Forest Law enforcement through district blacklisting in the Brazlian Amazon

Deforestation in the Brazilian Amazon has dropped substantially after a peak at over 27 thousand square kilometers in 2004. Starting in 2008, the Brazilian Ministry of the Environment has regularly published blacklists of critical districts with high annual forest loss. Farms in blacklisted districts face stricter registration and environmental licensing rules. In this paper, we quantify the impact of blacklisting on deforestation. We first use spatial matching techniques using a large set of covariates to identify appropriate control districts. We then explore the effect of blacklisting on change in deforestation in double difference regression analyses using panel data covering the period from 2002-2012. Several robustness checks are conducted including an analysis of field-based enforcement missions as a potential causal mechanism behind the effectiveness of the blacklist. We find that the blacklist has considerably reduced deforestation in the affected districts even after controlling for in situ enforcement activities.


Issue Date:
2015
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/211547
Total Pages:
31
JEL Codes:
Q32; Q15; Q38; Q5; H43




 Record created 2017-04-01, last modified 2017-04-26

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