Designing Weighted and Directed Networks under Complementarities (2019). R&R at the Journal of Economic Theory. Available at SSRN: https://ssrn.com/abstract=3299331.
Whether to maximize aggregate efficiency or to make tradeoffs between efficiency and equality, optimal networks under complementarities involve a hierarchy among agents. Formally, all optimal networks under complementarities are generalized nested split graphs, in which agents are ordered by `link-dominance’.
Resentment and the Evolution of Cooperative Norms (January 2020). Available at SSRN: https://ssrn.com/abstract=3512872.
If people disapprove and punish behaviors that violate common social practices and are harmful to others, then cooperation can be sustained as a self-fulfilling social norm. This insight generates long-run dynamics of cooperation and punishment consistent with recent cross-cultural and experimental findings that are difficult to explain by standard evolutionary models of cooperation.
Conditional Punishment: Descriptive Norms Drive Negative Reciprocity, with Lucas Molleman and Dennie van Dolder.
We show experimentally that descriptive norms about cooperation and punishment – 1) whether people in a payoff irrelevant reference group cooperate and 2) whether they punish defectors – affect an individual’s punishment of defectors.
Work in Progress
Lying and Naivety in Multi-player Cheap Talk, with Daniele Nosenzo.
When several senders talk at the same time to a receiver, lying costs change truth-telling between senders from strategic substitutes to strategic complements. Also, because of the receiver’s naivety, what exactly a sender lies matters.
The Market for Lemons and Liars, with Valeria Burdea.
Can intrinsic preferences for truth-telling solve the problem of adverse selection? No, because there is self-selection: people with different preferences for truth-telling participate in markets with different information disclosure rules. The self-selection leads to bad market outcomes as if all individuals are material payoff maximizers.