El trabajo infantil en México: Factores explicativos

Using data from the National Child Labor Survey (ENTI) for 2019 and 2022, the probability that a child or adolescent is in a condition of child labor is analyzed. For each year, a logistic regression is estimated and explanatory variables such as sex, reason for work, size of locality, region, and whether they received financial support through a scholarship or other government program are considered. It is analyzed whether economic incentives contribute to reducing the possibility of performing prohibited, risky, or inappropriate work. For both years, the variables together are statistically significant; however, in 2019, economic support does not significantly determine the probability of the event occurring. In 2022, economic support influences a decrease in labor participation and all regions, with respect to the South, show a decrease in child labor. The regions that report the greatest marginal change for the last year are the North, Capital, and Pacific regions. Living in towns with fewer than 2,500 inhabitants also increases child labor participation, as well as the fact that children have to work to financially support their households.

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Publication Details

Journal
Revista de Ciencias Sociales y Humanidades
Published
2025-01-01
DOI
https://doi.org/10.20983/noesis.2025.1.5
Primary Topic
Poverty, Education, and Child Welfare
Type
article
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article

El trabajo infantil en México: Factores explicativos

Jesús Eduardo López Mares, Juan Manuel Ocegueda Hernández, Rogelio Varela Llamas
Revista de Ciencias Sociales y Humanidades
Poverty, Education, and Child Welfare
article

El trabajo infantil en México: Factores explicativos

Jesús Eduardo López Mares, Juan Manuel Ocegueda Hernández, Rogelio Varela Llamas
article en

Abstract

Using data from the National Child Labor Survey (ENTI) for 2019 and 2022, the probability that a child or adolescent is in a condition of child labor is analyzed. For each year, a logistic regression is estimated and explanatory variables such as sex, reason for work, size of locality, region, and whether they received financial support through a scholarship or other government program are considered. It is analyzed whether economic incentives contribute to reducing the possibility of performing prohibited, risky, or inappropriate work. For both years, the variables together are statistically significant; however, in 2019, economic support does not significantly determine the probability of the event occurring. In 2022, economic support influences a decrease in labor participation and all regions, with respect to the South, show a decrease in child labor. The regions that report the greatest marginal change for the last year are the North, Capital, and Pacific regions. Living in towns with fewer than 2,500 inhabitants also increases child labor participation, as well as the fact that children have to work to financially support their households.

Revista de Ciencias Sociales y HumanidadesVol. 34(67)
Openalex Percentile: Top 95%
Poverty, Education, and Child Welfare
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