Thesis: Examining Implementation of REDD+ Projects in Indonesia from Economic Perspectives
This research aims to contribute toward an understanding of preferred mechanisms to implement REDD+ in different social, economic, ecological, and institutional contexts by examining local people’s preferences and participation in REDD+ activities. To achieve this research aim, the following objectives will be explored: 1) To identify key factors affecting household’s perception of and participation in existing REDD+ activities under different implementation contexts, 2) To understand local preferences on REDD+ scheme for developing further REDD+ design, 3) To examine REDD+ net benefits at a local level, under different implementation contexts. This study stands on a general framework for analysing sustainability of social-ecological systems adapted to REDD+ implementation contexts. Household surveys are conducted in three REDD+ project areas in Indonesia representing three REDD+ implementation contexts. The study utilizes quantitative and qualitative approaches, including ordered probit/logit models, market and non-market valuation techniques (cost-benefit analysis and discrete choice experiment).
Why my research is important
Reducing Emission from Deforestation and Forest Degradation - Plus (REDD+) is perceived as a good option to adapt to climate change and mitigate greenhouse gas (GHG) emissions, since the forestry sector contributes around 12-15% of global GHG emissions. However, forest s are not only ecosystems but also complex social-ecological systems. To achieve GHG emission reduction goals and co-benefits through REDD+ schemes, a sound understanding of the socio-ecological complexity is required. Knowledge on factors (social, economic and ecological) that affect REDD+ implementation and how they are connected is crucial to this understanding. This research’s novelty is contributing knowledge on how contextual differences in REDD+ implementation can influence local people’s perception of, participation in, and preferences for REDD+.