Technical Inefficiency Effects in Agriculture—A Meta-Regression

  •  Justice Djokoto    
  •  Francis Srofenyo    
  •  Akua Arthur    


A number of studies have examined the effect of study characteristics on mean technical efficiency as the dependent variable. This article departs from these earlier studies by using second-stage inefficiency covariates as key exploratory variables and study characteristics as control variables in a meta-regression. Unlike the vote count method of quantitative review, the parameters of the key variables have desirable properties and enable statistical inferences to be drawn. Additionally, the dependent variable employed is mean technical inefficiency. This is demonstrated using data on technical inefficiency of primary studies in Ghanaian agriculture, fitted to fractional regression models. The appropriate functional form of the fractional regression model is discussed with policy implications.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1916-9752
  • Issn(Onlne): 1916-9760
  • Started: 2009
  • Frequency: monthly

Journal Metrics

(The data was calculated based on Google Scholar Citations)

  • Google-based Impact Factor (2016): 2.28
  • h-index (December 2017): 31
  • i10-index (December 2017): 304
  • h5-index (December 2017): 22
  • h5-median (December 2017): 27