Bayesian technical efficiency analysis of groundnut production in Ghana
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Date
2022
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Publisher
Cogent Economics & Finance
Abstract
This 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%.
Description
Research Article
Keywords
posterior distributions, return to scale, Markov Chain Monte Carlo Methods