To estimate causal effects from observational data, an applied researcher must impose beliefs. The instrumental variables exclusion restriction, for example, represents the belief that the instrument has no direct effect on the outcome of interest. Yet beliefs about instrument validity do not...

This paper analyzes a geographic quasi-experiment embedded in a cluster-randomized experiment in Honduras. In the experiment, average treatment effects on school enrollment and child labor were large--especially in the poorest blocks--and could be generalized to a policy-relevant population...

We examine the generalizability of internally valid estimates of causal effects in a fixed population over time when that population is subject to aggregate shocks. This temporal external validity is shown to depend upon the distribution of the aggregate shocks and the interaction between these...

A modern, decision-theoretic framework can help clarify important practical questions of experimental design. Building on our recent work, this chapter begins by summarizing our framework for understanding the goals of experimenters, and applying this to re-randomization. We then use this...