Policy Challenge
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Program Type
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3
3
6
Learning In Secondary
Cash transfers (eLS)
12
-6
Evaluation Effect Average Age Observations Experimental Evaluation Country Intervention
Filmer 2009 -8 Grade 6 3,225 No Cambodia Students received payments of $54-$82 conditional on school enrollment
Chen 2012 19 Grade 7 2,742 No China Relief of $241 tuition fee for students with the best exam scores
Baird 2011 i 13 N/A 1,826 Yes Malawi Monthly transfers of $1.10-$11 conditional on school attendance
Yi 2015 -2 Grade 7 1,672 Yes China Annual transfer of $240 conditional on enrollment
Baird 2011 ii -1 N/A 1,617 Yes Malawi Unconditional monthly transfers of $1.10-$11 to students and parents
Liu 2013 6 Grade 9 472 Yes China Annual transfer of $222 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 (%)
Baird 2011 i 13 4 22 12
Baird 2011 ii -1 -14 12 10
Chen 2012 19 9 29 21
Filmer 2009 -8 -13 -3 26
Liu 2013 6 -18 30 10
Yi 2015 -2 -12 8 21
Overall