Optimal Refund Mechanism (Job Market Paper) [slides]
Abstract: This paper studies the optimal refund mechanism when an uninformed buyer can privately acquire information about his valuation over time. In principle, a refund mechanism can specify the odds that the seller requires the product returned while issuing a (partial) refund, which we call stochastic return. It guarantees the seller a strictly positive minimum revenue and facilitates intermediate buyer learning. However, our main result shows that stochastic return is always sub-optimal. The optimal refund mechanism takes simple forms: the seller either deters learning via a well-designed non-refundable price or encourages full learning via free return. Moreover, the optimal mechanism has the same structure for both positive learning and negative learning framework.
Abstract: This paper studies the optimal refund mechanism when an uninformed buyer can privately acquire information about his valuation over time. In principle, a refund mechanism can specify the odds that the seller requires the product returned while issuing a (partial) refund, which we call stochastic return. It guarantees the seller a strictly positive minimum revenue and facilitates intermediate buyer learning. However, our main result shows that stochastic return is always sub-optimal. The optimal refund mechanism takes simple forms: the seller either deters learning via a well-designed non-refundable price or encourages full learning via free return. Moreover, the optimal mechanism has the same structure for both positive learning and negative learning framework.
Information Design in Cheap Talk (new draft coming soon)
Update!!! The new version of this paper focuses on binary state space and finite action space. I provide a simple graphical algorithm to determine the optimal information structure under any arbitrary state-dependent preferences. The major tension is to acquire more information and to alleviate the conflict of interest. In an application where the sender and receiver have common interest at one state, the optimal experiment fully reveals the common interest state with mild restrictions (the less intuitive quasi-concavity condition assumed in the old version is no longer required).
Old version 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.
Update!!! The new version of this paper focuses on binary state space and finite action space. I provide a simple graphical algorithm to determine the optimal information structure under any arbitrary state-dependent preferences. The major tension is to acquire more information and to alleviate the conflict of interest. In an application where the sender and receiver have common interest at one state, the optimal experiment fully reveals the common interest state with mild restrictions (the less intuitive quasi-concavity condition assumed in the old version is no longer required).
Old version 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)
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.
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.
Work in progress:
Monitoring Frequency and Project Turnover (with Wing Suen and Yimeng Zhang)
Right is Wrong: Term Limit and Information Transmission
Social Discrimination and Evolution of Social Norms
Monitoring Frequency and Project Turnover (with Wing Suen and Yimeng Zhang)
Right is Wrong: Term Limit and Information Transmission
Social Discrimination and Evolution of Social Norms