Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda
Agriculture is central to Rwanda's economy, supporting the livelihood of about 70% of the population and contributing significantly to GDP. Smallholder farmers face many production challenges such as limited use of modern inputs, low productivity, and vulnerability to climate change. Despite efforts...
| Autores principales: | , , |
|---|---|
| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2025
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/174560 |
| _version_ | 1855534318489698304 |
|---|---|
| author | Benimana, Gilberthe Uwera Warner, James Missiame, Arnold Kwesi |
| author_browse | Benimana, Gilberthe Uwera Missiame, Arnold Kwesi Warner, James |
| author_facet | Benimana, Gilberthe Uwera Warner, James Missiame, Arnold Kwesi |
| author_sort | Benimana, Gilberthe Uwera |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Agriculture is central to Rwanda's economy, supporting the livelihood of about 70% of the population and contributing significantly to GDP. Smallholder farmers face many production challenges such as limited use of modern inputs, low productivity, and vulnerability to climate change. Despite efforts like the Crop Intensification Program and the Smart Nkunganire System, which aim to en hance access to resources, agricultural productivity remains suboptimal for Rwanda smallholder farmers. This study seeks to identify specific sources of technical inefficiencies among smallholder farmers, focusing on the total value of farmer’s crop output. By using stochastic frontier analysis, a robust quantitative method for separating inefficiencies and random shocks, the study assessed
the overall technical efficiency of smallholder farmers in Rwanda and identified the key factors influencing crop output value. The analysis reveals that fertilizer use, pesticide application, labor, seed use, and land size are key drivers of crop output value. This research further indicates that farmers operate at only 45% of their potential productivity, given the same level of input and technology, highlighting substantial room for efficiency improvements to reach the optimal output value frontier. Furthermore, additional analysis emphasizes the critical role of socioeconomic factors in shaping technical efficiency. The findings highlight the need for targeted interventions to optimize resource utilization, streamline labor allocation and strengthen access to extension services and government initiatives aimed at boosting agricultural production value. These strategies can substantially improve technical efficiency, enabling farmers to achieve optimal crop output values and advancing Rwanda's agricultural development objectives. |
| format | Artículo preliminar |
| id | CGSpace174560 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Food Policy Research Institute |
| publisherStr | International Food Policy Research Institute |
| record_format | dspace |
| spelling | CGSpace1745602025-11-06T07:09:34Z Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda Benimana, Gilberthe Uwera Warner, James Missiame, Arnold Kwesi agriculture smallholders stochastic models crops agricultural development Agriculture is central to Rwanda's economy, supporting the livelihood of about 70% of the population and contributing significantly to GDP. Smallholder farmers face many production challenges such as limited use of modern inputs, low productivity, and vulnerability to climate change. Despite efforts like the Crop Intensification Program and the Smart Nkunganire System, which aim to en hance access to resources, agricultural productivity remains suboptimal for Rwanda smallholder farmers. This study seeks to identify specific sources of technical inefficiencies among smallholder farmers, focusing on the total value of farmer’s crop output. By using stochastic frontier analysis, a robust quantitative method for separating inefficiencies and random shocks, the study assessed the overall technical efficiency of smallholder farmers in Rwanda and identified the key factors influencing crop output value. The analysis reveals that fertilizer use, pesticide application, labor, seed use, and land size are key drivers of crop output value. This research further indicates that farmers operate at only 45% of their potential productivity, given the same level of input and technology, highlighting substantial room for efficiency improvements to reach the optimal output value frontier. Furthermore, additional analysis emphasizes the critical role of socioeconomic factors in shaping technical efficiency. The findings highlight the need for targeted interventions to optimize resource utilization, streamline labor allocation and strengthen access to extension services and government initiatives aimed at boosting agricultural production value. These strategies can substantially improve technical efficiency, enabling farmers to achieve optimal crop output values and advancing Rwanda's agricultural development objectives. 2025-05-12 2025-05-13T14:47:18Z 2025-05-13T14:47:18Z Working Paper https://hdl.handle.net/10568/174560 en Open Access application/pdf International Food Policy Research Institute Benimana, Gilberthe Uwera; Warner, James; and Missiame, Arnold Kwesi. 2025. Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda. Rwanda SSP Working Paper 17. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/174560 |
| spellingShingle | agriculture smallholders stochastic models crops agricultural development Benimana, Gilberthe Uwera Warner, James Missiame, Arnold Kwesi Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda |
| title | Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda |
| title_full | Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda |
| title_fullStr | Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda |
| title_full_unstemmed | Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda |
| title_short | Unlocking agricultural efficiency: A stochastic frontier analysis of smallholder farmers in Rwanda |
| title_sort | unlocking agricultural efficiency a stochastic frontier analysis of smallholder farmers in rwanda |
| topic | agriculture smallholders stochastic models crops agricultural development |
| url | https://hdl.handle.net/10568/174560 |
| work_keys_str_mv | AT benimanagilbertheuwera unlockingagriculturalefficiencyastochasticfrontieranalysisofsmallholderfarmersinrwanda AT warnerjames unlockingagriculturalefficiencyastochasticfrontieranalysisofsmallholderfarmersinrwanda AT missiamearnoldkwesi unlockingagriculturalefficiencyastochasticfrontieranalysisofsmallholderfarmersinrwanda |