Academic studies can estimate the causal effects of programs and policies, however, their results may not extrapolate beyond their original setting. This workshop gathers leading researchers in causal inference and extrapolation to explore new approaches to this problem. The workshop will cover better ways to design experimental trials, analyze data, and synthesize results from multiple settings. Topics to be discussed include: principal stratification, split samples, Bayesian analysis, structural models, and general equilibrium effects.