"Learning Deterrence vs. Encouragement: Optimal Pricing and Return Policy", Jul 2020
Abstract: Information about a certain product is easy to acquire nowadays and the uninformed buyer can choose the optimal level of information acquisition (before-trading and post-trading) after observing the selling mechanism committed by the seller. A selling mechanism contains a selling price and a return policy that specifies the return probability and the amount of refund. Different selling mechanisms are used to induce different levels of buyer's private learning. We find that the seller's optimal selling mechanism either encourages full learning (with Free Return) or deters the buyer from private learning (with Learning Deterrence), while Stochastic Return mechanism that induces partial learning is always sub-optimal. Trading is efficient for both sufficiently optimistic and pessimistic buyer. Though the seller's expected revenue is monotone on the buyer's prior belief, the buyer's ex-ante trading surplus is non-monotone. More surprisingly, the buyer is worse off under a Free Return mechanism. When cost of learning converges to zero, the result converges to the standard niche-mass market analysis.
Abstract: Information about a certain product is easy to acquire nowadays and the uninformed buyer can choose the optimal level of information acquisition (before-trading and post-trading) after observing the selling mechanism committed by the seller. A selling mechanism contains a selling price and a return policy that specifies the return probability and the amount of refund. Different selling mechanisms are used to induce different levels of buyer's private learning. We find that the seller's optimal selling mechanism either encourages full learning (with Free Return) or deters the buyer from private learning (with Learning Deterrence), while Stochastic Return mechanism that induces partial learning is always sub-optimal. Trading is efficient for both sufficiently optimistic and pessimistic buyer. Though the seller's expected revenue is monotone on the buyer's prior belief, the buyer's ex-ante trading surplus is non-monotone. More surprisingly, the buyer is worse off under a Free Return mechanism. When cost of learning converges to zero, the result converges to the standard niche-mass market analysis.
"Information Design in Cheap Talk", Mar 2020, Journal of Economic Theory, reject and resubmit
Brownbag University of Toronto, Midwest Theory Conference
Abstract: An uninformed sender chooses a publicly observable experiment and sends a message to a receiver after privately learning the experimental outcome. To design the optimal experiment, the sender faces a tension between acquiring more information and alleviating the conflict of interest. In the benchmark model, the optimal experiment generates a conclusive signal (conclusive good news) about the state in which the two parties’ interests coincide. When the choice of experiment is not publicly observable and the sender cannot commit to it, an informative equilibrium exists if and only if there exists an equilibrium where the sender chooses to become perfectly informed.
Brownbag University of Toronto, Midwest Theory Conference
Abstract: An uninformed sender chooses a publicly observable experiment and sends a message to a receiver after privately learning the experimental outcome. To design the optimal experiment, the sender faces a tension between acquiring more information and alleviating the conflict of interest. In the benchmark model, the optimal experiment generates a conclusive signal (conclusive good news) about the state in which the two parties’ interests coincide. When the choice of experiment is not publicly observable and the sender cannot commit to it, an informative equilibrium exists if and only if there exists an equilibrium where the sender chooses to become perfectly informed.
"Optimal Experimentation Design with Secret Repetition" (with Zheng Gong), Dec 2018
ES European Winter Meeting, Brownbag University of Hong Kong, Brownbag University of Toronto (available upon request)
Abstract: We study a persuasion game with limited commitment in which a biased sender designs and conducts costly experiments to acquire information which he can conceal or reveal. The sender commits to the experiment design, but he can secretly repeat experiments and selectively report the outcomes. In the benchmark model, the optimal experiment turns out to be a one-round experiment and the sender truthfully discloses the experiment outcome. The cost of an experiment is a measure of credibility. Higher credibility leads to less informative experiment which lowers the receiver's payoff. With general payoff function of the sender, the above results remain with mild restrictions. We geometrically characterize the optimal experiment using the same concavification with Kamenica and Gentzkow (2011) but within a refined belief space.
ES European Winter Meeting, Brownbag University of Hong Kong, Brownbag University of Toronto (available upon request)
Abstract: We study a persuasion game with limited commitment in which a biased sender designs and conducts costly experiments to acquire information which he can conceal or reveal. The sender commits to the experiment design, but he can secretly repeat experiments and selectively report the outcomes. In the benchmark model, the optimal experiment turns out to be a one-round experiment and the sender truthfully discloses the experiment outcome. The cost of an experiment is a measure of credibility. Higher credibility leads to less informative experiment which lowers the receiver's payoff. With general payoff function of the sender, the above results remain with mild restrictions. We geometrically characterize the optimal experiment using the same concavification with Kamenica and Gentzkow (2011) but within a refined belief space.
"Right is Wrong: Term Limit and Information Transmission" (work in progress)
"Social Discrimination and Evolution of Social Norms" (work in progress)