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Leveraging Productivity Analysis for Smallholders’ Sustainable Development: Dairy Efficiency in Central Madagascar’s Crop-Livestock Family Farms

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Leveraging Productivity Analysis for Smallholders’ Sustainable Development: Dairy Efficiency in Central Madagascar’s Crop-Livestock Family Farms

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1
LEAF Research Unit, Terra Associated Laboratory, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal
2
Sustainable Societies Unit, School of Economics, University of Cape Town, Cape Town 7700, South Africa
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Received: 22 September 2025 Revised: 18 November 2025 Accepted: 17 December 2025 Published: 26 December 2025

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© 2025 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Rural Reg. Dev. 2026, 4(1), 10022; DOI: 10.70322/rrd.2025.10022
ABSTRACT: Milk production in developing African countries is a viable path for smallholders’ sustainable development. Supporting interventions should be shaped by evidence from comprehensive, context-specific analyses. Using survey data, this study contributes to the development-oriented literature on dairy productivity in African smallholder systems by conducting the first stochastic frontier analysis in the Malagasy context. Focusing on milk producers in central Madagascar’s crop-livestock family farms, a stochastic frontier production function with inefficiency effects is developed. The fitted frontier comprises the number of cows, annual purchased feed expenditure, farmer’s labor, and total household assets owned. Distance from the frontier is explained by the use of improved breeds, integration in the regional milk zone, farmer years of experience, the presence of off-farm income, and the number of oxen owned. Technical efficiency ranged from 4.6% to 90.8% around a mean of 55.5%. Results revealed how, in this context, cows are embedded in diversified family farming systems where resources are allocated across production activities and household needs. The study’s multidisciplinary stochastic frontier analysis provides a more complete picture to guide research and policy for smallholders’ sustainable rural development.
Keywords: AR4D; Development policy; Social indicators; Stochastic frontier analysis
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