Inviting oversight: Effects of forest certification on deforestation in the Brazilian Amazon

Pushpendra Rana and Erin O. Sills

World Development, 2024, vol. 173, issue C

Abstract: In the American tropics, logging is almost always highly selective, leaving most of the forest standing and available for future harvest under sustainable forest management. However, forest that has been logged is often more accessible to deforestation agents such as farmers. Thus, areas legally designated for sustainable forest management in reality may be more susceptible to illegal deforestation. Third-party certification of sustainable forest management is one strategy for protecting such forest. In this paper, we estimate the effect of certification by the Forest Stewardship Council (FSC) on deforestation, drawing on data from the years 2001 to 2019. We observe strong selection effects resulting in systematic differences between certified forest areas and other forest areas designated for sustainable forest management, and we find that after controlling for those selection effects, inviting oversight by FSC reduces the probability of deforestation. Our study design compares forests “treated” with FSC certification to “control” forests designated for sustainable forest management but not (yet) certified in the two Brazilian states of Pará and Rondônia. Adopting pixel-based analyses, we first create a matched sample of treated and control pixels and then estimate GLMM models, with two-way fixed effects (TWFE) models as a robustness check.We find that where forest managers have obtained certification and thus invited oversight by FSC auditors, rates of forest loss are lower (although the results are not fully robust across regions). The estimated effects vary across regions, likely due to varying socioeconomic and policy contexts and competing land uses. We conclude that especially in settings of low governance capacity and high deforestation pressure, certification can contribute to long-term forest conservation by reducing deforestation rates.

Keywords: Forest certification; Deforestation; Brazilian Amazon; GLMM models; Pixel-based (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:wdevel:v:173:y:2024:i:c:s0305750x2300236x

DOI: 10.1016/j.worlddev.2023.106418

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