The convergence of the World Health Organization Member States regarding the United Nations’ Sustainable Development Goal ‘Good health and well-being’

Convergence in productivity examines if entities in an industry get closer to the best practices or if the gap between the frontiers of the best and worst performers decreases over time. In a multi-input multi-output setting, the assessment of σ- and β-convergence can be measured with the use of non-parametric frontier techniques, such as data envelopment analysis. We propose an innovative approach to estimate convergence in the context of performance assessments resting on composite indicators, accounting for desirable and undesirable indicators. This methodology rests on ‘Benefit-of-the-Doubt’ models, specified with a directional distance function. It is applied to the Member States of the World Health Organization (WHO) in order to study their convergence in terms of the United Nations’ Sustainable Development Goal (SDG) ‘Good health and well-being’. We collected data for all years since the proposal of the SDGs, covering the period between 2016 and 2020. The results show that all WHO regions are β^-divergent, especially because of the generalised decline of the Worst Practice Frontier (WPF), alongside an improvement at a lower rate of the Best Practice Frontier (BPF). The regional analysis also revealed σ^-convergence in the Region of the Americas and the Eastern Mediterranean Region; the South-East Asia and African Regions exhibited σ^-divergence; the Western Pacific and European Regions remained stable in terms of the performance spread regarding the BPF. At the worldwide level, we also observed an increase of the gap between the BPF and the WPF, although the performance spread around the worldwide BPF remained relatively stable.