Essays on learning, social influence and economic policy design

The objective of this dissertation is to develop various theoretical frameworks in order to explore the relationship between collective phenomena and individual actions. In the process, the rational expectations hypothesis is relaxed in chapter 2 and chapter 3 adopting two different learning processes, while chapter 4 disrupts behavioural and expectational rules with an agent based model characterized by heterogeneous agents and no aggregate centralized mechanism.
Chapter 2 incorporates the concept of Behavioural Learning Equilibrium into a DSGE model, with a feedback mechanism between the financial market and real aggregates. Specifically, it investigates a comparison between the Rational Expectations Hypothesis and Bounded Rationality to understand whether asset price targeting represent a valid policy for a central bank.
Chapter 3 provides a theoretical framework to investigate the homophily effect on financial fluctuations in a simple asset market model with a feedback mechanism between expectations diffusions and asset price dynamics. A homophilous network generation algorithm produces the community framework through which investors locally exchanging information regarding investment strategies. They then may switch between different rules, which govern their expectations about future stock prices, taking in consideration relative performance and social influence.
Chapter 4 analyses the impact of different designs of COVID-19 related lockdown policies on economic loss and mortality using a micro-level simulation model, which combines a multi-sectoral closed economy with an epidemic transmission model. The empirical validity of the model is established using data on economic and pandemic dynamics in Germany in the first six months after the COVID-19 outbreak.