Measuring Technical Efficiency and Farmers’ Narrative of Jute Cultivation in Bangladesh
Abstract
Aim
The objective of this study is to evaluate the technical efficiency of jute farmers in Bangladesh and to examine their socioeconomic challenges by developing a Farmers’ Narrative Index (FNI) that links production efficiency with farmers’ experiences.
Material and methods
A quantitative field survey was conducted using a structured questionnaire informed by a literature review and reconnaissance survey. During March and April 2024, data were collected from 150 active jute farmers selected through convenience sampling across six upazilas in the Kushtia district, a central jute-producing region. Farmers were categorized by farm size. Technical efficiency was assessed using the stochastic frontier analysis (SFA) method. The FNI was developed to evaluate socioeconomic challenges and identify disparities using district-level survey data.
Results
The SFA results indicate that jute farmers exhibit a high average technical efficiency of 89%, reflecting nearly optimal utilization of existing technology. Fertilizer and irrigation significantly increased output, whereas higher seed costs were associated with reduced productivity. The FNI identified key regional disparities, highlighting primary challenges such as low market prices, water scarcity, and financial constraints. Favorable conditions, including good weather and NGO support, were also identified as factors enhancing yields.
Conclusion
The findings show that although jute farmers are technically efficient, their productivity is heavily limited by socioeconomic barriers. Consequently, policies that focus on input affordability, irrigation infrastructure, and market mechanisms are crucial. The FNI provides policymakers with a practical tool to identify vulnerable regions and customize support programs effectively, ultimately improving the sustainability and productivity of jute farming in Bangladesh.
© 2026 Kazi Mostafa Arif, Md Ariful Islam, Nahid Hasan, published by The Institute of Agricultural and Food Economics – National Research Institute
This work is licensed under the Creative Commons Attribution 4.0 License.