Spillover effects of blacklisting policy in the Brazilian Amazon

Abstract

Este trabalho avalia os efeitos da Lista de Municípios Prioritários, que indica os principais alvos de fiscalização da autoridade ambiental, sobre o desmatamento dos municípios na vizinhança dos listados. Argumenta-se que ter um vizinho listado causa uma variação exógena na presença das autoridades ambientais, e um estimador de diferença-em-diferenças é usado para determinar o impacto dessa presença sobre o desmatamento. Uma contribuição deste trabalho é acrescentar uma versão espacial do estimador para corrigir a dependência espacial na variável dependente. Nossos resultados mostram que o efeito líquido do tratamento é reduzir o desmatamento entre 19% e 23%, e que esse efeito enfraquece à medida que a distância até o município prioritário aumenta.

Optimal Environmental Targeting in the Amazon Rainforest

“…This type of targeted strategy can be applied in other contexts that encompass a substantial portion of global rainforest cover -in other parts of Amazonia, the Congo and Southeast Asia. 13 Within the Amazon context, recent papers have examined the effects of the Priority List, including Arima et al (2014), Cisneros et al (2015), Andrade and Chagas (2016), Harding et al (2018), Koch et al (2018), and Assunção and Rocha (2019). Those studies use difference-indifferences and matching methods to obtain average treatment effects similar in magnitude to the corresponding estimates in our study.…”

Leakage and boosting effects in environmental governance: a framework for analysis

“…Richards (2015), Pfaff and Robalino (2017), Hertel (2018) Changes in output prices: land-use restrictions tend to reduce agricultural or forestry output, raising prices and creating incentives for raising production elsewhere However, learning may also take place at the institutional level, leading to the diffusion of policies across jurisdictions (Stone 2001, Holzinger et al 2008. For instance, De Andrade and Chagas (2018) show that transfer of information from Brazilian municipalities blacklisted by the government for their high deforestation rates to neighboring municipalities had the effect of lowering deforestation also in the latter. Another well-described example of institutional learning is the 'latecomer effect', where institutional actors who confront a given problem following other actors can learn from these other actors to exhibit higher clarity of purpose, wield concentrated power, and accomplish their ends faster (Rudel et al 2019).…”

Forest Wars: A Trilogy on Combating Deforestation in the Brazilian Amazon

“…Although stricter enforcement has been shown to have significantly reduced Amazon forest clearings (Hargrave and Kis-Katos, 2013;Assunção et al, 2017b), it is the priority municipalities policy that, among all action plan efforts, has received most attention in the enforcement spillover literature. Results are mixed, with Cisneros et al (2015) finding no evidence of the policy's deterrent effect on priority municipalities' neighbors, but both Andrade (2016) and Assunção et al (2018b) documenting significant reductions in non-priority municipalities located near priority ones. To the best of my knowledge, this is the first assessment of tropical regeneration as a spillover of PPCDAm policies, and of law enforcement specifically, as well as the first study in the economic literature to explore the rich spatial data recently released on land use in Amazon deforested areas.…”