Naming and Shaming for Conservation: Evidence from the Brazilian Amazon - Cisneros, E.; Zhou, S.L.; Börner, J. (Public Library of Science, 2015)
Deforestation in the Brazilian Amazon has dropped substantially after a peak of 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 additional administrative hurdles to obtain authorization for clearing forests. In this paper we add to the existing literature on evaluating the Brazilian anti-deforestation policies by specifically quantifying the impact of blacklisting on deforestation. We first use spatial matching techniques using a set of covariates that includes official blacklisting criteria to identify control districts. We then explore the effect of blacklisting on change in deforestation in double difference regressions with panel data covering the period from 2002 to 2012. Multiple robustness checks are conducted including an analysis of potential causal mechanisms behind the success of the blacklist. We find that the blacklist has considerably reduced deforestation in the affected districts even after controlling for the potential mechanism effects of field-based enforcement, environmental registration campaigns, and rural credit.