change the average belief, but can split the prior into a distribution of posterior beliefs.
experiment
Use the interactive module to adjust the prior probability and the chosen high and low posteriors. Observe how the weights are calculated (when Bayes plausible) and the resulting expected adoption probability. Check the interactive model here: Bayesian Persuasion Posterior Splitting.
- Change the prior good probability to observe its effect.
- Adjust the low and high posterior bounds to see the updated weights and payoffs.