Amazon Fund 10 Years Later: Lessons from the World’s Largest REDD+ Program

摘要: Results-Based Funding (RBF) for Reducing Emissions from Deforestation and Forest Degradation (REDD+) has become an important instrument channeling financial resources to forest conservation activities. At the same time, much literature on funding is ambiguous about effectiveness of existing RBF schemes. Many evaluations follow a simplified version principal-agent model, but in practice, relation between aid providers recipients more complex. As consequence, intermediary steps are often not accounted studies. This research paper aims provide nuanced understanding by analyzing allocation one largest schemes REDD+ world: Brazilian Amazon Fund. part this analysis, study built dataset information, with unprecedented detail, Fund projects, order accurately reconstruct across different stakeholders (i.e., governments, NGOs, institutions), geographies, The results show that distribution lack clear strategy could maximize fund terms deforestation reduction. First, there evidences some cases governmental organizations additionality their which renders growing share type stakeholder particularly worrisome. Second, allocations did also systematically have privileged municipalities showed recent highest rates. rom 10 higher rates 2017, only 2 amongst top 100 receiving per/Ha considering 775 Legal Amazon. Third, reflects support projects adopt significantly diverging theories change, many primarily concerned attaining further reductions. These reflect current approach adopted Fund, do actively seek areas intervention, instead wait project submissions proponents. owners exert influence activities they how reduction expected be attained. article concludes as well other programs, should evolve over time develop targeted long-term impact reducing emissions deforestation.