covered by social security compared to 50 percent for the region as a whole (ILO 2014; Vanek et

al. 2014). 13

2.4 Ethnicity in Peru

Another salient feature of the Peruvian economy is the marginalization of its large

indigenous population. 14 In this paper, we use self-identification, rather than language-based

measures, to construct a binary variable equal to 1 if the individuals self-identify as Quechua,

Aymara or Amazonian and 0 if otherwise. Self-identification is the preferred measure because it

reduces the under-estimation of indigenous populations, and does not conflate the mechanism of

language proficiency and general education, both of which may determine employment

outcomes. 15 However, in Section 7 we use native language as a robustness check our findings. We

use two sources of data for ethnicity in Peru. First, individual-level data is from Peru’s National

Institute of Statistics and Information, drawing on the 2010 National Household Survey (ENAHO).

EHAHO is a nationally representative survey carried out on a yearly basis with technical assistance

from the United Nations Commission for Latin America and the Caribbean (ECLAC in Spanish).

We draw on five survey modules: Individual and Household Characteristics, Education,


India and Mali display the highest informality rates, above 80 percent of non-agricultural

workers in the most recent studies


Peru's Afro-descendant population is also subject to discrimination, see Galarza et al. (2015)

and Miranda et al. (2013).


For a comprehensive comparison of different approaches to measure ethnicity in Latin

America see Gonzales (1994, p. 23-27).


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