Dell, MelissaRay, Benjamin Alan2025-09-1720242025-05-282024Ray, Benjamin Alan. 2024. Improving Microestimates of Poverty from Satellite Images. Bachelors Thesis, Harvard University Engineering and Applied Sciences.31143920https://dash.harvard.edu/handle/1/42719175Accurately mapping the geographic distribution of poverty is pivotal for advancing development, yet this effort is often hampered by sparse, unreliable, and non-granular data. Using publicly available satellite images for nearly 20,000 villages in Africa, this paper demonstrates how self-supervised pre-training can enhance the accuracy and scalability of microestimates of poverty, as measured by the asset wealth index (AWI). This method outperforms a fully supervised machine learning approach by extracting more predictive features from the images, explaining approximately 72\% of the survey-measured variation in AWI and surpassing the current state-of-the-art by about 3 percentage points. By offering a more accurate and scalable solution for poverty estimation, this research provides valuable insights for informed policymaking and targeted poverty alleviation.application/pdfenRemote sensingEconomicsComputer scienceThesis or Dissertation2025-09-17