Safe Policy Learning under Regression Discontinuity Designs with Multiple Cutoffs

Understand

The regression discontinuity (RD) design is widely used for program evaluation with observational data.

• The primary focus of the existing literature has been the estimation of the local average treatment effect at the existing treatment cutoff.
• In contrast, we consider policy learning under the RD design.
• Because the treatment assignment mechanism is deterministic, learning better treatment cutoffs requires extrapolation.