Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper presents the results of a nationwide, low-cost intervention that used messages informed by behavioral economics and delivered through the government’s official mobile app to increase preschool attendance in Uruguay. We document null results for attendance and child development outcomes. We also estimate conditional average treatment effects (CATE) across individuals using causal forest algorithms. We present exploratory evidence that absenteeism and some measures of cognitive development might have improved for children around the median of the baseline distribution of attendance rate.