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.

Environmental policy evaluation is crucial to determining if policy objectives were achieved. In most cases, some of the outcomes can be measured but a proper statistical analysis is difficult to achieve since the data may not represent a random sample (i.e., the data is biased), are not representative of the population or cannot be compared to a control group. This work adapts quasi-experimental statistical methods widely used in epidemiological studies that could be applied to land use policy evaluation in situations of relatively poor data. In order to test and develop this set of methods, we evaluated the effect of a land-use policy known as the rural environmental registry (CAR) on the reduction of deforestation rates in the Brazilian Amazon rainforest. The random variable of interest is the number of deforested hectares in given private properties and the statistic of interest is the difference of the annual deforestation rate between the properties before and after the policy intervention. Since no formal statistical distribution properly fit the data, non-parametrical approaches such as Monte Carlo simulations and Bootstrap were used. Data from the Brazilian states of Mato Grosso and Pará were used, with different time periods and three rural property size classes. Results show that the properties inside the Rural Environmental Registry have reduced their deforestation rates in some property classes and time periods, but this effect has not been systematic across time and space indicating that the policy is only partially effective. We conclude that the proposed statistical methods can be useful in environmental policy evaluation in different contexts due to low demands in terms of data availability and statistical distribution assumptions.

Na década de 1990, os sistemas ERP alcançaram larga utilização. Em contrapartida, o interesse por software livre data dos primeiros desenvolvimentos nas décadas de 1960 e 1970 até os dias atuais. O problema desta pesquisa está em como adotar, selecionar e implantar um ERP livre. As contribuições do trabalho iniciam-se com a proposição de um modelo preliminar de ciclo de vida de ERP, considerando não haver distinções entre o modelo para um ERP proprietário ou livre. Refina-se este modelo inicial através da aplicação do método de pesquisa-ação em um trabalho de campo com a implantação de um ERP livre em uma organização brasileira. O principal resultado deste trabalho é um modelo final para adoção, seleção e implantação de ERP livres e proprietários. Nos processos de adoção e seleção, são destacadas as diferenças fundamentais para atender a ERP livres e proprietários. Em relação ao processo de implantação, não foram encontradas distinções significativas.