This paper investigates the weekly evolution of child skills as measured by unique data from a widely-emulated early childhood home-visiting program developed in Jamaica, adapted to rural China, and applied in different versions worldwide. The design of the study avoids problems of endogeneity of inputs and lack of truly comparable measures of skills across children that plague previous econometric studies of child development. Skills that are nominally classified as the same, in fact, do not appear to share a common unit scale across levels. They are produced by skill-specific, lifecycle-stage-specific technologies. We formulate and estimate a new dynamic stochastic skill production model for multiple skills that is consistent with the evidence. We quantify the dynamics of early life learning. The model explains the “fadeout” of measures of learning by the emergence of new skills not properly measured. We investigate the role of ability in learning. We find important differences in learning patterns between boys and girls.

More on this topic

BFI Working Paper·Sep 30, 2025

Closing Early Math Gaps by Parental Education with Technology at Home

Daniela Bresciani, Ariel Kalil, Haoxuan Liu, Susan E. Mayer, and Rohen Shah
Topics: Early Childhood Education
BFI Working Paper·Sep 16, 2025

The Promise of Digital Technology and Generative AI for Supporting Parenting Interventions in Latin America

Ariel Kalil, Michelle Michelini, and Pablo Ramos
Topics: Early Childhood Education, Technology & Innovation
BFI Working Paper·Sep 8, 2025

Chat2Learn: A Proof-of-Concept Evaluation of a Technology-Based Tool to Enhance Parent-Child Language Interaction

Linxi Lu and Ariel Kalil
Topics: Early Childhood Education, Technology & Innovation