**b** . **A government budget composition variable** .  Given that both education and health are labor-intensive activities, the government’s labor policies will determine the efficiency with which outputs are delivered.  We choose a budget composition indicator to reflect this, in particular, the ratio of the wage bill to the total budget.  A higher ratio is expected to be negatively correlated with efficiency.

**c** . **Per-capita GDP** . We included the per-capita GDP to control for the BalassaSamuleson effect in comparing across countries.  If richer countries tend to be more inefficient (given higher wages in these countries), a negative sign is expected. However, it must be recalled that to obtain the efficiency scores in the “fist stage” we constructed an auxiliary variable (the orthogonalized public expenditure). Hence the inclusion of this variable in the second stage is an attempt to control for any remaining Balassa- Samuleson effects.

**d** . **Urbanization** . The clustering of agents make it cheaper to provide services in urbanized areas rather than in rural.  Higher degree of urbanization should reflect in higher efficiency, making positive as the expected sign of the coefficient on this variable.

**e. Prevalence of AIDS.** Based on WHO mappings of the disease, we included a dummy variable in the most severely affected countries to control for the role of this epidemic in the poor health outcomes.  Evans _et. al._ (2000) report that AIDS lowers the Disability adjusted life expectancy (DALE) by 15 years or more.  Aids also affects education outcomes both directly and indirectly (Drake, _et. al._ 2003): directly because school-age children are affected: UNAIDS estimates that almost 4 million children have been infected since the epidemic began, and two thirds have died. However, the indirect channel is relatively more important: AIDS leaves orphaned children that are more likely to drop-out of school or repeat. All these factors reflect how AIDS affect the demand for education.  But the supply is also affected by the decreasing teacher labor force due to illness or death, or the need to care for family (Pigozzi, 2004). Prevalence of HIV/AIDS should be negatively associated with education and health outcomes.  Consequently, efficiency scores should be negatively associated with the dummy variable.

**f. Income distribution inequality** . Ravallion (2003) argues that, besides the mean income, its distribution affects social indicators because their attainment is mostly determined by the income of the poor.  Hence, we controlled for the distribution of income by including the Gini coefficient as an explanatory variable.  Higher inequality is expected to be associated with lower educational and health attainments, making negative the expected sign of this variable.

**g** . **Share of public sector in the provision of service.** Services can be provided by both the public and private sectors, and efficiency indicators will differ across countries depending on the relative productivities of both sectors. Previous studies have included this variable to explain differences in outcomes (Le Grand, 1987; Berger and Messer, 2002) or efficiency scores (Greene, 2003a). The specific variable we included was the ratio of publicly financed service over the total spending (sum of private and public spending).

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