# I. Introduction

There is a long-standing debate among policy makers and scholars on whether increasing financial resources can improve health and education outcomes. The question has been and remains equally relevant both in developed and developing countries. While a recent strand of literature (Lafortune, Rothstein, and Schanzenbach 2018; Jackson, Johnson, and Persico 2015) provides very rigorous evidence of a strong positive causal relationship between school spending and student outcomes for the United States, there is no clear sense of whether this relationship can be generalized to other countries and to other important dimensions of human capital beyond learning.

The Human Capital Index (HCI), as a cross-country metric that benchmarks human capital outcomes for the next generation, one of the key pillars of the Human Capital Project (HCP) (World Bank Group 2018a), has highlighted how differences in human capital, as proxied by a combination of education and health indicators, are associated with large productivity differences across countries. Countries in the bottom 10 percent of the HCI ranking are losing at least 60 percent of the productivity that they could have achieved if they had full health and full education. For countries in the top 10 percent, the lost potential is equivalent to 20 percent of what they could have obtained by achieving their full human capital potential. Such large differences in outcomes naturally raise the question of whether countries at the bottom of the HCI ranking are investing enough resources to close the human capital gap. Answering this question is complex for a variety of reasons.

First, the human capital outcomes that we observe today are the result of investments that countries made in the past and there is no clear evidence on how long it takes for these investments to materialize into better outcomes. Second, since the HCI puts emphasis on the _quality_ as well as on the _quantity_ of human capital (Kraay 2018), the nature of spending might be as relevant as the amount of spending. For instance, there is well-established evidence that high-quality pre-school programs that target the most disadvantaged children are an effective tool to increase learning outcomes (Almond, Currie, and Duque 2017). That is not the case for other types of investments, such as school construction (Ganimian and Murnane 2014). The entire field of research of cost-effectiveness in health and health care is based on the assumption that finite resources can be used strategically to achieve better outcomes for less money (World Health Organization 2019). Third, the return of an additional dollar spent in terms of human capital outcomes is dramatically different across countries because institutional, economic, demographic, and cultural differences contribute to spending being more or less efficient. For instance, Al-Samarrai et al. find that on overage a 10 percent increase in resources led to a 0.6 percent increase in Learning Adjusted Years of Schooling (LAYS) (AlSamarrai, Cerdan-Infantes, and Lehe 2018) _._ However, for countries in the top 25th percentile of the efficiency distribution, a 10 percent increase in resources led to a 2.7 percent increase in LAYS. Finally, spending on human capital is usually quantified in a sector-specific manner, which does not reflect the multisectoral nature of the interventions needed to improve outcomes. Interactions between different types of investments are not confined to the social sector. There is growing evidence showing that investments in water and sanitation (Alsan and Goldin 2015) and infrastructure (Barham, Lipscomb, and Mobarak 2011) as just two examples are crucial for improving human capital outcomes. Therefore, it is unclear to what extent the effect of social sector spending depends on investments in other sectors.

Besides the economic motivations discussed above, there are many data limitations that can potentially constrain our understanding of the relationship between spending and human capital. While the resources 2