Allocation of development assistance for health: is the predominance of national income justified? - Sterck, O; Roser, M; Ncube, M; Thewissen, S (Oxford University Press, 2018)
Gross national income (GNI) per capita is widely regarded as a key determinant of health outcomes. Major donors heavily rely on GNI per capita to allocate development assistance for health (DAH). This article questions this paradigm by analysing the determinants of health outcomes using cross-sectional data from 99 countries in 2012. We use disability-adjusted life years (Group I) per capita as our main indicator for health outcomes. We consider four primary variables: GNI per capita, institutional capacity, individual poverty and the epidemiological surroundings. Our empirical strategy has two innovations. First, we construct a health poverty line of 10.89 international-$ per day, which measures the minimum level of income an individual needs to have access to basic healthcare. Second, we take the contagious nature of communicable diseases into account, by estimating the extent to which the population health in neighbouring countries (the epidemiological surroundings) affects health outcomes. We apply a spatial two-stage least-squares model to mitigate the risks of reverse causality. Our model captures 92% of the variation in health outcomes. We emphasize four findings. First, GNI per capita is not a significant predictor of health outcomes once other factors are controlled for. Second, the poverty gap below the 10.89 health poverty line is a good measure of universal access to healthcare, as it explains 19% of deviation in health outcomes. Third, the epidemiological surroundings in which countries are embedded capture as much as 47% of deviation in health outcomes. Finally, institutional capacity explains 10% of deviation in health outcomes. Our empirical findings suggest that allocation frameworks for DAH should not only take into account national income, which remains an important indicator of countries' financial capacity, but also individual poverty, governance and epidemiological surroundings to increase impact on health outcomes.