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<p>Wheat is a strategic crop in Afghanistan, contributing significantly to food security, rural livelihoods, and economic stability. This research examines the substitution elasticity between labor and machinery in wheat production in the central regions of Baghlan province. Primary data were collected from 300 wheat farmers selected through simple random sampling. A translog cost function was estimated using seemingly unrelated regression equations (SURE) to analyze input substitution. The estimated Allen-Ozawa elasticity between labor and machinery is 2.96, indicating a strong substitutive relationship: a 1% increase in labor costs leads to a 2.96% decrease in machinery use. The Morishima elasticity further highlights substitution effects, with values of 1.25 and 0.95 for labor and machinery, respectively, confirming labor is more easily replaced by machinery than vice versa. Thus, rising labor prices drive a more substantial shift toward machinery adoption, while changes in machinery prices have a more negligible effect on labor use. These results highlight strong economic incentives for mechanization as labor costs rise. Agricultural policymakers and managers should prioritize investment in appropriate machinery and automation technologies to boost efficiency, lower costs, and support the region’s wheat farming sustainability and competitiveness.</p>

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Estimating substitution elasticities between labor and machinery in wheat production in Baghlan Province of Afghanistan

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月3日

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  • Hafizullah Radmand,
  • Habibullah Rezaei,
  • Ali Keramatzadeh,
  • Farshid Eshraghi

摘要

Wheat is a strategic crop in Afghanistan, contributing significantly to food security, rural livelihoods, and economic stability. This research examines the substitution elasticity between labor and machinery in wheat production in the central regions of Baghlan province. Primary data were collected from 300 wheat farmers selected through simple random sampling. A translog cost function was estimated using seemingly unrelated regression equations (SURE) to analyze input substitution. The estimated Allen-Ozawa elasticity between labor and machinery is 2.96, indicating a strong substitutive relationship: a 1% increase in labor costs leads to a 2.96% decrease in machinery use. The Morishima elasticity further highlights substitution effects, with values of 1.25 and 0.95 for labor and machinery, respectively, confirming labor is more easily replaced by machinery than vice versa. Thus, rising labor prices drive a more substantial shift toward machinery adoption, while changes in machinery prices have a more negligible effect on labor use. These results highlight strong economic incentives for mechanization as labor costs rise. Agricultural policymakers and managers should prioritize investment in appropriate machinery and automation technologies to boost efficiency, lower costs, and support the region’s wheat farming sustainability and competitiveness.