The resulting distribution of _net_ spending on education—after putting together gross public benefits and households’ contributions—reflects a progressive picture. This indicates that the progressivity of household contributions is often very influential in determining the final distributive profile of education spending. This is not the case in Liberia, where contributions are nonlinear, and in Thailand, where the progressivity of contributions is less marked and does not counteract the regressivity of the public spending.

Second, OIA reveals a somewhat different story (figures1b to 6b). Now, _average_ households’ private contributions toward educational services continue to be progressive (except again for Liberia) as they increase along with sets of circumstances that make children groups more likely to access a public school. _Average_ public benefits per children of school age are again typically regressive or neutral, as they were in the BIA. However, the OIA now reveals that the Thai distribution becomes more neutral than in the BIA case, while the Zambia distribution becomes slightly more regressive than the BIA indicated.<sup>22</sup> So, children pertaining to households with circumstances that make them more likely to attend school receive on average more unitary benefits than children with sets of circumstances that make them less likely to attend school. For example, in Côte d’Ivoire, girls in rural households with uneducated heads (no primary education completed) have a 39 percent probability of attending education. Boys in urban households whose heads have completed primary education or more have a 85 percent chance of attending school. In Tajikistan and Paraguay, the probabilities of attending school between groups with the least and most likely range only between 73 and 92 percent and between 77 and 96 percent, respectively.

Third, again, the extent of households’ private contributions among circumstance groups influences by and large the overall progressivity of the _net_ educational spending when using OIA. As it was in the previous analysis, Côte d’Ivoire, Tajikistan, Zambia, and Paraguay reveal a progressive distribution of _average_ net unitary benefits, while Liberia does not follow any clear pattern. Thailand’s results, however, diverge between the BIA and OIA: average net unitary benefits pass from a regressive pattern (increase with welfare level) to a more neutral pattern (close to uniform regardless of the favorable set of circumstances). This divergence results again from the neutrality of gross unitary benefits, a weak progressivity of households’ contributions, and high rates of enrollment in the country.

However, the comparison and generalization of results across these countries require a great deal of caution. There are discrepancies in the rates of enrollment in primary and secondary education within each country (table 1) and also across countries. Countries differ in the reference age group for which the

> 22 A possible reason to explain the change in Thailand is that the inclusion of circumstances other than incomes and geographical department reduces the influence that the concentration of richer populations in Bangkok has on the distributive profile of educational spending.

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