Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis

Due to capital constraints and land scarcity in developing countries, introducing new technology to boost productivity is difficult. As a result, working to improve cassava production efficiency is the best option available. Cassava is increasingly being used as a food source as well as an industria...

Descripción completa

Detalles Bibliográficos
Autores principales: Tafesse, Alula, Mena, Bekele, Belay, Abrham, Aynekulu, Ermias, Recha, John W.M., Osano, Philip M., Darr, Dietrich, Demissie, Teferi Dejene, Endalamaw, Tefera B., Solomon, Dawit
Formato: Journal Article
Lenguaje:Inglés
Publicado: Frontiers Media 2021
Materias:
Acceso en línea:https://hdl.handle.net/10568/116304
_version_ 1855526023971471360
author Tafesse, Alula
Mena, Bekele
Belay, Abrham
Aynekulu, Ermias
Recha, John W.M.
Osano, Philip M.
Darr, Dietrich
Demissie, Teferi Dejene
Endalamaw, Tefera B.
Solomon, Dawit
author_browse Aynekulu, Ermias
Belay, Abrham
Darr, Dietrich
Demissie, Teferi Dejene
Endalamaw, Tefera B.
Mena, Bekele
Osano, Philip M.
Recha, John W.M.
Solomon, Dawit
Tafesse, Alula
author_facet Tafesse, Alula
Mena, Bekele
Belay, Abrham
Aynekulu, Ermias
Recha, John W.M.
Osano, Philip M.
Darr, Dietrich
Demissie, Teferi Dejene
Endalamaw, Tefera B.
Solomon, Dawit
author_sort Tafesse, Alula
collection Repository of Agricultural Research Outputs (CGSpace)
description Due to capital constraints and land scarcity in developing countries, introducing new technology to boost productivity is difficult. As a result, working to improve cassava production efficiency is the best option available. Cassava is increasingly being used as a food source as well as an industrial raw material in the production of economic goods. This study estimates cassava production efficiency and investigates the causes of inefficiency in southern Ethiopia. Cross-sectional data from 158 households were collected using a systematic questionnaire. The Cobb-Douglas (CDs) stochastic frontier production model was used to calculate production efficiency levels. The computed mean result showed technical efficiency (TE), allocative efficiency (AE), and economic efficiency (EE) levels of 74, 90, and 66%, respectively. This demonstrated that existing farm resources could increase average production efficiency by 26, 10, and 34%, respectively. The study found that land size, urea fertilizer application, and cassava planting cut all had a positive and significant effect on cassava production. It was discovered that TE was more important than AE as a source of benefit for EE. Inefficiency effects modeled using the two-limit Tobit model revealed that household head age, level of education, cassava variety, extension contact, rural credit, off-farm activities involvement to generate income, and farm size were the most important factors for improving TE, AE, and EE efficiencies. As a result, policymakers in government should consider these factors when addressing inefficiencies in cassava production. It is especially important to provide appropriate agricultural knowledge through short-term training, to provide farmers with access to formal education, to access improved cassava varieties, and to support agricultural extension services.
format Journal Article
id CGSpace116304
institution CGIAR Consortium
language Inglés
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher Frontiers Media
publisherStr Frontiers Media
record_format dspace
spelling CGSpace1163042025-08-15T13:21:59Z Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis Tafesse, Alula Mena, Bekele Belay, Abrham Aynekulu, Ermias Recha, John W.M. Osano, Philip M. Darr, Dietrich Demissie, Teferi Dejene Endalamaw, Tefera B. Solomon, Dawit cassava cobb-douglas efficiency stochastic frontier tobit horticulture ecology food science Due to capital constraints and land scarcity in developing countries, introducing new technology to boost productivity is difficult. As a result, working to improve cassava production efficiency is the best option available. Cassava is increasingly being used as a food source as well as an industrial raw material in the production of economic goods. This study estimates cassava production efficiency and investigates the causes of inefficiency in southern Ethiopia. Cross-sectional data from 158 households were collected using a systematic questionnaire. The Cobb-Douglas (CDs) stochastic frontier production model was used to calculate production efficiency levels. The computed mean result showed technical efficiency (TE), allocative efficiency (AE), and economic efficiency (EE) levels of 74, 90, and 66%, respectively. This demonstrated that existing farm resources could increase average production efficiency by 26, 10, and 34%, respectively. The study found that land size, urea fertilizer application, and cassava planting cut all had a positive and significant effect on cassava production. It was discovered that TE was more important than AE as a source of benefit for EE. Inefficiency effects modeled using the two-limit Tobit model revealed that household head age, level of education, cassava variety, extension contact, rural credit, off-farm activities involvement to generate income, and farm size were the most important factors for improving TE, AE, and EE efficiencies. As a result, policymakers in government should consider these factors when addressing inefficiencies in cassava production. It is especially important to provide appropriate agricultural knowledge through short-term training, to provide farmers with access to formal education, to access improved cassava varieties, and to support agricultural extension services. 2021-11-22 2021-11-25T17:06:08Z 2021-11-25T17:06:08Z Journal Article https://hdl.handle.net/10568/116304 en Open Access Frontiers Media Tafesse, A., Mena, B., Belay, A., Aynekulu, E., Recha, J. W., Osano, P. M., Darr, D., Demissie, T. D., Endalamaw, T. B., & Solomon, D. (2021). Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis. In Frontiers in Sustainable Food Systems (Vol. 5). Frontiers Media SA. https://doi.org/10.3389/fsufs.2021.758951
spellingShingle cassava
cobb-douglas
efficiency
stochastic frontier
tobit
horticulture
ecology
food science
Tafesse, Alula
Mena, Bekele
Belay, Abrham
Aynekulu, Ermias
Recha, John W.M.
Osano, Philip M.
Darr, Dietrich
Demissie, Teferi Dejene
Endalamaw, Tefera B.
Solomon, Dawit
Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
title Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
title_full Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
title_fullStr Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
title_full_unstemmed Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
title_short Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
title_sort cassava production efficiency in southern ethiopia the parametric model analysis
topic cassava
cobb-douglas
efficiency
stochastic frontier
tobit
horticulture
ecology
food science
url https://hdl.handle.net/10568/116304
work_keys_str_mv AT tafessealula cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT menabekele cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT belayabrham cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT aynekuluermias cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT rechajohnwm cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT osanophilipm cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT darrdietrich cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT demissieteferidejene cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT endalamawteferab cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis
AT solomondawit cassavaproductionefficiencyinsouthernethiopiatheparametricmodelanalysis