Learning in social networks

Abstract

© 2014 Dr. Imogen Cara HalsteadPeople learn from their social networks - through watching one another's behaviour and listening to one another's advice. This dissertation explores several key features of social learning mechanisms, motivated by a case-study of pineapple farming communities in Ghana, West Africa. First, I revisit the Ghanaian setting originally studied by Conley & Udry (2010), and I present empirical evidence that works to recast existing understanding of the social learning mechanisms at play in this context. My findings suggest that novice pineapple farmers indiscriminately imitate the behaviour of their information contacts - farmers with whom they share advice - rather than adopting successful behaviours exclusively. Second, I present a theoretical model of Bayesian sequential social learning in a setting where agents observe other adopters' behaviour, and then outcomes after a time-lag (as is the case with pineapple cultivation). In equilibrium, earlier agents each successively wait to act in order to observe their immediate predecessor's outcome, while later agents act as soon as possible, instigating a run of herd-like behaviour (in an environment where output signals are only locally observed). I show that equilibrium behaviour is socially optimal when output signals are only locally observed, but that delays can lead to welfare inefficiencies when output signals are observed by the public at large. Third, I present a theoretical model of endogenous network formation in the context of Bayesian learning. Agents can establish multiple links (as evidenced in the Ghanaian farmers' information networks) and are equipped to reconcile different renditions of relayed advice. I show that generalised core-periphery structures are an equilibrium outcome of agents' dynamic best-response link formation decisions