rate that is higher than Quechuas and other indigenous people, but still significantly lower than Aymara men as well as nonindigenous men and women.

Together, these patterns suggest that while the actual universalization of education may close gaps in achievement across gender and ethnicity, as shown by the progression of the literacy rate for each cohort, any shortfall in complete coverage is likely to be borne primarily by indigenous people.

# _3.3. Empirical Model_

The empirical model used in this paper seeks to tease out the role of self-identified ethnicity and gender, both separately and jointly, in the observed education outcomes across different indigenous groups and age cohorts. To study this, an extension of the econometric model proposed by Taş, Reimão and Orlando (2014) is adopted. This model uses binary variables and interaction terms to quantify the penalty of being female and a member of an indigenous group, with respect to the reference group, which is nonindigenous men.<sup>14</sup> The reduced form model is given by: ���� ��������� ����� ����� ����� ������ ∗��������� ∗��������� ∗������� ����, where ���� is the education outcome of interest; �� is a dummy variable equal to zero if individual � is male and one if female; �� indicates self-identification as Aymara; �� selfidentification as Quechua; and �� self-identification as an indigenous person other than Aymara or Quecha. �� is a vector of control variables, which includes age and age-squared as well as a set of 115 dummy variables indicating individual �’s province of birth.<sup>15</sup> The control variables include place of birth in order to account for the fact that people born in urban areas or areas with better infrastructure and/or education systems may have better outcomes than those born elsewhere. This is a particularly important control if place of birth not only affects education outcomes, but is also correlated with ethnicity. This has been shown to be the case in Bolivia, since the Aymara population tends to be concentrated in the department of La Paz, where education outcomes are above the country average.<sup>16</sup> 14 Note that this empirical strategy is suitable for studying the role of intersectionality on basic outcomes, such as education, where methods that use a form of matching [e.g. Oaxaca-Blinder (Oaxaca 1973, Blinder 1973) or matching comparisons (Ñopo et al. 2010)] cannot be reliably employed. This is particularly pertinent for census data, which generally does not include variables (e.g., poverty at birth or parental education level at birth) that could serve as a good basis for matching when considering basic outcomes. More specifically, the current paper is particularly interested in education as an outcome, while education tends to be included in the matching characteristics when using these alternative methods. For more details, see Taş et al. (2014).

15 There are currently 112 provinces in Bolivia; the slightly higher number is explained by a very small number (<.01 percent) of respondents who were born in provinces that no longer exist due to changes in administrative divisions over the last century.

16 The regressions were also carried out using a dummy variable for rural residence, along the lines employed in Taş et al. (2014). The results are the same in sign and very similar in magnitude to the ones presented below. The specification presented in this paper is preferred, however, as place of birth is exogenous, while _current_ urban/rural residence may depend on the education outcome itself, as more educated people may be more likely to migrate from urban to rural areas relative to less educated individuals. Regressions were further carried out using separately the subsample of individuals born in the departmental capital and those born elsewhere; the results are again qualitatively similar to those presented here.

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