Using publicly available social and spatial data to evaluate progress on REDD+ social safeguards in Indonesia

Countries are grappling with how to monitor and evaluate the social impacts of reducing emissions from deforestation and forest degradation (REDD+) at national and sub-national scales as they develop REDD+ safeguard information systems (SIS). Given limited resources for social safeguard measuring, reporting and verification (MRV), and the fact that REDD+ is a performance based mechanism requiring monitoring over the medium to long-run, there is a need to develop SIS that are low cost, rigorous, and sustainable over time. Of critical importance are approaches that adequately operationalize social safeguards, provide opportunities for ongoing MRV, and are feasible in terms of within country human and financial capital. In this paper we provide an illustration of how publicly available social and spatial data can be used for the quantitative evaluation of the social impacts of early REDD+ activities using the example of Kalimantan, Indonesia.

Our analysis suggests that in the very early stages REDD+ projects are doing a reasonably good job of protecting rights (Safeguard #3), and are having a negative impact on human welfare (Safeguard #5). Other social safeguards could not be effectively evaluated due to lack of appropriate indicators in publicly available population representative datasets. Our experience suggests that there are several opportunities and challenges for countries as they move forward with REDD+ SIS. We find that for Indonesia there is sufficient data to estimate impacts for some, but not all, aspects of REDD+ social safeguards. More recently collected data have greater potential for the linking of social and spatial datasets, and fairly straight forward matching methods can be applied to construct appropriate treatment and comparison groups. Challenges include limited ability to operationalize some safeguards using existing data sources, lack of geo-referencing in several publicly available datasets, incompatibility of data layers in terms of their spatial and temporal resolution and frequency, and the complexity of generating appropriate counterfactual scenarios. Despite the limitations of existing data sources, we recommend against designing entirely new systems for REDD+ SIS. Strengthening ongoing national and sub-national data collection efforts to include appropriate geo-referenced indicators for the full range of REDD+ social safeguard indicators, and integration of carbon and social MRV systems are important avenues to explore.

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