The standard economic view suggests that people will commit an action if its expected benefits outweigh its costs. But before people weigh the costs and benefits of an action, what affects whether they think of the action in the first place? We argue that actions are more likely to enter into consideration when they are cognitively accessible. We describe three psychological parameters that influence accessibility: automatic assumptions, identity, and perceptions of privacy. These parameters make it possible to identify new interventions for behavior change.

Economists have become increasingly interested in studying the nature of production functions in social policy applications, with the goal of improving productivity. Traditionally models have assumed workers are homogenous inputs. However, in practice, substantial variability in productivity means the marginal productivity of labor depends substantially on which new workers are hired--which requires not an estimate of a causal effect, but rather a prediction. We demonstrate that there can be large social welfare gains from using machine learning tools to predict worker productivity, using data from two important applications - police hiring and teacher tenure decisions.