Bayesian technical efficiency analysis of groundnut production in Ghana

Cogent Economics & Finance

Dominic Chakuri¹  Edward Ebo Onumah¹  Freda Elikplim Asem¹ 

[1] University of Ghana Legon, Accra, Ghana, Department of Agricultural Economics and Agribusiness;

关键词: Bayesian stochastic frontier model;    posterior distributions;    Markov Chain Monte Carlo Methods;    return to scale;   

DOI  :  10.1080/23322039.2022.2074627

来源: DOAJ

【 摘 要 】

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%.

【 授权许可】

Unknown