Policy Challenge
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Program Type
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17
3
5
Learning In Secondary
Monetary incentives to students (eLS)
28
5
Evaluation Effect Average Age Observations Experimental Evaluation Country Intervention
Behrman 2012 i 19 Grade 11 36,101 Yes Mexico Students received $249-$1491 for improving test scores
Sharma 2011 4 Grade 8 2,624 Yes Nepal Awards to students based on semester and end-of-year test scores
Blimpo 2010 ii 27 Grade 10 790 Yes Benin Teams of students received $44-$133 for passing certification exam
Blimpo 2010 i 30 Grade 10 770 Yes Benin Students received $11-$33 for passing certification exam
Blimpo 2010 iii 36 Grade 10 762 Yes Benin Student received $708 if her team scored high on certification exam

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 (%)
Behrman 2012 i 19 17 21 46
Blimpo 2010 i 30 10 50 7
Blimpo 2010 ii 27 7 47 7
Blimpo 2010 iii 36 13 59 6
Sharma 2011 4 -5 13 34
Overall