Three essays on the economics of social interactions

Abstract

This Doctoral thesis is divided in three chapters, each corresponding to a self-consistent paper in which, even if with different focus and methodology, the aim is to understand the economics beyond social interactions. In particular I investigate how different strategic, informational or social environment affect the diffusion and evolution of agents’ beliefs, preferences and norms.

The first chapter On the Interplay Between Norms and Strategic Environments” is a joint work with Pietro Dindo and we study the role of different strategic environment for the dynamics of norms in a heterogeneous population divided into two cultural groups.

In the second chapter "Cultural Transmission with Incomplete Information: Parental Self-Efficacy and Group Misrepresentation” a joint work with Fabrizio Panebianco, we analyze, using the solution concept of self-confirming equilibrium, a cultural transmission model where parents have incomplete information about the the social structure and the efficacy of their vertical transmission efforts.

The last chapter ”Non-Bayesian Social Learning and the Spread of Misinformation in Networks” studies learning in a setting where agents receive each period independent noisy signals about the true state of the world and then communicate in a network where there are stubborn agents who spread misinformation.

The first chapter On the Interplay Between Norms and Strategic Environments” is a joint work with Pietro Dindo and we study the role of different strategic environment for the dynamics of norms in a heterogeneous population divided into two cultural groups.

In the second chapter "Perceived Group Under-Representation. Cultural Transmission with Incomplete Information” a joint work with Fabrizio Panebianco, we analyze, using the solution concept of self-confirming equilibrium, a cultural transmission model where parents have incomplete information about the social structure and the efficacy of their vertical transmission efforts.

The last chapter ”Non-Bayesian Social Learning and the Spread of Misinformation in Networks” studies learning in a setting where agents receive each period independent noisy signals about the true state of the world and then communicate in a network where there are stubborn agents who spread misinformation.