Environmental policy’s new role in the Brazilian Amazon


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After major reductions, field-based enforcement still exerts significant and sizeable negative effects on deforestation at the local scale; Reason may not be the fine itself, but the host of economic implications that arise from having received one (embargo, etc.); Signs of “avoidance behavior”, i.e. small-scale deforestation increasing in response to enforcement that targets large-scale deforestation less pronounced than suggested by previous analyses; Average operational costs per fine are at about R$4650 and thus probably still lower than the environmental benefit of avoided deforestation measured at carbon offset price values

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Environmental policy’s new role in the Brazilian Amazon

  1. 1. Environmental policy’s new role in theBrazilian AmazonJan Börner (UniBonn/CIFOR)Jorge Hargrave (IPEA)Krisztina Kis-Katos (Freiburg University)Konstantin König (ICRAF)Monique Sacardo Ferreira (IPEA)
  2. 2. Background• Deforestation ratespeaked in 2004• Command-and-Control policyconsidered largelyineffective• Broad changes ingovernance system in2004/5 (PPCdAM)• Since then reductionsby over two thirds0500010000150002000025000300002004200520062007 2008200920102011yearsDeforestation(sq.km) 0100020003000400050006000700080009000Numberoffines
  3. 3. Background• Shift from large to smaller scale deforestation:result of enforcement strategy (Rosa et al.2012) or structural change (Pacheco 2011)?Rosa et al. 2011
  4. 4. Research questions1. Districts with high fine intensity were focus ofmany complementary measures (e.g.embargoes, exclusion from credit, etc.). Whatis the deterrence effect of an individual fine(field-based enforcement)?2. Does targeting field operations towards large-scale deforestation induce „avoidancebehavior“, e.g., an increase in small-scaledeforestation?
  5. 5. 2010 fine locations and 2010/11change in deforestation
  6. 6. Empirical strategy• Grid-based approach– Measurement of all covariates at 20x20km resolution– Measurement of fine (location) and deforestation at<=10x10 km resolution• Matching analysis– Pooling of 2010 and 2011 observation periods– Exclusion of non-treated neighbors of treated gridcells to reduce neighborhood effects– Stratification by fine type (all fines vs onlydeforestation fines)– Analysis for small versus large-scale (>20ha*)deforestation– Problems: clouds and imprecise fines* Minimum detection of DETER monitoring system
  7. 7. Cloud and/or Deforestation?20102011PRODES-Deforestation PRODES-Clouds PRODES + DETER -Deforestation
  8. 8. Imprecisely measured fines0204060800. 44%Imprecise (56%)
  9. 9. Matching full set of covariatesembForest2007acc_defCloudsClouds_laggedprodes_lagprod_splagt1DISTANCIADISTANCIAsqMUNimpreciseTI_percentUCAssentasmallshsh_high_lagagrshpastshtractor_wPrec_annShare.owners-1 -0.5 0 0.5 1unmatchedmatched MHDmatched INVStandardized difference in means
  10. 10. Matching (change indeforestation)ATT AI SE / AI p Number oftreated cellsAll fine types / all cells -2.98 2.18 / 0.171 2848All fine types / excludingneighbors-4.39 2.21 / 0.047 2848Only deforestation fines -8.21 4.33 / 0.058 614Only deforestation finesno clouds-8.42 5.31 / 0.113 410Only deforestation finesno clouds >20ha patches-10.59 4.72 / 0.024 410Only deforestation finesno clouds <20ha patches2.17 2.21 / 0.328 410
  11. 11. Matching (share of deforestationpatches > 20ha)ATT AI SE / AI p Number oftreated cellsAll fine types / excludingneighbors0.02 0.01 / 0.051 2848Only deforestation fines 0.01 0.02 / 0.493 614Only deforestation finesno clouds0.01 0.02 / 0.518 410
  12. 12. Key findings• Significant deterrence effects of fines issued infield-based enforcement campaigns• On average a single additional fine reducesdeforestation by 10-20% in the subsequent year• Effects vary across states (different dynamics ofconfounding factors)• Only limited evidence for “avoidance behavior”
  13. 13. Caveats• Clouds, imprecisely measured fines, andunobserved state-level action remain notfully controlled confounding factors• Balance on past deforestation cannot befully achieved with full set of covariates• Further robustness tests pending
  14. 14. Conclusions• After major reductions, field-based enforcement stillexerts significant and sizeable negative effects ondeforestation at the local scale• Reason may not be the fine itself, but the host ofeconomic implications that arise from havingreceived one (embargo, etc.)• Signs of “avoidance behavior”, i.e. small-scaledeforestation increasing in response to enforcementthat targets large-scale deforestation lesspronounced than suggested by previous analyses• Average operational costs per fine are at aboutR$4650 and thus probably still lower than theenvironmental benefit of avoided deforestationmeasured at carbon offset price values
  15. 15. THANK YOU