Data That Saves Lives? Statistical Capacity as a Pillar of Health Governance: Evidence from 99 Countries

Abstract This study investigates whether stronger national statistical systems are associated with changes in recorded health outcomes, focusing primarily on maternal mortality and secondarily on child mortality across 99 countries from 2013 to 2023. Motivated by the heightened awareness of data gaps during the COVID-19 pandemic, the analys s evaluates whether statistical infrastructure—measured through the World Bank's Statistical Performance Indicator (SPI_ALL)—is associated with changes in recorded preventable mortality, consistent with differences in reporting completeness and governance capacity. Using dynamic panel estimators, specifically the two-step System GMM estimator within the Arellano–Bond / Blundell–Bond framework, we control for macroeconomic, institutional, and demographic factors. Results show that higher statistical capacity is significantly associated with higher recorded maternal mortality across both low- and high-income countries. In contrast, its effect on child mortality is statistically significant only in high-income settings. This asymmetry highlights the role of institutional capacity in mediating the effectiveness of data systems, particularly governments’ ability to translate information into actionable governance responses. The findings suggest that statistical capacity functions not merely as a monitoring tool but as a foundational component of public health governance. By linking national data systems to improvements in the measurement, coverage, and usability of mortality statistics, this study supports WHO's strategy for interoperable health information systems and reinforces global priorities under the 2030 Sustainable Development Goals (SDGs).