Policy Challenge
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Program Type
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6
3
10
Learning In Primary
Incentivos monetarios para maestros (sLP)
11
1
Evaluación Efecto Edad promedio Observaciones Evaluación experimental País Intervención
Santibanez 2014 -7 Grado 5 36,420 No México Las escuelas recibieron capacitación y un subsidio de $4980
Aturupane 2014 i 5 Grado 4 3,107 No Sri Lanka Las escuelas establecieron comités para mejorar la gestión y los resultados
Barr 2012 i 11 Grado 3 2,153 Si Uganda Capacitación de los comités escolares sobre la implementación de la supervisión de las escuelas
Barr 2012 ii 22 Grado 3 2,153 Si Uganda Capacitación de los comités escolares sobre la implementación de la supervisión de las escuelas
Blimpo 2011 i -4 Grado 4 1,629 Si Gambia Las escuelas recibieron capacitación para mejorar capacidades y un subsidio de $553

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).
Evaluación Efectos Valor Mínimo Valor Máximo Peso en el efecto promedio (%)
Aturupane 2014 i 5 -11 21 20
Barr 2012 i 11 -9 30 9
Barr 2012 ii 22 4 40 10
Blimpo 2011 i -4 -13 6 44
Santibanez 2014 -7 -25 11 17
Overall