Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.

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 district...

Full description

Bibliographic Details
Main Authors: Elías Cisneros, Sophie Lian Zhou, Jan Börner
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4580616?pdf=render
id doaj-56017e74d2664cff95e42f86f0a19825
record_format Article
spelling doaj-56017e74d2664cff95e42f86f0a198252020-11-24T21:24:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01109e013640210.1371/journal.pone.0136402Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.Elías CisnerosSophie Lian ZhouJan BörnerDeforestation 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.http://europepmc.org/articles/PMC4580616?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Elías Cisneros
Sophie Lian Zhou
Jan Börner
spellingShingle Elías Cisneros
Sophie Lian Zhou
Jan Börner
Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.
PLoS ONE
author_facet Elías Cisneros
Sophie Lian Zhou
Jan Börner
author_sort Elías Cisneros
title Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.
title_short Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.
title_full Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.
title_fullStr Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.
title_full_unstemmed Naming and Shaming for Conservation: Evidence from the Brazilian Amazon.
title_sort naming and shaming for conservation: evidence from the brazilian amazon.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description 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.
url http://europepmc.org/articles/PMC4580616?pdf=render
work_keys_str_mv AT eliascisneros namingandshamingforconservationevidencefromthebrazilianamazon
AT sophielianzhou namingandshamingforconservationevidencefromthebrazilianamazon
AT janborner namingandshamingforconservationevidencefromthebrazilianamazon
_version_ 1725989167372959744