In an ongoing evaluation of post-secondary financial aid, we use random assignment to assess the causal effects of large privately-funded aid awards. Here, we compare the unbiased causal effect estimates from our RCT with two types of non-experimental econometric estimates. The first applies a selection-on-observables assumption in data from an earlier, nonrandomized cohort; the second uses a regression discontinuity design. Selection-on-observables methods generate estimates well below the experimental benchmark. Regression discontinuity estimates are similar to experimental estimates for students near the cutoff, but sensitive to controlling for the running variable, which is unusually coarse.