Resource Use Efficiency of Dry Season Irish Potato Production in Plateau State, Nigeria: a Double Bootstrapping Dea Approach
Year: 2025
Type: article
Abstract: The study analyzed resource use efficiency of dry season Irish Potato production in Plateau State, Nigeria. A random sampling was the main technique used in selecting 109 Irish Potato farmers that took part in the study. The primary data was collected by trained enumerators and analyzed using bootstrap Data Envelopment Analysis (DEA) and truncated regression model. Result of the dry season Variable Return to Scale (VRS) DEA reveals average technical efficiency (TE) for radial, non-radial and bias-corrected estimates to be 0.95, 0.79 and 0.84 respectively with a mean allocative and economic efficiency of 0.60 and 0.56. The estimated radial TE score was higher than the bias-corrected TE score indicating over-estimation of the radial score which in turn leads to bias results. Regression analysis showed that age (0.01,P<0.00), membership of farm group (-0.19,P<0.00), educational level (-0.15,P<0.00), extension contact (-0.13,P<0.00) and access to credit (-0.22,P<0.00) were the positive and significant variables contributing to the efficiency of Irish potato production. In conclusion, the dry season Irish potato farmers were operating below the production frontier, indicating possibilities of input reduction for improved on-farm performance. Regression analysis showed that age, membership of farm group, educational level, extension contact and access to credit were the positive and significant variables contributing to the efficiency of Irish potato production. The study recommends the formulation of policies that ensure provision of quality extension contact, increased credit access and education among Irish potato farmers. There is also need for training of farmers on effective inputs use management as a potential measures to enhance their productive efficiency.
Authors: Alegwu, F. O.,, Yustus, S. F.
Institution: Usmanu Danfodiyo University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4414475140
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