Regional efficiency of forest-based bioelectricity in Brazil: A DEA and jackstrap approach for low-carbon bioeconomy planning

Brazil is a global leader in forest biomass production, which plays a strategic role in its renewable energy matrix and low-carbon transition. Forest-based bioelectricity offers a decentralized and renewable energy alternative, yet its regional performance remains underexplored. This study evaluates the efficiency of forest-based bioelectricity generation across 48 Brazilian Intermediate Regions with thermoelectric plants that operate on wood biomass. We apply output-oriented Data Envelopment Analysis (DEA) under both CCR and BCC models. To ensure robustness and mitigate the impact of outliers, we implement the jackstrap resampling method. The results reveal marked heterogeneity in technical and scale efficiency. Average naïve scores were 0.408 (CCR) and 0.519 (BCC), which dropped to 0.354 and 0.467 after robust correction, confirming the presence of overestimated efficiencies and influential DMUs. Benchmark networks constructed from DEA models highlight core regions such as Altamira, Bauru, and Rondonópolis that drive reference structures, while others exhibit structural inefficiencies or scale mismatches. These findings support targeted policy recommendations for infrastructure expansion, capacity optimization, and circular economy integration. The approach strengthens efficiency assessments for regional energy planning and offers transferable insights for biomass-based energy systems aligned with Sustainable Development Goals (SDGs 7, 9, and 12).