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Using publicly available satellite imagery and deep learning to understand economic well-being in Africa

Published in Nature Communications, 2020

Accurate and comprehensive measurements of economic well-being are fundamental inputs into both research and policy, but such measures are unavailable at a local level in many parts of the world. Here we train deep learning models to predict survey-based estimates of asset wealth across ~ 20,000 African villages from publicly-available multispectral satellite imagery.

Recommended citation: Yeh, C., Perez, A., Driscoll, A. et al. Using publicly available satellite imagery and deep learning to understand economic well-being in Africa. Nat Commun 11, 2583 (2020). https://www.nature.com/articles/s41467-020-16185-w

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EC 204 Empirical Economics 2

Undergraduate course, Boston University, Department of Economics, 2023

Second semester of a two-semester sequence of empirical techniques used in economic analysis