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Economic Integration of Afro–Latin American Immigrants in Mexico

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Despite Mexico’s increase as a destination country (although < 1% of its population was born abroad, and most immigrants are U.S.–born minors of return migration), its Latin American immigrant population has increased considerably. Mexican ethnicity scholarship has traditionally focused on indigenous populations, but recent studies called for a better understanding of African descendants’ experiences. Integration and assimilation theories (for other contexts) highlight ethnicity’s role, but how migration and ethnicity intersect in the Mexican context is unclear. We study differences in labor market integration of Latin American immigrants. Using Mexican 2015 Intercensal Survey and 2020 Census data, we estimate OLS models to understand how Afro-descendant self-identification, migration, and birth country shape earnings. Results show higher earnings for immigrant populations, except for Central Americans, and an interaction effect of Afro-descendance, immigration status, and birthplace. Our findings suggest continued research on integration and racialization processes in Mexico and other Latin American countries.

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Data Availability

Original microdata are publicly available from the INEGI website at Mexican 2015 Intercensal Survey and 2020 Population Census

Code Availability

Upon request.


  1. LAC comprises Mexico, Central America, the Caribbean, and South America. We use LAC, Latin America and the Caribbean, and Latin America interchangeably.

  2. An Afro-descendant is “a person of African origin who lives in the Americas and in all areas of the African diaspora as a result of slavery, having historically been denied the exercise of their fundamental rights” (Office of the United Nations High Commissioner for Human Rights (OHCHR), 2002).

  3. Research using the MIS and other surveys has shown that Afro-descendants encounter disadvantages in the earnings distribution (Villarreal & Bailey, 2019) and intergenerational social mobility (Solís et al., 2019). However, dissimilar results may be explained by the methodological approach. First, Villarreal and Bailey (2019) used Afro-descendant self-identification as an endogenous predictor of income using a quasi-experimental design where two instrumental variables are considered: (1) if an individual lives in a state where the Mexican government carried out the campaign to increase the self-identification of Afro-Mexicans, and (2) the genomic ancestry of the Mexican population of ten states. Second, Solís et al. (2019) used data from the Intergenerational Social Mobility Module 2016 that used “black or mulatto” as an identification category. It is not possible to equate these concepts with the Afro-descendant category used in census data or MIS.

  4. Scholars in LAC have discussed the divergences that exist––both in terms of self-identification processes and its social consequences––when ethnonyms such as Afro-descendant and/or black and mulatto are used. Research has established that the signifiers of what is Afro-descendant and/or Black can reflect dissimilar experiences of social reproduction, so that those who recognize themselves as Black or mulatto do not necessarily self-identify as Afro-descendant and vice versa (Restrepo, 2021; Segato, 2006; Wade, 2013a).

  5. We exclude this population due to data limitations associated with very small sample size. Sample size of pooled 2015–2020 data of indigenous South Americans (n = 61) and from the Caribbean (n = 2) is almost null, which does not allow comparisons between the immigrant and native population, the main purpose of the paper.

  6. See Cimadamore et al. (2006) and Puyana Mutis and Horbath (2019).

  7. These are the two most recent nationally representative data sources collecting information on the population that self-identifies as Afro-descendant or Afro-Mexican. Pooled data also allow for a larger sample. We control for recent migration and year to account for variations in the sociodemographic composition derived from changes in migration patterns and labor market integration.

  8. Microdata exclude population living in collective dwellings. Therefore, our analyses exclude transit migrants and other people on the move, living in shelters and nonprivate dwellings.

  9. Due to small sample size, we cannot define a finer measure of birthplace.

  10. Afro-descendant self-identification is captured in 2015 as those who considered themselves “black, Afro-Mexican or Afro-Descendent according to their culture, history and traditions” and in 2020 as those who consider themselves “Afro-Mexican, Black or Afro-descendent due to their ancestors, costumes and traditions.” The wording changed slightly in the questionnaire.

  11. We estimate binomial logistic regression models to analyze selectivity into employment. Results show that immigrants from the Caribbean and South America are less likely to be employed than those born in Central America. Likewise, recent Afro–Latin American immigrants present the greatest disadvantages when it comes to entering the workforce (see Appendices 3, 4).


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We appreciate the comments from Erin Hamilton and Nicole Denier to a preliminary version of this paper.


Johanna Navarrete received funding for her doctoral studies from CONACYT under its national program of scholarships for graduate studies (CONACYT, 2018-2). Claudia Masferrer is a member of the National Researchers System (CONACYT); this research is part of the project “Geographic Variations in the Integration Processes of Young Migrants: The Importance of the Local Context of Return and Reception” funded by the Sectoral Fund for Social Development (Fondo Sectorial de Desarrollo Social/Sedesol-Conacyt) (#292077), PI: Claudia Masferrer.

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JN and CM: study conception and design; data analysis and interpretation of results; draft manuscript preparation.

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Correspondence to Johana Navarrete-Suárez.

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Appendix 1

See Table 3.

Table 3 Population distribution for LAC countries by time since arrival and ethnicity

Appendix 2

See Fig. 3.

Fig. 3
figure 3

Activity status. Sources 2015 Mexico Intercensal Survey, 2020 Mexico Census

Appendix 3

See Table 4.

Table 4 Logistic regression models of labor market participation, Mexico 2015–2020

Appendix 4

See Fig. 4.

Fig. 4
figure 4

Average estimated probabilities of occupation by sex, time since arrival, and ethnicity in Mexico, 2015–2020. Sources Pooled data from 2015 Mexican Intercensal Survey and 2020 Mexican Census. Note The mean estimated probability was calculated from the models with interactions as the average of the estimated probability for the individuals in each group. *Different (p < .05) from all groups regardless of Afro-descendancy. +Not significantly different (p < .05) from nonrecent Afro-descendant immigrants

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Navarrete-Suárez, J., Masferrer, C. Economic Integration of Afro–Latin American Immigrants in Mexico. Popul Res Policy Rev 41, 1873–1892 (2022).

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