What can REDD+ Benefit Sharing Mechanisms learn from the European Rural Development Policy?

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Key messages

  1. Designing incentives to achieve multiple objectives
    • The Rural Development Policy (RDP) provides lessons for REDD+ in its implementation of a single financial instrument that can coherently attend to different country needs, priorities and contexts with streamlined monitoring and funding allocations.
    • Differentiated payment calculations [applied at different levels] can account for contextual conditions increasing the likelihood that beneficiaries will perceive compensation as equitable, which motivates them to participate and comply with the scheme, and support the delivery of the desired outcomes.
  2. Multi-level governance (MLG)
    • The RDP is at risk of being dominated by elite actors, especially when powers are decentralized and wider representation is not ensured. Elite capture is a common issue in forest management and requires specific attention within the context of REDD+ benefit distribution.
    • Although local level decision-making can enhance outcomes, evidence from the RDP suggests that overt top-down governance still prevents local actors from fully participating despite policy priorities to the contrary, even when local governance institutions are created. As such, REDD+ safeguards for procedural equity are important, but not necessarily sufficient, to counter these effects.
  3. Monitoring and evaluation
    • Despite a strong commitment to monitoring, as impact indicators remain elusive, the available RDP output indicators currently provide only superficial insights into policy performance and are limited in their ability to assess the quality of activities in practice. Proxy indicators are needed, particularly for measuring the long-term outcomes and co-benefits of REDD+.
    • The RDP’s consistent monitoring and evaluation system is a strength that could be applied to REDD+. A qualitative evaluation approach should also be considered to complement quantitative indicators, account for data gaps, and capture other intangible policy/project aspects.


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