IMF Working Papers

Harnessing Satellite Data to Improve Social Assistance Targeting in the Eastern Caribbean

By Sophia Chen, Ryu Matsuura, Flavien Moreau, Joana Pereira

April 5, 2024

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Sophia Chen, Ryu Matsuura, Flavien Moreau, and Joana Pereira. Harnessing Satellite Data to Improve Social Assistance Targeting in the Eastern Caribbean, (USA: International Monetary Fund, 2024) accessed November 21, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

Prioritizing populations most in need of social assistance is an important policy decision. In the Eastern Caribbean, social assistance targeting is constrained by limited data and the need for rapid support in times of large economic and natural disaster shocks. We leverage recent advances in machine learning and satellite imagery processing to propose an implementable strategy in the face of these constraints. We show that local well-being can be predicted with high accuracy in the Eastern Caribbean region using satellite data and that such predictions can be used to improve targeting by reducing aggregation bias, better allocating resources across areas, and proxying for information difficult to verify.

Subject: Environment, Income, Machine learning, National accounts, Natural disasters, Population and demographics, Technology

Keywords: Aggregation bias, Caribbean, Eastern Caribbean, Hard-to-verify information, Income, Machine learning, Natural disasters, Satellite data, Satellite imagery processing, Small Island Developing States., Social assistance targeting

Publication Details

  • Pages:

    45

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2024/084

  • Stock No:

    WPIEA2024084

  • ISBN:

    9798400274312

  • ISSN:

    1018-5941

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