An Assessment Of Youth Agripreneurship And The Adoption Of Smart Farming Technologies For Sustainable Rice Production In Adamawa State: A Spatial Regression Approach

• Adamu Jibrilla

  Adamawa State University, Mubi, Faculty of Social Sciences, Communication and Media Studies, Department of Economics-Nigeria

  Author

• Hamisu Ali

  Adamawa State University, Mubi, Faculty of Social Sciences, Communication and Media Studies, Department of Economics-Nigeria

  Author

• Babangida Adamu

  Adamawa State University, Mubi, Faculty of Social Sciences, Communication and Media Studies, Department of Economics-Nigeria

  Author

Youth agripreneurship is increasingly recognized as a viable strategy for enhancing agricultural productivity, promoting rural employment, and achieving sustainable food systems in Nigeria. This study assesses youth participation in rice agripreneurship and the adoption of smart farming technologies in Adamawa State, explicitly accounting for spatial dependence in production outcomes. Using cross sectional data from 384 youth rice agripreneurs across Adamawa State, the study applies spatial econometric techniques, including the Spatial Autoregressive Model (SAR), Spatial Error Model (SEM), and Spatial Durbin Model (SDM), to examine both direct and spillover effects. The results indicate strong and statistically significant spatial dependence in youth rice production, with the spatial autoregressive coefficient (ρ) ranging from 0.29 to 0.41 across models (p < 0.01), confirming the presence of productivity spillovers among neighbouring farming communities. Farm size (β ≈ 0.38, p < 0.01), labour input (β ≈ 0.21, p < 0.05), capital investment (β ≈ 0.27, p < 0.01), and access to agricultural credit (β ≈ 0.19, p < 0.05) consistently exhibit positive effects on rice output. Adoption of smart farming technologies significantly enhances productivity, particularly the use of precision farming tools (β ≈ 0.24, p < 0.01), access to smart farm inputs (β ≈ 0.31, p < 0.01), and participation in smart agriculture training (β ≈ 0.17, p < 0.05). Evidence from the SDM further reveals positive indirect effects of neighbouring farmers’ technology adoption, highlighting spatial diffusion and peer learning processes. The study concludes that youth rice agripreneurship in Adamawa State is both input-driven and spatially interconnected, with smart farming technologies playing a critical role in enhancing sustainable production. The study recommends that policy interventions that promote technology access, youth-focused credit schemes, and spatially coordinated extension services are therefore essential for maximizing productivity gains and sustainability outcomes.

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