<ul><li>Economists often estimate treatment effects in experiments using remotely sensed variables (RSVs) like satellite images or mobile phone activity.</li><li>A common practice is to use an observational sample to train a predictor of the economic outcome from the RSV.</li><li>However, using this method may introduce bias if the RSV is post-outcome, meaning a variation in the economic outcome causes variation in the RSV.</li><li>The study proposes a new identification method that requires three predictions of RSVs for more accurate causal inference.</li></ul>

Program Evaluation with Remotely Sensed Outcomes

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