# **_A.4. Economic cost at present value_**

We estimate the per student per year effect of a reduction in LAYS on earnings using the returns estimates for one year of schooling in that country and ILO estimates of mean monthly income in 2017 PPP $. We use an 8% return to education for all countries as a long-term return for basic education.<sup>94</sup> To estimate the long-term effect in Present Value we assume that all currently enrolled students enter the labor market on average in 10 years, and have a working life of 45 years. We use a discount rate of 3%. This discount rate is consistent with the standards in global health analyses, established primarily through the recommendations of the Panels on Cost-Effectiveness in Health and Medicine (Gold et al,. 2996; Neumann et al., 2016). The Gates reference case (Wilkinson et al., 2014, 2016), developed to support health economic evaluations funded by the Bill and Melinda Gates Foundation globally also endorses a discount rate of 3%. In education, the OECD uses a discount rate of 2% to estimate private net financial returns of education (OECD, 2019). As our analysis is global, we use the higher discount rate of 3% similar to global health analyses. The choice of the discount rate is important as it makes a considerable difference when analyzing the long-term effects. The recent Reference Case Guidelines from the Bill & Melinda Gates Foundation (Robinson et al., 2019) while providing similar guidance on 3% as discount rate also emphasize that the use of a discount rate should reflect local conditions. Similarly, Haacker et al., 2019, discuss that while 3% is appropriate for health analyses in high income countries, higher discount rates of 4% and 5% are more appropriate for upper-middle income and lower-middle income and low-income countries. However, we choose to use a consistent discount rate for all countries of 3% so as not to penalize lower income countries in the global analysis.

We estimate the economy wide affect by aggregating the per-student-present-value effect on earnings over all students currently enrolled in pre-primary, primary, and secondary, in alignment with the HCI. We adjust this aggregate by the expected survival rate of the student cohort, using the HCI adult survival rate, and for the share of work-life that this student cohort is expected to be in gainful employment, this component is also referred to as Human Capital Utilization (Pennings, 2019). All these factors are available at the country level.

Ideally, we would like to rely on work-life tables for every country, unfortunately this is not available at a global scale.<sup>95</sup> We also assume that the current expected earnings, which reflect the prevailing structure of the labor market, prices, and discrimination, is on average, a useful aggregate proxy. We do, however, have concerns, to what extent this assumption would hold if we were to disaggregate results by gender, since both expected earnings and labor force participation are significantly lower for women, given prevailing discrimination, both of which are likely to improve in the next 45 years.

One important point is to how to best benchmark our returns to education assumption. This is critical since much of the literature on Mincerian regressions<sup>96</sup> uses years of schooling, which are computed using a quality unadjusted measure of years of schooling. We are comfortable with our assumptions for two main reasons. First, one could argue that labor markets should be able to price years of education, taking into consideration their quality. And second, if not, a quality adjusted

> 94 We have checked the robustness of this assumption using Patrinos et al (2018) country-specific returns and did not find significant differences at the aggregate level.

> 95 See Alter and Becker (1985) for a more detailed discussion around this issue.

> 96 Mincer, 1974

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