In general, we find that higher education levels of the household head tend to have a positive marginal effect on enrollment, but, holding other factors constant, is not significant in most countries.<sup>20</sup> This variable is of interest for several reasons. One is that parental education can influence how much parents invest in their children’s human capital development from the beginning of life onwards. Additionally, as in the case of household income, it can be an indicator of the level of economic mobility in society, where a lower influence of parental education on children ́s schooling would be an indication of greater mobility. To explore this further, we compute the unconditional correlation between parent ́s education and the value of the schooling gap, measured as the difference between the number of years of schooling expected given the age of an individual and the actual number of years completed, for all individuals in the 12-17 age range (Ferreira et al 2012).

Table 4 presents the results for each Central American country for circa 2000, 2005, and 2012. For each of these periods, the Latin American average is below the result for Central America, which suggests that in general, (schooling) mobility is lower in Central America. The countries with the highest correlation coefficients are Honduras and Nicaragua with values of 51 percent, suggesting that these two countries have the lowest educational mobility in the sub-region. Guatemala, Panama, and El Salvador follow with values of 47, 46, and 44 percent, respectively, and Costa Rica registers the lowest value with 40 percent. As for the evolution of these relationships, Guatemala is the country with the largest decline over time, followed by Panama, El Salvador, and Costa Rica. In contrast, Honduras and Nicaragua, show constant correlations since the year 2000, suggesting no progress in mobility.

The last set of marginal effects in Figure 17 focuses on the location of households in rural versus urban areas. The estimates show that in all countries, living in a rural area is significantly correlated with the probability of being enrolled during secondary age, and notably, this is the marginal effect with the greatest magnitude in El Salvador, Guatemala, Honduras, and Nicaragua, where living in a rural area is associated with a reduced probability of enrolment of 13, 15, 16, and 14 percent, respectively. There are several channels through which geographic location can influence school attendance, and given that this effect results from an estimation that controls for personal and household characteristics, it is possible that this is capturing the effect of access to services, especially at the US levels. For example, in Honduras, analysis finds that over 1,000 additional secondary schools in rural areas would be needed to provide access for all secondary-age youth who are currently out of school, compared to the fewer than 200 that are currently operating today (World Bank 2014b).

The correlation of service supply with enrollment can be directly examined in the case of El Salvador, where we have access to detailed information at the municipality level on the number of schools of each level from the 2011 National School Census, which we merge with the household survey. Table 5 presents our results and compares them with the base estimation from which the coefficients in Figures 15-17 are derived. Two additional estimations are presented. The first includes only the number of schools for each level in the municipality of reference, and its effect is not statistically significant. However, in the second estimation (third column of the table) we

> 20 The lack of significance is not entirely surprising given how many other variables related to household head’s education are being controlled for, including household poverty and single-parent status

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