Cobb-douglas stochastic frontier production approach on technical efficiency of small-scale cassava production in Delta State, Nigeria

This survey was conducted to analysed the status of technical efficiency of small-scale cassava farmers in Delta State. A multistage sampling technique was employed to select a total of 240 respondents. Data collected with aids of questionnaire were analysed using descriptive and inferential statistics. The study exposed that the respondents were in their active age of production who were mostly married female households. The educational qualification of farmers was primary school with moderate family size having wealth of farming experiences. Access to farm credit was a major problem with lack of extension service contact and indigenous stem cuttings as against improved varieties stems. The survey results demonstrated that fertilizer, family labour, and herbicides had negative statistically significant with cassava technical efficiency and education had positively statistically significant at 10% level indicating that education positively influenced the farmers‘ technical efficiency in resource utilization. The result exposed that the mean technical efficiency of the cassava farmers was 0.72 (72%). This infers cassava farmers could raise their efficiency by 28% revealing that farmers were operating a little below the Frontier level and could be enhanced through resource use optimization. The study suggest that farmers expand their scope of production and improve productivity by enhancing their resource use optimization.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.17163424
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Cobb-douglas stochastic frontier production approach on technical efficiency of small-scale cassava production in Delta State, Nigeria

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Cobb-douglas stochastic frontier production approach on technical efficiency of small-scale cassava production in Delta State, Nigeria

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Abstract

This survey was conducted to analysed the status of technical efficiency of small-scale cassava farmers in Delta State. A multistage sampling technique was employed to select a total of 240 respondents. Data collected with aids of questionnaire were analysed using descriptive and inferential statistics. The study exposed that the respondents were in their active age of production who were mostly married female households. The educational qualification of farmers was primary school with moderate family size having wealth of farming experiences. Access to farm credit was a major problem with lack of extension service contact and indigenous stem cuttings as against improved varieties stems. The survey results demonstrated that fertilizer, family labour, and herbicides had negative statistically significant with cassava technical efficiency and education had positively statistically significant at 10% level indicating that education positively influenced the farmers‘ technical efficiency in resource utilization. The result exposed that the mean technical efficiency of the cassava farmers was 0.72 (72%). This infers cassava farmers could raise their efficiency by 28% revealing that farmers were operating a little below the Frontier level and could be enhanced through resource use optimization. The study suggest that farmers expand their scope of production and improve productivity by enhancing their resource use optimization.

Zenodo (CERN European Organization for Nuclear Research)
Delta State University (NG), Delta State Polytechnic Ogwashi-Uku (NG), Western Delta University (NG)
Decent work and economic growth
Openalex Percentile: Top 33%
Geochemistry and Geologic Mapping
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Cobb-douglas stochastic frontier production approach on technical efficiency of small-scale cassava production in Delta State, Nigeria · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS