Optimal Environmental Targeting in the Amazon Rainforest
This paper sets out an empirically-driven approach for targeting environmental policies optimally in order to combat deforestation. We focus on the Amazon, the world's most extensive rainforest, where Brazil's federal government issued a ‘Priority List’ of municipalities in 2008, to be targeted with more intense environmental monitoring and enforcement. In this setting, we first estimate the causal impact of the Priority List on deforestation using ‘changes-in-changes’ (Athey and Imbens, 2006), a flexible treatment effects estimation method, finding that it reduced deforestation by 40 percent and cut emissions by 39.5 million tons of carbon. Second, we develop a novel framework for computing targeted ex-post optimal blacklists. This involves a procedure for assigning municipalities to a counterfactual list that minimizes total deforestation subject to realistic resource constraints, drawing on the ex-post treatment effect estimates from the first part of the analysis. Accounting for spillovers, we show that the ex-post optimal list resulted in carbon emissions over 7.4 percent lower than the actual list, amounting to savings of more than $900 million, and emissions over 25 percent lower (on average) than a randomly selected list. The approach we propose is relevant for assessing both targeted counterfactual policies to reduce deforestation and quantifying the impacts of policy targeting more generally.
We would like to thank Fernanda Brollo, Sylvain Chabe-Ferret, Francisco Costa, Clarissa Gandour, Kelsey Jack, Charles Manski, Ismael Mourifié, Marcel Oestreich, Martino Pelli, Alex Pfaff, Alberto Salvo, Paul Scott, Edson Severini, Kate Sims, and Aloysius Siow for helpful discussions, and workshop participants at Brock University, the Instituto Escolhas, the 2018 LSE-NHH Conference, the Montreal Workshop in Environmental and Resource Economics, the 2018 NBER Summer Institute, the INRA Environmental and Natural Resources Conservation Workshop in Montpellier, Toulouse School of Economics, the University of Ottawa, the University of Toronto, and the 6th World Congress of Environmental and Resource Economists for additional comments. Faisal Ibrahim provided outstanding research assistance. Financial support from the University of Toronto Mississauga is gratefully acknowledged. Assunção is gratefully thankful for financial support from the CNPq. All remaining errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research or their respective organizations.