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Causal Inference with Satellite Imagery: A Comparison of Methods for Forest Conservation Data

Author

Listed:
  • Haya Alsharif
  • Ashesh Rambachan
  • Rahul Singh
  • Davide Viviano

Abstract

Can satellite-based predictions substitute for traditional outcome measurements in program evaluation? Using forest cover data from the Democratic Republic of the Congo, Brazil, and Indonesia, we conduct semisynthetic simulations comparing estimation methods. The RSV estimator (Rambachan, Singh, and Viviano 2025) formalizes the postoutcome structure of remotely sensed data—changes in forest cover cause changes in satellite imagery—delivering approximately unbiased treatment effects with correct coverage. Some alternative approaches exhibit significant bias despite highly accurate pretrained predictors. When limited validation data are available, the RSV estimator efficiently incorporates observational samples while remaining robust to distribution shift, achieving meaningful reductions in standard errors.

Suggested Citation

  • Haya Alsharif & Ashesh Rambachan & Rahul Singh & Davide Viviano, 2026. "Causal Inference with Satellite Imagery: A Comparison of Methods for Forest Conservation Data," AEA Papers and Proceedings, American Economic Association, vol. 116, pages 87-91, May.
    • Handle: RePEc:aea:apandp:v:116:y:2026:p:87-91
    DOI: 10.1257/pandp.20261019
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    More about this item

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy

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