Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration
考虑激励的合成控制：通过激励探索准确估计反事实
Synthetic control methods (SCMs) are a canonical approach used to estimate treatment effects from panel data in the internet economy. We shed light on a frequently overlooked but ubiquitous assumption made in SCMs of "overlap": a treated unit can be written as some combination -- typically, convex or linear -- of the units that remain under control. We show that if units select their own interventions, and there is sufficiently large heterogeneity between units that prefer…