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

_IMF Working Papers, April 5, 2024_

## Source details

**Canonical URL:** [Harnessing Satellite Data to Improve Social Assistance Targeting in the Eastern Caribbean](https://www.imf.org/en/publications/wp/issues/2024/04/05/harnessing-satellite-data-to-improve-social-assistance-targeting-in-the-eastern-caribbean-547416)

## Other formats

- [Markdown version](/en/publications/wp/issues/2024/04/05/harnessing-satellite-data-to-improve-social-assistance-targeting-in-the-eastern-caribbean-547416/index.md)
- [Structured JSON version](/en/publications/wp/issues/2024/04/05/harnessing-satellite-data-to-improve-social-assistance-targeting-in-the-eastern-caribbean-547416/index.json)
- [Bundle manifest](/en/publications/wp/issues/2024/04/05/harnessing-satellite-data-to-improve-social-assistance-targeting-in-the-eastern-caribbean-547416/bundle-manifest.json)

## Bibliographic details
- Authors: Sophia Chen, Ryu Matsuura, Flavien Moreau, Joana Pereira
- Published: April 5, 2024
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798400274312.001

---

### Executive 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.
- The authors leverage recent advances in machine learning and satellite imagery processing to propose an implementable strategy under these constraints.
- Main empirical claim: local well-being can be predicted with high accuracy in the Eastern Caribbean region using satellite data.
- Policy implication: satellite-based predictions can improve targeting by reducing aggregation bias, better allocating resources across areas, and proxying for information difficult to verify.

### Findings and implications for targeting
- Predictive performance
  - Local well-being is predicted with high accuracy using satellite data (as reported by the study).
- Targeting improvements enabled by satellite predictions
  - Reducing aggregation bias.
  - Better allocating resources across areas.
  - Providing proxies for hard-to-verify information relevant to eligibility or need.
- Context-specific relevance
  - Strategy responds to the need for rapid support during large economic and natural disaster shocks.
  - Tailored to Small Island Developing States in the Eastern Caribbean context.

### Methodology and technical approach
- Data and techniques
  - Use of satellite imagery processing combined with machine learning advances.
- Implementation emphasis
  - The paper proposes an implementable strategy suitable where traditional household or administrative data are limited or slow to update.

---

## Content in this bundle

- **Working Paper**
  - [Working Paper (Markdown version)](/-/media/files/publications/wp/2024/english/wpiea2024084-print-pdf.pdf.md){rel="alternate" type="text/markdown"}
  - [Working Paper (PDF)](/-/media/files/publications/wp/2024/english/wpiea2024084-print-pdf.pdf){rel="external" type="application/pdf"}

---

_Source: https://www.imf.org/en/publications/wp/issues/2024/04/05/harnessing-satellite-data-to-improve-social-assistance-targeting-in-the-eastern-caribbean-547416_