Addressing Contextual and Location Biases in the Assessment of Protected Areas Effectiveness on Deforestation in the Brazilian Amazônia
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2017
- handle: 10670/1.viggfi
- halshs: halshs-01479031
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Eric Nazindigouba Kere et al., « Addressing Contextual and Location Biases in the Assessment of Protected Areas Effectiveness on Deforestation in the Brazilian Amazônia », HAL-SHS : économie et finance, ID : 10670/1.viggfi
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Résumé
Using a remotely sensed pixel data set, we develop a multilevel model and propensity scoreweighting with multileveldata to assess the impact of protected areas on deforestation in the Brazilian Amazon. These techniquesallow taking into account location bias, contextual bias and the dependence of spatial units. Our results showthat the hierarchical structure of the database matters and should be considered in the assessment of protectedareas effectiveness. Our results also suggest that protected areas have slowed down deforestation between 2005and 2009, whatever the type of governance. The effectiveness of protected areas differs according to socioeconomicand environmental variables measured at municipal level. For instance, indigenous protected areas arefound to be marginally more efficient than sustainable use areas and integral use areas. Protected Areas thatwere more recently implemented are also found to avoid more deforestation than older ones. This corroboratesthe idea that recently created protected areas in the Brazilian Amazon have a greater agricultural potential.