Economic feasibility of forest landscape restoration in Ethiopia: Evidence from a multi-scale cost-benefit analysis of institutional and farmer-led systems

Forest landscape restoration (FLR) is central to addressing land degradation, climate change, and rural livelihoods, yet large-scale implementation remains constrained by uncertainty about financial feasibility amid competing land-uses. Existing literature often underrepresents context-specific opportunity costs and cross-scale benefits, limiting the targeting of effective restoration incentives and investments. This study evaluates the financial feasibility of institutional restoration systems (82 forest plantations and 51 Assisted Natural Regeneration (ANR) sites) and farmer-led restoration systems (555 woodlots and 725 agroforestry sites) in Ethiopia, examining how opportunity costs and value-creation options (VCOs) shape economic land-use decisions. We apply a Benefit-Cost Analysis framework to assess four VCOs: technical efficiency improvement, low-interest credit, societal non-market benefits, and carbon credits on financial feasibility. The analysis integrates financial survey data, tree inventories, and contingent valuation per restoration options. Results show that opportunity costs fundamentally shape restoration financial viability and strategy choice. Agroforestry and short-rotation woodlots remain financially viable across contexts, whereas ANR, forest plantations, and mid- to long-rotation woodlots, become non-viable under high opportunity costs. Farm- and communal-level VCOs improve profitability but are generally insufficient to offset delayed returns in long-rotation systems. In contrast, carbon credit VCOs substantially enhance financial viability, particularly for longer investment horizons, although their effectiveness would depend on enabling market and institutional conditions. These findings suggest that restoration policies and investments should be differentiated by local opportunity costs and supported by appropriate tenure and benefit sharing arrangements. By integrating these dimensions, the study provides a scalable decision-support framework for prioritizing restoration investments, targeting incentives, and identifying economically feasible restoration pathways across heterogeneous land-use contexts.