Essays In Social Networks And Development Economics

(cont.) substitutes for commitment. On net, savings allows individuals to smooth risk that cannot be shared interpersonally, with the largest benefits for those who are weakly connected in the network. The final chapter (co-authored with my classmates Horacio Larreguy and Juan Pablo Xandri) attempts to determine which models of social learning on networks best describe empirical behavior. Theory has focused on two leading models of social learning on networks: Bayesian and DeGroot rules of thumb learning. These models can yield greatly divergent behavior; individuals employing rules of thumb often double-count information and may not exhibit convergent behavior in the long run. By conducting a unique lab experiment in rural Karnataka, India, set up to exactly differentiate between these two models, we test which model best describes social learning processes on networks. We study experiments in which seven individuals are placed into a network, each with full knowledge of its structure. The participants attempt to learn the underlying (binary) state of the world. Individuals receive independent, identically distributed signals about the state in the first period only; thereafter, individuals make guesses about the underlying state of the world and these guesses are transmitted to their neighbors at the beginning of the following round. We consider various environments including incomplete information Bayesian models and provide evidence that individuals are best described by DeGroot models wherein they either take simple majority of opinions in their neighborhood.