Policy Challenge
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Program Type
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2
4
6
Enrollment In Secondary
Scholarships and achievement awards (eES)
7
-2
Evaluation Effect Average Age Observations Experimental Evaluation Country Intervention
Barrera-Osorio 2007 -5 Grade 11 118,481 No Colombia 100% reduction in school fees
Gajigo 2012 10 Grade 10 7,896 No Gambia Payment of school fees; the average cost per student was $59
Angrist 2002 0 Grade 10 1,577 Yes Colombia Vouchers for attending private schools covering fees and tuition
Edmonds 2014 1 13 438 Yes Nepal Scholarship and monthly stipend conditional on school attendance
Liu 2013 5 Grade 10 395 Yes China Annual transfer of $222 conditional on enrollment
Yi 2015 8 Grade 9 380 Yes China Annual transfer of $240 conditional on enrollment

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 (%)
Angrist 2002 0 -3 3 19
Barrera-Osorio 2007 -5 -5 -5 20
Edmonds 2014 1 -2 4 18
Gajigo 2012 10 5 15 16
Liu 2013 5 0 10 15
Yi 2015 8 0 16 12
Overall