treatments are conditionally randomly assigned and the controls are sufficiently flexible to avoid omitted variables bias … treatments. Thus, recent concerns about heterogeneity-induced bias in regressions leveraging potential outcome restrictions (e … contamination bias and propose a new class of efficient estimators of weighted average effects that avoid bias. In a re-analysis of …

assignment methods such as matched pair designs ensure balance across arms while maintaining randomization and permitting … reduces the informativeness of experiments. A simple structural model suggests that for a typical experiment, using a balanced …

's outcomes. This improvement is observed in both the field experiment and the subsequent large-scale government adoption. We also …

This paper considers causal inference and sample selection bias in non-experimental settings in which: (i) few units in …-treatment characteristics. We propose the use of propensity score matching methods and implement them using data from the NSW experiment … and compare the estimates of the treatment effect obtained using our methods to the benchmark results from the experiment …

behavioral change. In a field experiment with around 1,000 participants, we directly observe the interventions' effects on …