We develop a decentralized Bayesian model of college admissions with two ranked colleges, heterogeneous students, and two realistic match frictions: students find it costly to apply to college, and college evaluations of their applications are uncertain. Students thus face a portfolio choice...

This paper introduces a general model of matching that includes evolving public Bayesian reputations and stochastic production. Despite productive complementarity, assortative matching robustly fails for high discount factors, unlike in <xref ref-type="bibr" rid="R3">Becker (1973)</xref>. This failure holds around the highest...

The timing of elections is flexible in many countries. We study this optimization by first creating a Bayesian learning model of a mean-reverting political support process. We then explore optimal electoral timing, modelling it as a renewable American option with interacting waiting and stopping...

The timing of elections is flexible in many countries. We study this optimization by first creating a Bayesian learning model of a mean-reverting political support process. We then explore optimal electoral timing, modelling it as a renewable American option with interacting waiting and stopping...