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Research Assistants

Evaluating the Impact of REDD+ Carbon Credit Projects using Satellite Data

In this project we will gather information on existing and previously completed carbon credit projects registered under the REDD+ framework and evaluate how much carbon was conserved by applying a variety of causal inference methods, including matching, diff-in-diff, synthetic controls, and others to understand:

  • How much carbon was truly conserved compared to how much was claimed by the project.
  • How different methods and assumptions influence the generated estimates.

The overall goal of the project is to work toward a general methodology that can be applied to improve future carbon credit projects.

Requisite Skills and Qualifications:


  • Strong R coding skills
  • Causal inference/econometric training


  • Background working with spatial data
  • Knowledge of machine learning methods
  • Interest in environmental applications