Abstract
AbstractCommunity Forest Management (CFM) devolves forest management to local communities to achieve conservation and human well‐being goals. Yet, the evidence for CFM's impacts is mixed and difficult to interpret because of inadequate attention to rival explanations for the observed empirical patterns. In a national‐scale analysis in Madagascar that carefully considers these rival explanations, we estimate CFM impacts on household living standards, as measured by per capita consumption expenditures. The estimated impact is positive, but small and not statistically different from zero. However, we can statistically reject substantial negative impacts (which others have suggested may exist). The estimated impacts vary conditional on household education and proximity to forests: they are more positive and statistically significant for households closer to forest and with more education. To help improve CFM design, scholars and practitioners should anticipate heterogeneity in CFM impacts and work to better characterize them, theoretically and empirically.
Highlights
Community Forest Management (CFM) is one of the most widespread conservation approaches in developing countries
We investigate the impacts of CFM in Madagascar on household living standards, as measured by household consumption expenditures
CFM households are defined as households within a commune that has 10% or more of its area covered by CFM; we performed a sensitivity test using a threshold of 25%
Summary
Community Forest Management (CFM) is one of the most widespread conservation approaches in developing countries. It can play an important role in the climate mitigation mechanism reducing emissions from deforestation and degradation REDD+ (Newton et al 2015). CFM advocates suggest that it can avoid the negative impacts of forest protection on the well-being of local communities (Behera 2009). Well-designed studies evaluating the impacts of CFM on human wellbeing are needed to better direct future efforts. One challenge is that conservation interventions are rarely randomly assigned. In studies of CFM impacts on well-being, these confounders are rarely identified and controlled (Engel et al 2013)
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