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use the same formats, measures, and methodologies used to analyze gender differentials. However, data on ethnic gaps are available for only 7 of the 18 countries examined elsewhere in this book: Bolivia, Brazil, Chile, Ecuador, Guatemala, Paraguay, and Peru; as usual, earnings are computed as hourly earnings in the main job.
What Does the Literature Show? Some 28–34 million indigenous people live in Latin America, representing roughly 10 percent of the population (Hall and Patrinos 2006). In all countries, these groups are disproportionately represented among the poor and extreme poor, a situation that has not changed significantly over time. Moreover, since the 1990s, despite decreasing poverty rates in most countries in the region, poverty among indigenous groups either increased or declined at a significantly slower pace than in the rest of the population (Psacharopoulos and Patrinos 1994; Jiménez, Casazola, and Yáñez Aguilar 2006). On average, 63–69 percent of the indigenous population in the region is economically active. Indigenous people are overrepresented among the self-employed and in the agricultural sector. Despite higher levels of labor force participation over time, in most countries their earnings are significantly lower than those of their nonindigenous peers. This gap narrowed in the past decade, but it remains high in some countries, including Bolivia, Brazil, Chile, and Guatemala (ILO 2007). Attempts to explain ethnic earnings gaps have analyzed differences in human capital, especially education but also age, migrant status, and the interplay of ethnicity and gender. Despite improvements in educational attainment, indigenous groups earn significantly less than their nonindigenous counterparts (Psacharopoulos 1992). Although low education indicators may explain much of the persistent ethnic earnings differential in some countries, productive characteristics explain only half the earnings gap in other countries (Patrinos 2000). Rangel (1998) explores indicators such as quality of education, measured in terms of certification of teachers, teacher/ pupil ratio, and materials, as potential drivers of ethnic earnings differentials in the region. Hall and Patrinos (2006) consider differences in returns by levels of education. None of these studies fully explain pay differentials. Rangel (1998) shows that indigenous groups tend to be concentrated in low-paid sectors and low-skilled and low-paid jobs. One possible explanation for this concentration could be the impact of social networks, which may have a significant influence on the economic sector, type, and even quality of jobs obtained by indigenous workers, especially migrants. This factor is subject to significant heterogeneity across countries and across ethnic groups within countries (Hall and Patrinos 2006; Fazio 2007).