Optimism leads to optimality: Ambiguity in network formation

Abstract

We analyze a model of endogenous two-sided network formation where players are affected by uncertainty in their opponents’ decisions. We model this uncertainty using the notion of equilibrium under ambiguity. Unlike the set of Nash equilibria, the set of equilibria under ambiguity does not always include underconnected and thus inefficient networks such as the empty network. On the other hand, it may include networks with unreciprocated, one-way links, which comes with an efficiency loss as linking efforts are costly. We characterize equilibria under ambiguity and provide conditions under which increased player optimism comes with an increase in connectivity and realized benefits in equilibrium. Next, we analyze network realignment under a myopic updating process with optimistic shocks, and derive a global stability condition of efficient networks. Under this condition, called ‘aligned preferences’, a subset of the Pareto optimal equilibrium networks is reached, specifically, networks that maximize the players’ total benefits of connections.

Reference

Péter Bayer, and Ani Guerdjikova, “Optimism leads to optimality: Ambiguity in network formation”, TSE Working Paper, n. 22-1289, January 2022.