Bayesian technical efficiency analysis of groundnut production in Ghana

Dominic Chakuri, Freda Elikplim Asem, Edward Ebo Onumah

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper considered Bayesian Stochastic Frontier Model to analyse technical efficiency and their determinants of groundnut farmers in Ghana. The paper used a 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%.

Original languageEnglish
Article number2074627
JournalCogent Economics and Finance
Volume10
Issue number1
DOIs
Publication statusPublished - 2022

Keywords

  • Bayesian stochastic frontier model
  • Markov Chain Monte Carlo Methods
  • posterior distributions
  • return to scale

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