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All Journal International Journal of Mechanical, Electrical and Civil Engineering Journal of Humanities, Social Sciences, and Education INTELEKTUAL: JURNAL ILMIAH MULTIDISIPLIN MAHASISWA DAN AKADEMISI AGRONES: JOURNAL OF AGRICULTURE, AGRIBUSINESS WELFARE, TECHNOLOGI, HUMANITY, ENVIRONMENT, SOCIAL AND ECONOMY
La Harudin
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Nursing Social Sciences Other

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Technical and Economic Efficiency in Farming: A Literature Study Using the DEA and Frontier Production Approaches La Harudin
Journal of Agriculture, Agribusiness, Welfare, Technology, Humanity, Environment, Social, and Economy Vol. 1 No. 1 (2025): April 2025 Edition
Publisher : Fakultas Teknologi Pertanian Unsultra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64690/agrones.v1i1.271

Abstract

Technical and economic efficiency are key indicators in evaluating farm performance, particularly in the context of limited land resources, input constraints, and the challenges posed by climate change. This study aims to systematically review existing literature that employs Data Envelopment Analysis (DEA) and Frontier Production Function approaches particularly Stochastic Frontier Analysis (SFA) to measure farm efficiency in Indonesia and other developing countries. DEA provides a non-parametric means of assessing technical efficiency without assuming a specific production function, whereas frontier approaches offer parametric analysis by incorporating random disturbances in the production process. Based on a review of 20 selected articles, the findings reveal that farmers' technical efficiency generally ranges from 60% to 85%, while economic efficiency tends to be lower due to input-output price imbalances and limited access to market information. Key factors influencing efficiency include farmers’ education level, farm size, technology adoption, and participation in farmer groups. This study highlights the strengths of these quantitative approaches as data-driven tools for agricultural policy formulation at both micro (farm) and macro (national policy) levels. The findings underscore the importance of integrating DEA and SFA methods to provide a more comprehensive picture of farm performance. Enhancing efficiency thus requires a combination of technical training, agricultural digitalization, and the development of inclusive policies that support smallholder farmers in a sustainable manner.
Co-Authors Abdul Rizal Adrianus Adrianus Anwar Anwar David Oscar Simatupang Haerudin Tao Hasriati Hasriati La Panga Mani Yusuf Nurmaya Nurmaya