Bayesian technical efficiency analysis of groundnut production in Ghana

dc.contributor.authorChakuri, D.
dc.contributor.authorAsem, F.E.
dc.contributor.authorOnumah, E.E.
dc.date.accessioned2024-05-28T10:24:35Z
dc.date.available2024-05-28T10:24:35Z
dc.date.issued2022
dc.descriptionResearch Articleen_US
dc.description.abstractThis paper considered Bayesian Stochastic Frontier Model to analyse technical efficiency and their determinants of groundnut farmers in Ghana. The paper used cross-sectional data of three-hundred (300) observations to obtain posterior distributions of the farmers’ technical efficiency levels. All computations were done using Markov Chain Monte Carlo methods (MCMC). results revealed that the groundnut farmers produce at an increasing return to scale of 1.10. Average technical efficiency of the farmers was found to be 70.5%, ranging from a minimum of 13.0% to a maximum of 95.1%. Frequency of extension visit, educational level and gender of the farmers were identified to significantly explain inefficiency of the farmers. The paper concluded that groundnut farmers in the northern part of Ghana are operating in the first stage of the production function and could increase their frontier output by 29.5%.en_US
dc.identifier.otherhttps://doi.org/10.1080/23322039.2022.2074627
dc.identifier.urihttp://ugspace.ug.edu.gh:8080/handle/123456789/42027
dc.language.isoenen_US
dc.publisherCogent Economics & Financeen_US
dc.subjectposterior distributionsen_US
dc.subjectreturn to scaleen_US
dc.subjectMarkov Chain Monte Carlo Methodsen_US
dc.titleBayesian technical efficiency analysis of groundnut production in Ghanaen_US
dc.typeArticleen_US

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