instruments that are correlated with our measure, we find a significant positive effect on the level of GDP per capita, with similar coefficients in every case.<sup>22</sup>

# <Table 5 here>

Next, we examine the relationship between equality of opportunity and other development outcomes, namely institutional quality and infant mortality.<sup>23</sup> Table 6A presents the results. Higher equality of opportunity (measured using PISA scores) predicts higher institutional quality of a country (see Appendix 2 for how this variable was created). Controlling for inequality of outcomes with the Gini index of income, whose coefficient is not statistically significant, the coefficients of both the HOI and the D-Index remain statistically significant. These coefficients also increase in size once we take into account the Gini of income. Interestingly, the magnitude of the effects is higher using IVs than for OLS, suggesting that the causal effect of inequality of opportunity on development outcomes is actually understated by the OLS estimation.

Table 6B shows the results from the same analysis as above, re-defining the “opportunity” as timely completion of six years of education. Equality of opportunity measured with this variable does not have a clear relationship with institutional quality, with some specifications having significant results and others not. For the other development outcomes, infant mortality and malnutrition, the results are clear: equality of opportunity measured by the HOI or D-Index of timely completion of six years of education predicts lower infant mortality and malnutrition rates.<sup>24</sup> <Tables 6A and 6B here>

# **Estimated magnitude of economic impacts**

How much does equality of opportunity matter as a driver of development? Using the data from PISA, a one standard deviation increase in the Human Opportunity Index (33 percentage points) increases income by 0.718 standard deviations, increases institutional quality by 0.814 standard deviations, and reduces infant mortality by almost one standard deviation (Table 7). An increase of one point (9.4 percentage points) in inequality of opportunity or the D-Index reduces per capita income by almost 10 percentage points and institutional quality by 2.3 percentage points, and increases infant mortality by almost 3 percentage points. By these estimates, the extent to which inequality of opportunity hinders development is economically meaningful, in addition to being statistically significant.

We also compute the elasticity of GDP per capita to HOI and find that a 1 percent higher HOI for a given country would lead to 2.3 percent higher GDP per capita. This means, for example, that if the current HOI for Argentina were higher by 1 percent (around 0.4 points), its GDP per capita would be higher by 150 USD.

> 22 With school attendance (10-14 years) or starting primary school on time (6-7 years) as the indicator of opportunity, there appears to be no causal relation. We believe this result is due to the fact that attendance in school and timely start to schooling are not good proxies for education achievement, which is what determines opportunities. Therefore, in the rest of the paper we use only the measure derived from PISA test scores and timely completion of six years of schooling.

> 23 For this specification we do not use malnutrition as a development outcome as only few observations were available to estimate the first stage.

> 24 As results with D-Index are very similar, we omit them from Table 6B to reduce the number of tables. Results are available upon request.

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