Amazon fund 10 years later: lessons from the world's largest REDD+ program

Detalhes bibliográficos
Autor(a) principal: Juliano Correa
Data de Publicação: 2019
Outros Autores: Richard van der Hoff, Raoni Guerra Lucas Rajão
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFMG
Texto Completo: https://doi.org/10.3390/f10030272
http://hdl.handle.net/1843/51969
https://orcid.org/0000-0002-7277-9899
https://orcid.org/0000-0002-0708-0264
https://orcid.org/0000-0002-1133-4837
Resumo: Results-Based Funding (RBF) for Reducing Emissions from Deforestation and Forest Degradation (REDD+) has become an important instrument for channeling financial resources to forest conservation activities. At the same time, much literature on conservation funding is ambiguous about the effectiveness of existing RBF schemes. Many effectiveness evaluations follow a simplified version of the principal-agent model, but in practice, the relation between aid providers and funding recipients is much more complex. As a consequence, intermediary steps of conservation funding are often not accounted for in effectiveness studies. This research paper aims to provide a nuanced understanding of conservation funding by analyzing the allocation of financial resources for one of the largest RBF schemes for REDD+ in the world: the Brazilian Amazon Fund. As part of this analysis, this study has built a dataset of information, with unprecedented detail, on Amazon Fund projects, in order to accurately reconstruct the allocation of financial resources across different stakeholders (i.e., governments, NGOs, research institutions), geographies, and activities. The results show that that the distribution of resources of the Amazon Fund lack a clear strategy that could maximize the results of the fund in terms of deforestation reduction. First, there are evidences that in some cases governmental organizations lack financial additionality for their projects, which renders the growing share of funding to this type of stakeholder particularly worrisome. Second, the Amazon Fund allocations did also not systematically have privileged the municipalities that showed the recent highest deforestation rates. rom the 10 municipalities with the higher deforestation rates in 2017, only 2 are amongst the top 100 receiving per/Ha considering the 775 municipalities from Legal Amazon. Third, the allocation of the financial resources from the Amazon Fund reflects the support of different projects that adopt significantly diverging theories of change, many of which are not primarily concerned with attaining further deforestation reductions. These results reflect the current approach adopted by the Amazon Fund, that do not actively seek areas for intervention, but instead wait for project submissions from proponents. As a consequence, project owners exert much influence on to the type of activities that they support how deforestation reduction is expected to be attained. The article concludes that the Amazon Fund as well as other RBF programs, should evolve over time in order to develop a more targeted funding strategy to maximize the long-term impact in reducing emissions from deforestation.
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spelling 2023-04-14T20:07:51Z2023-04-14T20:07:51Z2019103https://doi.org/10.3390/f100302721999-4907http://hdl.handle.net/1843/51969https://orcid.org/0000-0002-7277-9899https://orcid.org/0000-0002-0708-0264https://orcid.org/0000-0002-1133-4837Results-Based Funding (RBF) for Reducing Emissions from Deforestation and Forest Degradation (REDD+) has become an important instrument for channeling financial resources to forest conservation activities. At the same time, much literature on conservation funding is ambiguous about the effectiveness of existing RBF schemes. Many effectiveness evaluations follow a simplified version of the principal-agent model, but in practice, the relation between aid providers and funding recipients is much more complex. As a consequence, intermediary steps of conservation funding are often not accounted for in effectiveness studies. This research paper aims to provide a nuanced understanding of conservation funding by analyzing the allocation of financial resources for one of the largest RBF schemes for REDD+ in the world: the Brazilian Amazon Fund. As part of this analysis, this study has built a dataset of information, with unprecedented detail, on Amazon Fund projects, in order to accurately reconstruct the allocation of financial resources across different stakeholders (i.e., governments, NGOs, research institutions), geographies, and activities. The results show that that the distribution of resources of the Amazon Fund lack a clear strategy that could maximize the results of the fund in terms of deforestation reduction. First, there are evidences that in some cases governmental organizations lack financial additionality for their projects, which renders the growing share of funding to this type of stakeholder particularly worrisome. Second, the Amazon Fund allocations did also not systematically have privileged the municipalities that showed the recent highest deforestation rates. rom the 10 municipalities with the higher deforestation rates in 2017, only 2 are amongst the top 100 receiving per/Ha considering the 775 municipalities from Legal Amazon. Third, the allocation of the financial resources from the Amazon Fund reflects the support of different projects that adopt significantly diverging theories of change, many of which are not primarily concerned with attaining further deforestation reductions. These results reflect the current approach adopted by the Amazon Fund, that do not actively seek areas for intervention, but instead wait for project submissions from proponents. As a consequence, project owners exert much influence on to the type of activities that they support how deforestation reduction is expected to be attained. The article concludes that the Amazon Fund as well as other RBF programs, should evolve over time in order to develop a more targeted funding strategy to maximize the long-term impact in reducing emissions from deforestation.O Financiamento Baseado em Resultados (RBF) para Redução de Emissões por Desmatamento e Degradação Florestal (REDD+) tornou-se um importante instrumento para canalizar recursos financeiros para atividades de conservação florestal. Ao mesmo tempo, muita literatura sobre financiamento de conservação é ambígua sobre a eficácia dos esquemas de RBF existentes. Muitas avaliações de eficácia seguem uma versão simplificada do modelo principal-agente, mas, na prática, a relação entre provedores de ajuda e beneficiários de financiamento é muito mais complexa. Como consequência, as etapas intermediárias do financiamento da conservação muitas vezes não são consideradas nos estudos de eficácia. Este trabalho de pesquisa visa fornecer uma compreensão diferenciada do financiamento da conservação, analisando a alocação de recursos financeiros para um dos maiores esquemas de RBF para REDD+ no mundo: o Fundo Amazônia Brasileiro. Como parte dessa análise, este estudo construiu um conjunto de informações, com detalhes sem precedentes, sobre os projetos do Fundo Amazônia, a fim de reconstruir com precisão a alocação de recursos financeiros entre diferentes partes interessadas (ou seja, governos, ONGs, instituições de pesquisa), geografias, e atividades. Os resultados mostram que a distribuição dos recursos do Fundo Amazônia carece de uma estratégia clara que possa maximizar os resultados do fundo em termos de redução do desmatamento. Primeiro, há evidências de que, em alguns casos, as organizações governamentais carecem de adicionalidade financeira para seus projetos, o que torna particularmente preocupante a parcela crescente de financiamento a esse tipo de público. Em segundo lugar, as alocações do Fundo Amazônia também não privilegiaram sistematicamente os municípios que apresentaram as maiores taxas recentes de desmatamento. Dos 10 municípios com maiores taxas de desmatamento em 2017, apenas 2 estão entre os 100 maiores receptores por/ha considerando os 775 municípios da Amazônia Legal. Em terceiro lugar, a alocação dos recursos financeiros do Fundo Amazônia reflete o apoio de diferentes projetos que adotam teorias de mudança significativamente divergentes, muitos dos quais não estão preocupados principalmente em obter maiores reduções do desmatamento. Esses resultados refletem a atual postura adotada pelo Fundo Amazônia, que não busca ativamente áreas para intervenção, mas sim aguarda a submissão de projetos por parte dos proponentes. Como consequência, os proprietários do projeto exercem muita influência sobre o tipo de atividades que eles apoiam, como se espera que a redução do desmatamento seja alcançada. O artigo conclui que o Fundo Amazônia, assim como outros programas RBF, deve evoluir ao longo do tempo para desenvolver uma estratégia de financiamento mais direcionada para maximizar o impacto de longo prazo na redução das emissões do desmatamento.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorOutra AgênciaengUniversidade Federal de Minas GeraisUFMGBrasilENG - DEPARTAMENTO DE ENGENHARIA PRODUÇÃOForestsPolítica ambiental - Custo-benefícioDesmatamento - AmazôniaFundo de investimentos da AmazôniaMudanças climáticas - política governamentalREDD+Amazon FundResults-Based Fundingbenefit distributionresource allocationclimate change fundingeffectivenessforest conservation fundingAmazon fund 10 years later: lessons from the world's largest REDD+ programFundo Amazônia 10 anos depois: lições do maior programa de REDD+ do mundoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://www.mdpi.com/1999-4907/10/3/272Juliano CorreaRichard van der HoffRaoni Guerra Lucas Rajãoapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/51969/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALAmazon Fund 10 Years Later.pdfAmazon Fund 10 Years Later.pdfapplication/pdf2994541https://repositorio.ufmg.br/bitstream/1843/51969/2/Amazon%20Fund%2010%20Years%20Later.pdf3a98ba5858acc9814a5a8b7a20d7876bMD521843/519692023-04-14 17:07:51.216oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-04-14T20:07:51Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Amazon fund 10 years later: lessons from the world's largest REDD+ program
dc.title.alternative.pt_BR.fl_str_mv Fundo Amazônia 10 anos depois: lições do maior programa de REDD+ do mundo
title Amazon fund 10 years later: lessons from the world's largest REDD+ program
spellingShingle Amazon fund 10 years later: lessons from the world's largest REDD+ program
Juliano Correa
REDD+
Amazon Fund
Results-Based Funding
benefit distribution
resource allocation
climate change funding
effectiveness
forest conservation funding
Política ambiental - Custo-benefício
Desmatamento - Amazônia
Fundo de investimentos da Amazônia
Mudanças climáticas - política governamental
title_short Amazon fund 10 years later: lessons from the world's largest REDD+ program
title_full Amazon fund 10 years later: lessons from the world's largest REDD+ program
title_fullStr Amazon fund 10 years later: lessons from the world's largest REDD+ program
title_full_unstemmed Amazon fund 10 years later: lessons from the world's largest REDD+ program
title_sort Amazon fund 10 years later: lessons from the world's largest REDD+ program
author Juliano Correa
author_facet Juliano Correa
Richard van der Hoff
Raoni Guerra Lucas Rajão
author_role author
author2 Richard van der Hoff
Raoni Guerra Lucas Rajão
author2_role author
author
dc.contributor.author.fl_str_mv Juliano Correa
Richard van der Hoff
Raoni Guerra Lucas Rajão
dc.subject.por.fl_str_mv REDD+
Amazon Fund
Results-Based Funding
benefit distribution
resource allocation
climate change funding
effectiveness
forest conservation funding
topic REDD+
Amazon Fund
Results-Based Funding
benefit distribution
resource allocation
climate change funding
effectiveness
forest conservation funding
Política ambiental - Custo-benefício
Desmatamento - Amazônia
Fundo de investimentos da Amazônia
Mudanças climáticas - política governamental
dc.subject.other.pt_BR.fl_str_mv Política ambiental - Custo-benefício
Desmatamento - Amazônia
Fundo de investimentos da Amazônia
Mudanças climáticas - política governamental
description Results-Based Funding (RBF) for Reducing Emissions from Deforestation and Forest Degradation (REDD+) has become an important instrument for channeling financial resources to forest conservation activities. At the same time, much literature on conservation funding is ambiguous about the effectiveness of existing RBF schemes. Many effectiveness evaluations follow a simplified version of the principal-agent model, but in practice, the relation between aid providers and funding recipients is much more complex. As a consequence, intermediary steps of conservation funding are often not accounted for in effectiveness studies. This research paper aims to provide a nuanced understanding of conservation funding by analyzing the allocation of financial resources for one of the largest RBF schemes for REDD+ in the world: the Brazilian Amazon Fund. As part of this analysis, this study has built a dataset of information, with unprecedented detail, on Amazon Fund projects, in order to accurately reconstruct the allocation of financial resources across different stakeholders (i.e., governments, NGOs, research institutions), geographies, and activities. The results show that that the distribution of resources of the Amazon Fund lack a clear strategy that could maximize the results of the fund in terms of deforestation reduction. First, there are evidences that in some cases governmental organizations lack financial additionality for their projects, which renders the growing share of funding to this type of stakeholder particularly worrisome. Second, the Amazon Fund allocations did also not systematically have privileged the municipalities that showed the recent highest deforestation rates. rom the 10 municipalities with the higher deforestation rates in 2017, only 2 are amongst the top 100 receiving per/Ha considering the 775 municipalities from Legal Amazon. Third, the allocation of the financial resources from the Amazon Fund reflects the support of different projects that adopt significantly diverging theories of change, many of which are not primarily concerned with attaining further deforestation reductions. These results reflect the current approach adopted by the Amazon Fund, that do not actively seek areas for intervention, but instead wait for project submissions from proponents. As a consequence, project owners exert much influence on to the type of activities that they support how deforestation reduction is expected to be attained. The article concludes that the Amazon Fund as well as other RBF programs, should evolve over time in order to develop a more targeted funding strategy to maximize the long-term impact in reducing emissions from deforestation.
publishDate 2019
dc.date.issued.fl_str_mv 2019
dc.date.accessioned.fl_str_mv 2023-04-14T20:07:51Z
dc.date.available.fl_str_mv 2023-04-14T20:07:51Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/51969
dc.identifier.doi.pt_BR.fl_str_mv https://doi.org/10.3390/f10030272
dc.identifier.issn.pt_BR.fl_str_mv 1999-4907
dc.identifier.orcid.pt_BR.fl_str_mv https://orcid.org/0000-0002-7277-9899
https://orcid.org/0000-0002-0708-0264
https://orcid.org/0000-0002-1133-4837
url https://doi.org/10.3390/f10030272
http://hdl.handle.net/1843/51969
https://orcid.org/0000-0002-7277-9899
https://orcid.org/0000-0002-0708-0264
https://orcid.org/0000-0002-1133-4837
identifier_str_mv 1999-4907
dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Forests
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dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv ENG - DEPARTAMENTO DE ENGENHARIA PRODUÇÃO
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
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