A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook

This article analyses the technical efficiency of maize production in Zimbabwe’s smallholder farming communities following the fast-track land reform of the year 2000 with a view of highlighting key entry points for policy. Using a randomly selected sample of 522 smallholder maize producers, a stoch...

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Autores principales: Mango, Nelson, Makate, Clifton, Hanyani-Mlambo, Benjamin T., Siziba, Shephard, Lundy, Mark M.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Informa UK Limited 2015
Materias:
Acceso en línea:https://hdl.handle.net/10568/69147
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author Mango, Nelson
Makate, Clifton
Hanyani-Mlambo, Benjamin T.
Siziba, Shephard
Lundy, Mark M.
author_browse Hanyani-Mlambo, Benjamin T.
Lundy, Mark M.
Makate, Clifton
Mango, Nelson
Siziba, Shephard
author_facet Mango, Nelson
Makate, Clifton
Hanyani-Mlambo, Benjamin T.
Siziba, Shephard
Lundy, Mark M.
author_sort Mango, Nelson
collection Repository of Agricultural Research Outputs (CGSpace)
description This article analyses the technical efficiency of maize production in Zimbabwe’s smallholder farming communities following the fast-track land reform of the year 2000 with a view of highlighting key entry points for policy. Using a randomly selected sample of 522 smallholder maize producers, a stochastic frontier production model was applied, using a linearised Cobb–Douglas production function to determine the production elasticity coefficients of inputs, technical efficiency and the determinants of efficiency. The study finds that maize output responds positively to increases in inorganic fertilisers, seed quantity, the use of labour and the area planted. The technical efficiency analysis suggests that about 90% of farmers in the sample are between 60 and 75% efficient, with an average efficiency in the sample of 65%. The significant determinants of technical efficiency were the gender of the household head, household size, frequency of extension visits, farm size and the farming region. The results imply that the average efficiency of maize production could be improved by 35% through better use of existing resources and technology. The results highlight the need for government and private sector assistance in improving efficiency by promoting access to productive resources and ensuring better and more reliable agricultural extension services.
format Journal Article
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institution CGIAR Consortium
language Inglés
publishDate 2015
publishDateRange 2015
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publisherStr Informa UK Limited
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spelling CGSpace691472025-03-13T09:44:14Z A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook Mango, Nelson Makate, Clifton Hanyani-Mlambo, Benjamin T. Siziba, Shephard Lundy, Mark M. production smallholders maize inorganic fertilizers stochastic models farmers producción maíz abonos inorgánicos modelos estocásticos agricultores This article analyses the technical efficiency of maize production in Zimbabwe’s smallholder farming communities following the fast-track land reform of the year 2000 with a view of highlighting key entry points for policy. Using a randomly selected sample of 522 smallholder maize producers, a stochastic frontier production model was applied, using a linearised Cobb–Douglas production function to determine the production elasticity coefficients of inputs, technical efficiency and the determinants of efficiency. The study finds that maize output responds positively to increases in inorganic fertilisers, seed quantity, the use of labour and the area planted. The technical efficiency analysis suggests that about 90% of farmers in the sample are between 60 and 75% efficient, with an average efficiency in the sample of 65%. The significant determinants of technical efficiency were the gender of the household head, household size, frequency of extension visits, farm size and the farming region. The results imply that the average efficiency of maize production could be improved by 35% through better use of existing resources and technology. The results highlight the need for government and private sector assistance in improving efficiency by promoting access to productive resources and ensuring better and more reliable agricultural extension services. 2015-12-31 2015-12-07T19:20:38Z 2015-12-07T19:20:38Z Journal Article https://hdl.handle.net/10568/69147 en Open Access Informa UK Limited Mango, Nelson; Makate, Clifton; Hanyani-Mlambo, Benjamin; Siziba, Shephard; Lundy, Mark. 2015. A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe : The post-fast-track land reform outlook . Cogent Economics & Finance 3:1117189.
spellingShingle production
smallholders
maize
inorganic fertilizers
stochastic models
farmers
producción
maíz
abonos inorgánicos
modelos estocásticos
agricultores
Mango, Nelson
Makate, Clifton
Hanyani-Mlambo, Benjamin T.
Siziba, Shephard
Lundy, Mark M.
A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook
title A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook
title_full A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook
title_fullStr A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook
title_full_unstemmed A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook
title_short A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: The post-fast-track land reform outlook
title_sort stochastic frontier analysis of technical efficiency in smallholder maize production in zimbabwe the post fast track land reform outlook
topic production
smallholders
maize
inorganic fertilizers
stochastic models
farmers
producción
maíz
abonos inorgánicos
modelos estocásticos
agricultores
url https://hdl.handle.net/10568/69147
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