Abstract
In Ethiopia, technical efficiency studies started about three decades ago. These studies have reached different conclusions regarding agriculture efï¬ciency based on technical efficiency scores. This study represents the first attempt to use meta-analysis to examine the mean technical efficiency estimates in agriculture in Ethiopia. The current study employed 45 frontier studies published from 1993 to 2014 for the meta-analysis. The study employed fractional regression to model for the meta-regression analysis. The result of the study shows that there is no publication bias in technical efficiency studies in Ethiopia. The meta-analysis result shows the overall mean technical efficiencies are 68 and 71% based on fixed effect model and random effect model, respectively, suggesting that there are still opportunities for improvement in the efficiency of Ethiopian agriculture. The result also shows that technical efficiency was found to be decreasing over years for studies carried out in all the four regions together (Tigray, Amhara, Oromia, and South). Overall, the study obtained moderator variables (that is, wheat, maize, sample size, food crop, number of inputs) significantly affecting the estimation of the reported mean technical efficiencies in primary studies across the four meta-regression model specifications. The finding of the decline in technical efficiency over years implies that even though there is a scope of improving efficiency in the country, government should also consider side by side introduction and dissemination of new agricultural technologies to reverse the decreasing technical efficiency. This will ultimately boost the country’s agricultural and food production. Besides, the results call upon researchers and academicians to be curious in identifying study-specific attributes, which are essential for modeling farm-level efficiency. Key words: Meta-analysis, technical efficiency, fixed effect and random effect models.  
Highlights
In terms of functional forms, the result shows that the Cobb-Douglas production functional form yields on average a higher estimate (0.717) than the Translog functional form (0.644)
With regard to the distribution of the reported mean efficiency of the selected primary studies, Figure 1 portrays the distribution of the mean technical efficiency estimates of the studies and it was found that the distribution is normal for the whole sample
When the efficiency estimates plotted by grouping the sample using publication type (Journal and Thesis), it was observed that the distribution skewed to the right for those unpublished studies and normal for the published studies
Summary
The publication bias will be evident if the association between sample size and mean technical efficiency estimates is negative and significant. The dependent variable will be the reported mean technical efficiency estimates of each primary study.
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