Efficiency-Based Peer Analysis for Targeted Extension to Improve Productivity among Ugandan Dairy Farmers
Copyright © 2026 Elizabeth Ahikiriza, Guido V Van Huylenbroeck, Ludwig Lauwers. Published by Nan Yang Academy of Sciences Pte. Ltd.
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
Abstract
In sub-Saharan Africa, targeting on-farm extension can support farmers to increase agricultural productivity. To achieve a targeted extension system, it is crucial to be able to assign contact farmers who can act as role models for follower farmers. Given the importance of productivity increase, frontier analysis can help to define benchmarks for selecting contact farmers. However, in countries transitioning from subsistence to more commercialized production systems, this benchmarking needs to take into account the heterogeneity among farms and farming systems. This paper evaluates the potential of peer outcomes from two non-parametric frontier analysis techniques (Free Disposable Hull, FDH, and Data Envelopment Analysis, DEA) for their suitability to generate possible benchmarks in the case of Ugandan dairy farming. To account for the existing transitional heterogeneity of small subsistence, large extensive and medium intensive farming systems, meta-frontier analysis is compared with separated technology-specific analyses. Data from 471 dairy farmers were analysed using output-oriented efficiency models that used land, the number of dairy cows and labour as inputs and milk as a single output. Results confirmed that the non-convex FDH yields more realistic peers than the convex DEA. Comparing meta-frontier and technology-specific outcomes indicates that peers do not necessarily come from similar production systems, because in particular large extensive farming systems proved to be inferior to the two other systems. A detailed peer analysis revealed that the FDH and DEA frontiers are complementary in suggesting benchmarks. The non-convex frontier better captures heterogeneity, while the convex DEA has some advantage in exploring inter-technology benchmarks.
Keywords: Benchmarking, Contact Farmers, Follower Farmers, Frontier Analysis, Transition, Sub-Saharan Africa
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