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<p>This paper seeks to address the impact of farm mechanization on the net farm income level of the farmers of Eastern India. This study uses the survey data of 2638 farming households from the Eastern Indian states namely Bihar, Uttar Pradesh, Jharkhand, Odisha and West Bengal. To assess the impact of machinery adoption on the outcome variable, the Propensity Score Matching (PSM) method was employed and the probit model estimates revealed that crop diversification, access to credit, Govt. support, and market and extension facilities have positive and significant effects on the adoption of machines. The extent of mechanization was highest in Uttar Pradesh, followed by Jharkhand, West Bengal, Odisha and Bihar. The kernel matching and nearest neighbour matching estimates reveal that the adoption of machinery has increased net farm income by 18, 12 and 30 percent in the case of rotavators, threshers and motor pumps, respectively. Overall, the net farm income of the adopters increased by almost 20 percent compared to the non-adopters. Given these significant positive impacts of mechanization, it necessitates a multi-stakeholder approach linking the Government, research, education and extension facilities to deepen the design and demonstration of low-cost and scale-appropriate agricultural equipment.</p>

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Does Mechanization Improve Net Farm Income? Evidence from Household Survey in Eastern India

  • 期刊论文

  • 发表日期：

    2026年2月24日

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  • Soumya Mohapatra,
  • Anjani Kumar,
  • Sonali Katoch

摘要

This paper seeks to address the impact of farm mechanization on the net farm income level of the farmers of Eastern India. This study uses the survey data of 2638 farming households from the Eastern Indian states namely Bihar, Uttar Pradesh, Jharkhand, Odisha and West Bengal. To assess the impact of machinery adoption on the outcome variable, the Propensity Score Matching (PSM) method was employed and the probit model estimates revealed that crop diversification, access to credit, Govt. support, and market and extension facilities have positive and significant effects on the adoption of machines. The extent of mechanization was highest in Uttar Pradesh, followed by Jharkhand, West Bengal, Odisha and Bihar. The kernel matching and nearest neighbour matching estimates reveal that the adoption of machinery has increased net farm income by 18, 12 and 30 percent in the case of rotavators, threshers and motor pumps, respectively. Overall, the net farm income of the adopters increased by almost 20 percent compared to the non-adopters. Given these significant positive impacts of mechanization, it necessitates a multi-stakeholder approach linking the Government, research, education and extension facilities to deepen the design and demonstration of low-cost and scale-appropriate agricultural equipment.