Addressing Contextual and Location Biases in the Assessment of Protected Areas Effectiveness on Deforestation in the Brazilian Amazônia
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15 janvier 2016
- handle: 10670/1.5xjpv6
- halshs: halshs-01256600
info:eu-repo/semantics/OpenAccess
Mots-clés
Brazilian Legal Amazon Protected areas deforestation Impact analysis. C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q2 - Renewable Resources and Conservation/Q.Q2.Q23 - Forestry Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q2 - Renewable Resources and Conservation/Q.Q2.Q28 - Government Policy Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q57 - Ecological Economics: Ecosystem Services • Biodiversity Conservation • Bioeconomics • Industrial EcologySujets proches
Reserves (Protected areas)Citer ce document
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 : 10670/1.5xjpv6
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Résumé
Using a remotely sensed pixel data set, we develop a multilevel model and propensity score weighting with multilevel data to assess the impact of protected areas on deforestation in the Brazilian Amazon. These techniques allow taking into account location bias, contextual bias and the dependence of spatial units. The results suggest that protected areas have slowed down deforestation between 2005 and 2009, whatever the type of governance. The results also evidence that protected and unprotected areas do not share the same location characteristics. In addition, the effectiveness of protected areas differs according to socioeconomic and environmental variables measured at municipal level.