Paths to stability in two-sided matching under uncertainty

We consider one-to-one matching problems under two modalities of uncertainty in which types are assigned to agents either with or without replacement. Individuals have preferences over the possible types of the agents from the opposite market side and initially know the 'name' but not the 'type' of their potential partners. In this context, learning occurs via matching and using Bayes' rule. We introduce the notion of a stable and consistent outcome, and show how the interaction between blocking and learning behavior shapes the existence of paths to stability in each of these two uncertainty environments. Existence of stable and consistent outcomes then follows as a side result.