Some children left behind: Variation in ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Some children left behind: Variation in the effects of an educational intervention
Auteur(s) :
Buhl-Wiggers, Julie [Auteur]
Kerwin, Jason [Auteur]
Department of Applied Economics [Minnesota] [APEC]
Muñoz-Morales, Juan [Auteur]
Lille économie management - UMR 9221 [LEM]
Smith, Jeffrey [Auteur]
Thornton, Rebecca [Auteur]
Kerwin, Jason [Auteur]
Department of Applied Economics [Minnesota] [APEC]
Muñoz-Morales, Juan [Auteur]
Lille économie management - UMR 9221 [LEM]
Smith, Jeffrey [Auteur]
Thornton, Rebecca [Auteur]
Titre de la revue :
Journal of Econometrics
Éditeur :
Elsevier
Date de publication :
2022-05-11
ISSN :
0304-4076
Discipline(s) HAL :
Sciences de l'Homme et Société/Economies et finances
Résumé en anglais : [en]
We document substantial variation in the effects of a highly-effective literacy program in northern Uganda. The program increases test scores by 1.4 SDs on average, but standard statistical bounds show that the impact ...
Lire la suite >We document substantial variation in the effects of a highly-effective literacy program in northern Uganda. The program increases test scores by 1.4 SDs on average, but standard statistical bounds show that the impact standard deviation exceeds 1.0 SD. This implies that the variation in effects across our students is wider than the spread of mean effects across all randomized evaluations of developing country education interventions in the literature. This very effective program does indeed leave some students behind. At the same time, we do not learn much from our analyses that attempt to determine which students benefit more or less from the program. We reject rank preservation, and the weaker assumption of stochastic increasingness leaves wide bounds on quantile-specific average treatment effects. Neither conventional nor machine-learning approaches to estimating systematic heterogeneity capture more than a small fraction of the variation in impacts given our available candidate moderators.Lire moins >
Lire la suite >We document substantial variation in the effects of a highly-effective literacy program in northern Uganda. The program increases test scores by 1.4 SDs on average, but standard statistical bounds show that the impact standard deviation exceeds 1.0 SD. This implies that the variation in effects across our students is wider than the spread of mean effects across all randomized evaluations of developing country education interventions in the literature. This very effective program does indeed leave some students behind. At the same time, we do not learn much from our analyses that attempt to determine which students benefit more or less from the program. We reject rank preservation, and the weaker assumption of stochastic increasingness leaves wide bounds on quantile-specific average treatment effects. Neither conventional nor machine-learning approaches to estimating systematic heterogeneity capture more than a small fraction of the variation in impacts given our available candidate moderators.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
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