Measuring the technical efficiency and effectiveness of small-scale farmers and their impact on rural household food security in Burundi

Smallholder farming systems in Burundi are characterized by an integrated mix of cash and food crops. The dynamics between subsystems can influence the degree of complementarity and technical efficiency of their operations, particularly given seasonality, labor and input demand within the farming sy...

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Veröffentlicht in:Applied mathematical sciences 2024, Vol.18 (10), p.449-466
Hauptverfasser: Niyonzima, Audace, D'Haese, Marijke, Heidi, Megerle, Jean, Ndimubandi, Nicodeme, Nimenya, Serge, Ngendakumana, Niragira, Sanctus
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Sprache:eng
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Zusammenfassung:Smallholder farming systems in Burundi are characterized by an integrated mix of cash and food crops. The dynamics between subsystems can influence the degree of complementarity and technical efficiency of their operations, particularly given seasonality, labor and input demand within the farming system. In this paper, we use survey data from households engaged in maize production in Ngozi province as a speculative crop given its contribution in terms of income and food security in rural households. The stochastic production frontier model was used to analyze the dependence of the difference between random effects and producers’ technical inefficiency on maximum maize production. The variables used for the production function are labor, capital and land, while the inefficiency variables are farmer age, gender of household head, household size, education level, access to credit, distance to market for maize producers, agricultural extension, cooperative membership, access to labor, use of organic fertilizer, use of selected seeds, use of mineral fertilizer. The results of the analysis give a gamma value of 0.54, leading to the conclusion that the gap between observed and optimum maize production is largely explained by the effects of maize growers' technical inefficiency. The results also show that the inefficiency variables introduced into the model contribute to improving the technical efficiency of maize farmers in the study area, with the exception of the variables distance to the market for maize farmers, access to labor, and use of mineral fertilizer. The average technical efficiency score for maize farmers in the study area is 72%, meaning that on average, maize farmers are operating at 72% of their production capacity; their technical inefficiency is 28%. They can still increase their maize production by 28% at no extra cost. Thus, we found that maize production in the study area is a highly capital-intensive rather than labor-intensive activity, as the "capital" variable is positive and significantly correlated with maize production.
ISSN:1314-7552
1314-7552
DOI:10.12988/ams.2024.918615