Working Paper

Ex-ante Heterogeneity in Directed Search Games

Directed search models usually assume that workers' skills are drawn from the same distribution. I study a game in which finitely many workers, each knowing his own skill, apply to one of two firms, and each firm hires its most skilled applicant. The standard symmetric equilibrium turns out to be fragile: it is very sensitive to small differences in workers' skill distributions. I characterize an equilibrium that survives such differences, show that it always exists, and show that it is in a sense the only equilibrium robust to all small asymmetries. The robust equilibrium can be constructed by a recursive algorithm, and I relate it to the symmetric equilibrium used in the literature. 

Selling Mechanisms Under Misspecified Learning (Job Market Paper)

Buyers in a repeated selling mechanism hold a misspecified parametric model of their environment and learn by Bayesian updating from allocation outcomes alone. Because the mechanism generates the outcomes buyers learn from, its design shapes what they come to believe. This paper asks when a seller can choose a mechanism under which a given, possibly misspecified, belief is sustained by learning, and characterizes such mechanisms. With a single buyer, conditions on the buyer's model alone guarantee that a unique mechanism draws every initial belief to the target belief. With two buyers, local stability is established under conditions on the buyers' models and the value distribution, and a computational method identifies mechanisms that extend the basin of attraction to every belief below the sustained one. The main revenue implication is that value-dependent beliefs can allow the seller to exceed the Myerson benchmark, whereas value-independent beliefs cannot.