Data and Code for:How Many (Half) Moons? Measuring Technology Adoption, From the Sky and on the Ground

Measuring technology adoption is central to evaluating development policies, yet standard approaches face tradeoffs between accuracy, cost, and scalability. Using data from a randomized controlled trial in Niger, we compare four methods for measuring adoption of demi-lunes, an agricultural technology: direct observation, survey self-reports, manual satellite-based observation, and satellite imagery with machine learning (SIML). Treating direct observation as ground truth, we quantify measurement error on extensive and intensive margins and assess tradeoffs between costs and error at project and policy scales. We find that self-reports perform well at both scales, while satellite-based methods scale cheaply but generate significant measurement error.