Identifying Gender-Specific Risk Factors for Income Poverty across Poverty Levels in Urban Mexico: A Model-Based Boosting Approach

Social Sciences

additive regression models
boosting algorithm
poverty
urban households
gender
Mexico
Author

Juan Armando Torres Munguía

Published

March 8, 2024

Doi

Abstract

This paper aims to identify income-poverty risk factors in urban Mexican households. Special emphasis is paid to examine differences between female- and male-headed families. To this, a dataset with 45 theoretical factors at the individual/household, community, and regional levels, integrating information from nine sources, is created. To these data, additive quantile models are estimated via the boosting algorithm. From a gender standpoint, the following main contributions come from this paper. First, educational lag is particularly relevant for female-headed households. Second, there is a gendered life cycle in the income trajectory for poor households with a head having a medium level of education. Third, some households, traditionally disregarded, are found to be even poorer: those lacking social connectedness, without credit cards, with an extended composition, in which the female head spends a large part of her time on housework, and families headed by young women with a medium level of education. Finally, communities and regions where families have a lower income-to-poverty ratio are characterized as having an unequal income distribution, lower human development, lower levels of women’s economic participation, poor quality of services, and lower gender-based violence levels in the public sphere but higher gender-based violence levels in the family context.

Citation

Torres Munguía, Juan (2024). Identifying Gender-Specific Risk Factors for Income Poverty across Poverty Levels in Urban Mexico: A Model-Based Boosting Approach. Social Sciences, 13 (3). DOI: 10.3390/socsci13030159. Retrieved from: https://www.mdpi.com/2076-0760/13/3/159