Diffusion and Growth Trajectories of Bio-Energy Crops in Agrarian Economies: An Extension and Production Analysis
Abhilasha Deepa Minz *
Department of Extension Education, ACG, Birsa Agricultural University, Garhwa-822114, India.
Kirti Kumud Binjha
Department of Agronomy, RAC, Birsa Agricultural University, Ranchi-834006, India.
*Author to whom correspondence should be addressed.
Abstract
The global transition towards sustainable bio-energy relies heavily on scaling dedicated energy feedstocks across agrarian economies. However, field-level adoption and yield optimisation depend on the strength of public agricultural extension infrastructure. This study evaluates the diffusion, yield productivity, and public extension efficiency associated with primary bio-energy feedstocks (sugarcane, cassava, maize, and oil palm) across 45 agrarian economies in Sub-Saharan Africa (SSA), South/Southeast Asia (SSEA), and Latin America & the Caribbean (LAC) from 2000 to 2023 using long-term FAOSTAT and ASTI panel data. Combining Bass innovation diffusion modelling, panel econometrics (Driscoll-Kraay and System-GMM), and Data Envelopment Analysis (DEA), we analyse macro-level adoption trajectories and technology transfer efficiency.
The results reveal that bio-energy output growth across all regions was predominantly driven by harvested area expansion (sugarcane CAGR 3.42% in LAC; oil palm CAGR 4.12% in SSEA) rather than intensive yield optimisation. Fitting the Bass model indicates a structural deficit in top-down institutional innovation drive (p) in SSA (p=.006) relative to LAC (p=0.028), forcing lower-income nations to rely on informal peer imitation (q) and delaying peak adoption (t^*≈2028). Fixed-effects panel regressions demonstrate a statistically significant positive yield elasticity with respect to lagged extension agent density (β=0.185, p<.001), indicating that a 10% increase in extension personnel per 10,000 workers is associated with a 1.85% increase in feedstock productivity per hectare. Furthermore, DEA efficiency scores reveal severe technical slacks in public advisory delivery in SSA (0.412) compared to LAC (0.842).
We conclude that scaling bio-energy crops sustainably requires moving beyond hardware input delivery towards strategic investment in extension human capital and modernised advisory networks to bridge persistent yield frontiers.
Keywords: Agricultural extension, bass diffusion model, Bio-energy feedstocks, panel econometrics, technology transfer, yield elasticity