Policy Challenge
Path 2 Copy Created with Sketch.
Program Type
Path 2 Copy Created with Sketch.
4
3
3
Adult Employment
Technical and soft skills in-classroom training (eAEM)
13
-6
Evaluation Effect Average Age Observations Experimental Evaluation Country Intervention
Bausch 2016 -6 15-25 871 Yes Morocco Training in financial education, entrepeneurial/business and soft skills
Adoho 2014 i 15 22 608 Yes Liberia Technical and soft skills in-classroom training with job search assistance
Calero 2017 i 3 23 350 Yes Brazil Workshops using arts/theatre for vocational, work-readiness and basic skills

Graph of Effects

This graph shows the effects of [Number of Evaluations] evaluations of [Program Type] programs. The first evaluation, [Evaluation name 1], estimated an effect of [Estimated effect Eval. 1] points (graphed with the top grey circle). Because this is an estimate, there is uncertainty about what the true effect is. But we know that the true effect will probably lie between a low value of [True effect lie between – Low value, Eval. 1] and a high value of [True effect lie between – High value, Eval. 1] (graphed with the top horizontal line). We can combine the estimates from all the evaluations and compute an average effect of [Estimated effect, Average] (graphed with the black circle). There is also uncertainty about where the true average effect is. But we know that the true average effect probably lies between [True effect lie between – Low value, Average] and [True effect lie between – High value, Average] points (graphed with the bottom horizontal line).
Evaluation Effects Low Value High Value Weight in Average Effect (%)
Adoho 2014 i 15 8 21 33
Bausch 2016 -6 -12 -1 34
Calero 2017 i 3 -3 9 33
Overall