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Addressing Contextual and Location Biases in the Assessment of Protected Areas Effectiveness on Deforestation in the Brazilian Amazônia

Author

Listed:
  • Eric Nazindigouba Kere

    (ECMR - Macroeconomics Policy, Forecasting and Research Department - African Development Bank)

  • Johanna Choumert

    (EDI - Economic Development Initiatives - Economic Development Initiatives)

  • Pascale Combes Motel

    (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

  • Jean-Louis Combes

    (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

  • Olivier Santoni

    (FERDI - Fondation pour les Etudes et Recherches sur le Développement International)

  • Sonia Schwartz

    (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

Abstract

Using a remotely sensed pixel data set, we develop a multilevel model and propensity scoreweighting 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. Our results show that the hierarchical structure of the database matters and should be considered in the assessment of protected areas effectiveness. Our results also suggest that protected areas have slowed down deforestation between 2005 and 2009, whatever the type of governance. The effectiveness of protected areas differs according to socioeconomic and environmental variables measured at municipal level. For instance, indigenous protected areas are found to be marginally more efficient than sustainable use areas and integral use areas. Protected Areas that were more recently implemented are also found to avoid more deforestation than older ones. This corroborates the idea that recently created protected areas in the Brazilian Amazon have a greater agricultural potential.

Suggested Citation

  • Eric Nazindigouba Kere & Johanna Choumert & Pascale Combes Motel & Jean-Louis Combes & Olivier Santoni & Sonia Schwartz, 2017. "Addressing Contextual and Location Biases in the Assessment of Protected Areas Effectiveness on Deforestation in the Brazilian Amazônia," Post-Print halshs-01479031, HAL.
    • Handle: RePEc:hal:journl:halshs-01479031
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    Citations

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    Cited by:

    1. Sébastien Desbureaux, 2016. "Common Resources Management and the "Dark Side" of Collective Action: an Impact Evaluation for Madagascar’s Forests," Working Papers 2016.30, FAERE - French Association of Environmental and Resource Economists.
    2. Amin, A. & Choumert-Nkolo, J. & Combes, J.-L. & Combes Motel, P. & Kéré, E.N. & Ongono-Olinga, J.-G. & Schwartz, S., 2019. "Neighborhood effects in the Brazilian Amazônia: Protected areas and deforestation," Journal of Environmental Economics and Management, Elsevier, vol. 93(C), pages 272-288.
    3. Apeti, Ablam Estel & N’Doua, Bossoma Doriane, 2023. "The impact of timber regulations on timber and timber product trade," Ecological Economics, Elsevier, vol. 213(C).
    4. Reynaert, Mathias & Souza-Rodrigues, Eduardo & van Benthem, Arthur A., 2024. "The environmental impacts of protected area policy," Regional Science and Urban Economics, Elsevier, vol. 107(C).
    5. Li, Yi & Song, Zhenjiang, 2022. "Have protected areas in China achieved the ecological and economic “win-win” goals? Evidence from the Giant Panda Reserves of the Min Mont Range," Forest Policy and Economics, Elsevier, vol. 144(C).
    6. Keles, Derya & Delacote, Philippe & Pfaff, Alexander & Qin, Siyu & Mascia, Michael B., 2020. "What Drives the Erasure of Protected Areas? Evidence from across the Brazilian Amazon," Ecological Economics, Elsevier, vol. 176(C).
    7. Rousselière, Damien & Bouchard, Marie J. & Rousselière, Samira, 2024. "How does the social economy contribute to social and environmental innovation? Evidence of direct and indirect effects from a European survey," Research Policy, Elsevier, vol. 53(5).
    8. Ablam Estel Apeti & Bossoma Doriane N’doua, 2023. "The impact of timber regulations on timber and timber product trade," Post-Print hal-04262489, HAL.
    9. Tacconi, Luca & Rodrigues, Rafael J. & Maryudi, Ahmad, 2019. "Law enforcement and deforestation: Lessons for Indonesia from Brazil," Forest Policy and Economics, Elsevier, vol. 108(C), pages 1-1.

    More about this item

    Keywords

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    JEL classification:

    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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