Are REDD projects pro-poor in their spatial targeting? Evidence from Kenya

Reducing emissions from deforestation and forest degradation (REDD) is globally supported as a cost effective programme that could achieve global mitigation and spur pro-poor socioeconomic development. Various actors are now actively lobbying and disbursing REDD demonstration funds on the premise of spurring pro-poor carbon investments in less developed areas that were otherwise excluded from the Clean Development Mechanism. In practice, little is known as to whether the REDD projects are actually pro-poor in their spatial targeting. This paper focuses on Kenya to analyse the distribution of REDD projects across quantified subnational vulnerability indices. A vulnerability index map for Kenya was first developed from long-term socioeconomic (crop yields, literacy rates and poverty rates) and climate (rainfall) data drawn from the 47 counties of Kenya. The number and types of REDD projects were located on the vulnerability map. Correlation tests were performed and experts consulted to clarify the socioeconomic features of vulnerability that significantly influence spatial choices for the projects. Results show that most projects are located in low-vulnerability counties and are mainly developed and managed by international private and consulting companies. Correlation tests revealed that the low-vulnerability counties, hosting more projects, are endowed with humid forest resources at .728; p<0.01, land title deeds at .552; p<0.01 and better access to water at .475; p<0.01. Experts suggested that such conditions posit low transaction costs and higher carbon revenues for profit-seeking project developers that currently dominate the REDD demonstrations. Conversely, some project experiences indicate that medium to high-vulnerability areas e.g. dry-lands with mitigation potential, enable projects to have low opportunity costs and explicit livelihood impacts. By directing REDD funds to relatively vulnerable areas, projects and national REDD policies are likely to enhance synergies between mitigation and adaptation. More targeted field assessment of the interaction between projects and local socioeconomic conditions can be formulated from this study