Economic Efficiency of Wheat Producers: The Case of Debra Libanos District, Oromia, Ethiopia

Bezu, Kebebew Hundie; Chala, Badassa Wolteji; Itticha, Milkessa Wakjira

doi:10.24925/turjaf.v9i6.953-960.4244

Cited by 5 publications

(1 citation statement)

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“…2011; Asfaw et al, 2019;Jeilan Husen and Fentaw, 2019;Hailu, 2020;Bezu et al, 2021). The goal of the current study is to lay the groundwork for understanding the distribution of the mean TE on the output of Ethiopian wheat.…”

Section: Introductionmentioning

confidence: 99%

A systematic review and meta-regression analysis of technical efficiency in Ethiopian wheat farming

Mulusew,

Hong

2023

Front. Sustain. Food Syst.

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Replications are important for science, both statistically and philosophically. A plethora of empirical studies that have been done so far show that there are always variations, errors and inconclusive findings on the technical efficiency (TE) scores of wheat output in Ethiopia. In this study, we intend to contribute to these controversies by providing the first thorough investigation of the magnitude of mean-effect size and the underlying factors of mean technical efficiency variations in wheat production across studies in Ethiopia. These efficiency scores are retrieved from 31 studies, or a household size of 12,754 over the years 2011–2022. The analysis of meta-regression was done using a random effect model using Comprehensive Meta-analysis (CMA-4) software. The Begg and Mazumdar rank-correlation test, egger test, and funnel plot were used to determine publication bias across studies. Since 2022, we have utilized the classic fail-safe-N test. One issue with publication bias is the omission of some non-significant studies from the analysis, which, if they were included, would cancel out the observed effect. Further, the missing study problem or “file drawer” problem, of the study would also be computed using the “Trim and Fill” estimation approach. To evaluate heterogeneity, a forest plot is used. The effect size is also determined using the random effect model along with the I-squared statistic, the tau-squared and tau, and the Q-test. As a result, a mean effect size of 71.6% with a 95% confidence interval of 67.9%−75.3% is observed. The meta-regression demonstrates that the 31 mean technical efficiency studies included in the research had varying efficiency scores due to variations in sample size, methodologies used, publication status, and study range. It suggests that, with all other factors held constant, a 1% change in these regressors causes a 0.01%, 10.88%, 21.22%, and 6.74% change, respectively, in the mean technical efficiency scores across studies in Ethiopia. In addition, the technical efficiency score across studies is also affected by the location in which the study is conducted.

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Section: Introductionmentioning

confidence: 99%