Welfare Economics. A key theme of Cognitive Economics is finite cognition (often misleadingly called “bounded rationality …

We study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual … characterize the conditions under which there will be asymptotic learning -- that is, the conditions under which, as the social … unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some …

learning. Individuals in our model are permitted to appreciate and use the information content in the default options set by …

different learning mechanisms within the investor population, we characterize the optimal timing of obfuscation for financial … participation in the market. We show that educational initiatives that are directed to facilitate learning by investors may induce …

transparent countries. On the other hand, herding among funds tends to be more prevalent in less transparent countries. There is …

We examine how a social stigma of seeking information can inhibit learning. Consider a Seeker of uncertain ability who … experiment with treatments designed to detect both effects. Seekers have three days to retrieve information from paired Advisors … whether a Seeker's ability is revealed to the paired Advisor, irrespective of the seeking decision. We find that low …

decision-making and willingness to share in the context of a personal financial decision. Content geared toward giving better … deception have externalities on other peoples' literacy and decision-making. Our work has important implications for policies …

networks are recognized as the most credible source of information about new technologies. We incorporate social learning in … extension policy using a large-scale field experiment in which we communicate to farmers using different members of social … communicator influences learning and adoption. Farmers find communicators who face agricultural conditions and constraints most …

We examine the role of generalized constant gain stochastic gradient (SGCG) learning in generating large deviations of …