Human Capital Index (HCI) – from uncertainty to robustness of comparisons

In order to monitor progress in human development within and between countries and over time, several simple and composite indices have been developed and are regularly used, particularly in public policy decision-making. In 2019, the World Bank adopted an index developed by Kraay (2018), the Human Capital Index (HCI).It combines demographic, education, and health dimensions on a complementary statistical and econometric basis. It is used by the World Bank in the area of human development for monitoring and comparison purposes, in time and space. Beyond the debate about the construction of the index itself in terms of weighting and aggregation, the $$HCI$$HCI is subject to statistical and econometric uncertainties that are not adequately captured by comparisons and are therefore, not robust.In this article, we propose a systematic approach taking into account these simultaneous uncertainties using a projection method. We present its practical implementation to construct confidence intervals to the $$HCI$$HCI that reflect these uncertainties. It appears that if confidence intervals overlap for two countries or for the same country over time, then comparisons would be inconclusive regardless of the point estimates.