A related idea in non-punishment of “wrong” reports that have insufficient support (again in the common-prior/private-info setting) comes from this paper [pdf] (presented at the same conference), which suggests collecting reports from all agents and assigning rewards/punishments by assuming that agents’ reports represent their private signal, computing their posterior, and scoring this assumed posterior. Under the model assumptions, this makes it an optimal strategy for agents to truly reveal their private signal to the mechanism, while allowing the mechanism to collect non-cascaded base data to make a decision.
In general, I feel like the academic literature on market design / mechanism design has a lot to say about questions of this flavor.
A related idea in non-punishment of “wrong” reports that have insufficient support (again in the common-prior/private-info setting) comes from this paper [pdf] (presented at the same conference), which suggests collecting reports from all agents and assigning rewards/punishments by assuming that agents’ reports represent their private signal, computing their posterior, and scoring this assumed posterior. Under the model assumptions, this makes it an optimal strategy for agents to truly reveal their private signal to the mechanism, while allowing the mechanism to collect non-cascaded base data to make a decision.
In general, I feel like the academic literature on market design / mechanism design has a lot to say about questions of this flavor.