percent for 1990-1999, and 60 percent for the 2000-2011 period. The surveys are representative of the total population of each country, with the exception of Argentina and Bolivia for surveys prior to the 2000s and Uruguay, where the samples are for urban areas only. Appendix Table A.1 identifies the years which are available for each country.<sup>8</sup> Since we have access to the micro data of each survey it is possible for us to standardize relevant indicators such as household structure, age, gender, economic activity, schooling level, school attendance, socioeconomic characteristics, education, income, etc. in order to produce comparable data within countries, and across countries and years.

It is important to note that the homogenization process undertaken considers that different countries have different arrangements in terms of the age for attending Primary, Lower Secondary and Upper Secondary, respectively, which is an important comparability factor for the present analysis. In this regard, we follow the ICSED 1997 classification by UNESCO when available - which identifies the official age at which youth should be in the schooling system, by education level- and official local data elsewhere.<sup>9</sup> The definitions are summarized in Appendix Table A.2.

The evolution of school enrollment by using snapshots of different generations observed at school age at different years is shown in Figure 1, which uses the complete database of 234 household surveys. Panel A shows the decadal regional average proportion of individuals in the relevant age groups, attending Lower Secondary, Upper Secondary and Higher Education, respectively.<sup>10</sup> A first feature of interest is that for the three levels, there is a growing proportion of youth in school. The shares increase from around 80 to 89 percent for Lower Secondary, from 57.5 to 70.9 for Upper Secondary, and from 20.8 to 31.6 for Higher Education. This means that if employment rates for 15-18 and 19-24 year olds had remained at least constant over time, there would have been an important reduction of more than 10 points in the share of Osow youth when transiting these ages. The relative stability in the shares of this group shown in de Hoyos et.al. (2013) and 8These surveys are compatible with the database in de Hoyos, et.al. (2013). However, rather than relying the data processed by SEDLAC, we use the original surveys to be able to construct additional variables used later in Section 3 in our econometric estimations. Is is important to stress that the picture on the evolution of the share of Osow youth in LA by gender groups with our data is practically the same as that in de Hoyos, et.al. (2013). It is also similar to the trends presented in Cardenas, et.al. (2011) although the levels differ with respect to this study since those authors do not consider those searching for work in their calculations.

9ICSED definitions can be found at <u>http://www.uis.unesco.org/Education/ISCEDMappings/Pages/default.aspx.</u>

> 10Since our household survey database generates an unbalanced panel of countries and years due to differences in timing of the surveys we compute decadal averages by interpolating values for each country between each two points in time for which there is data. The averages are not population weighted, although a very similar picture emerges when using population weights.

6