Machine learning algorithms can find predictive signals that researchers fail to notice; yet they are notoriously hard …

information collection affects equity analyst performance. Collection of hard information, proxied by office workday length, is … positively associated with the quantity and timeliness of analyst reports. Soft information collection, as proxied by propensity … star analyst. Both hard and soft information collection improve forecast precision, a causal result that we confirm using …

maker has learned? The key constraint we impose, which is shared across models of Bayesian learning, is that any learning … Dean 2015) and the NIAS condition (Caplin and Martin 2015) to allow for arbitrary learning. We apply our framework to show … how identification of what was learned can be strengthened with additional assumptions on the form of Bayesian learning …

We provide semiparametric identification results for a broad class of learning models in which continuous outcomes …

learning and policy recommendation in advisory committees. We quantify the effectiveness of advisory panels, and evaluate …

-inconsistent preferences and overconfidence, and have implications for the effectiveness of information interventions on sleep choice …

In this chapter, we discuss field experiments in surveys that are conducted with the purpose of learning about … experimental paradigm, randomized information provision, along with some examples. Next, we outline a few methodological issues …