The Dynamics of Farmer Regeneration and Mechanization Intensity: An Econometric Modeling of the Impact of Youth Labor Scarcity on Agricultural Machinery Adoption Based on the 2023 Agricultural Census

Authors

  • Nasrullah Universitas Borobudur

DOI:

https://doi.org/10.70076/apj.v1i4.156

Keywords:

Agricultural Mechanization, Farmer Regeneration, Labor Scarcity, 2023 Agricultural Census, Induced Innovation, Econometric Modeling, Rural-Urban Migration, Food Security, Technological Literacy, Indonesia

Abstract

The structural transformation of Indonesia’s agrarian sector has triggered a demographic crisis marked by a significant decline in youth participation in agriculture. This study examines the relationship between stagnant farmer regeneration and rising mechanization intensity, focusing on how youth labor scarcity drives agricultural technology adoption. Using an econometric framework, the analysis integrates secondary data from the 2023 Agricultural Census and the 2020 Population Census Long Form. Regression models are applied to data from 514 regencies to assess the impact of demographic imbalance on mechanization uptake. The results reveal a strong positive association between labor scarcity and mechanization (p < .001), particularly in major production regions dominated by elderly farmers. Empirical estimates indicate that a 10% reduction in youth labor participation increases mechanized service utilization by 4.12%, confirming machinery as a functional substitute for human labor in aging rural economies. The study concludes that although demographic pressure accelerates technological adoption, its effectiveness depends on managerial capacity and targeted government support. These findings provide policy-relevant insights for achieving food sovereignty through demographically adaptive agricultural transformation.

References

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Published

2024-10-07

How to Cite

Nasrullah. (2024). The Dynamics of Farmer Regeneration and Mechanization Intensity: An Econometric Modeling of the Impact of Youth Labor Scarcity on Agricultural Machinery Adoption Based on the 2023 Agricultural Census. Agricultural Power Journal, 1(4), 37–47. https://doi.org/10.70076/apj.v1i4.156