This study has two-fold objectives: first, to test the global convergence hypothesis in the progress of child stunting across 174 countries over the period 1990–2015; second, to identify factors determining the process of convergence or divergence.

The study design comprises macro-level cross-country analyses. Our empirical strategy uses parametric convergence models such as absolute and conditional β-convergence models, while non-parametric convergence models such as Kernel density plots serve as robustness checks.

The study uses a global setting comprising child stunting information from 174 countries.

The participants for this study are 174 countries. The information on child stunting prevalence for most countries is available from the UNICEF-WHO-WB Joint Child Malnutrition Estimates Expanded Database (April-2019), while national-level surveys are used for those countries where UNICEF-WHO-WB Database is not available. The data for socio-economic variables are taken from the World Bank’s data bank (1990–2015).

Findings from the absolute β-convergence model estimates show that progress in child stunting has diverged over the entire period (1990–2015). However, the speed of divergence has reduced for the recent period (2010–2015). The conditional β-convergence model estimates show that cross-country heterogeneity in GDP per capita, poverty and health care expenditure are significant factors explaining divergence in child stunting.

For replacing current divergence with convergence in child stunting worldwide, the study demonstrates the critical role of economic factors and public spending on health care to reduce child stunting, particularly in countries where progress is slow.