The role of pre-primary school attendance in school readiness in Bangladesh: Exploring the interaction effects with socioeconomic status and home learning environment

This study investigates the moderating effect of family socioeconomic status and the home learning environment on the relationship between preschool attendance and school readiness in Bangladesh. Using nationally representative data from the Multiple Indicator Cluster Survey (2013 and 2019), we conducted logit regression and interaction analyses with using the newly developed Stata command (‘ ginteff ’). This command enables a rigorous examination of interaction effects in models with nonlinear dependent variables, which has traditionally been a challenging task. The findings indicate that preschool attendance is positively and significantly associated with two domains of school readiness, namely literacy-numeracy and approaches to learning, while no significant association is found with social-emotional and physical development. Although preschool attendance enhances overall school readiness and literacy-numeracy regardless of household wealth and the home learning environment, its effects are disproportionately larger for children from wealthier families. This supports the cumulative advantage theory, which suggests that certain groups derive greater benefits from educational interventions, potentially exacerbating existing inequalities. In contrast, the home learning environment did not significantly moderate the effects of preschool attendance. These findings underscore the need for policies that enhance access to and quality of pre-primary education for disadvantaged children in Bangladesh, ensuring that early education interventions help reduce rather than reinforce socioeconomic disparities. • Preschool attendance improves early literacy-numeracy and approaches to learning but not social-emotional domain. • Interaction analysis indicates that children from wealthier families benefit more from preschool attendance. • The Stata command (‘ ginteff ’) was used to rigorously test interaction effects in models with nonlinear dependent variables.