The authors derive a nonparametric identification formula for the average treatment effect that combines experimental data with observational data on a post-outcome remotely sensed proxy and provide n^{-1/2} inference robust to misspecification.
Substituting these expressions into the previous step and cancelingfR(r)yields E{∆e(d,z)−∆ oα(d,z)|R}=0
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Program Evaluation with Remotely Sensed Outcomes
The authors derive a nonparametric identification formula for the average treatment effect that combines experimental data with observational data on a post-outcome remotely sensed proxy and provide n^{-1/2} inference robust to misspecification.