Abstract:  We study optimal mechanism design in settings where a designer has private information and interacts repeatedly with strategic agents. Motivated by applications like ad auctions, we introduce calibrated mechanism design, in which mechanisms must be robust to the information agents learn over time through participation. We formalize this via calibrated information structures, capturing what…