Numerous initiatives to Reducing Emissions from Deforestation and Degradation (REDD) are emerging worldwide, particularly in countries prone to deforestation. Despite its recent reductions, Brazil remains among the top deforesting countries in the world where REDD initiatives could potentially have the most tangible returns for climate-change mitigation. This study develops a conceptual framework and a spatially explicit model to analyse regulatory enforcement of REDD in the context of the Brazilian Amazon. It validates the model’s performance based on 2002-9 historical deforestation and enforcement data. It analyses the costs of liability establishment and legal coercion for alternative REDD targets and evaluates welfare impacts in terms of land users’ opportunity costs.The paper presents the following findings and recommendations:

command-and control (C&C) measures in isolation constitute the most cost-effective REDD instrument
the cost-effectiveness of C&C enforcement differs by region
enforcement of the 80% REDD target could backfire for the development of regions depending heavily on the expansion of agriculture
the prospect of REDD raises equity issues in relation to the vulnerable
combining existing C&C sticks with payments for environmental services (PES) carrots could increase the political scope for REDD
institutional barriers to combining C&C with PES persist in the form of unclear tenure conditions
an optimal REDD policy mix therefore requires balancing cost-effectiveness and distributional equity
accelerating the process of land tenure delimitation and regularisation
removing administrative obstacles to effective enforcement
alternative forms to compensate land users for higher enforcement levels, like subsidised credit lines, certification, and technology development, will promote sustainable development but should be conditional on avoided deforestation.

In doing so, however, the author offers the following cautions regarding the enforcement model:

the linear relationship between fines and enforcement probabilities may produce misleading results, especially for very high fine levels
the nature of the enforcement-compliance game may change over multi-period iterations
the total C&C investment needs are somewhat underestimated
the approach assumes that compliance is binary whereas compliance decisions are continuous in reality
in the absence of adequate empirical observations the analysis ignores that deforestation in the Brazilian Amazon is the outcome of a pre-existing C&C disincentive
fines are used in this model merely as a currency for the size of the penalty required to induce compliance.

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Limiting land conversion & deforestation