Determinants of poverty among Indigenous people in Mexico's Guerrero Mountain Region

Jorge Mora‐Rivera, Isael Fierros‐González and Fernando García‐Mora

Development Policy Review, 2024, vol. 42, issue 1

Abstract: Motivation The eradication of poverty is one of Mexico's greatest challenges. This challenge is even greater for Indigenous communities, where seven out of 10 people were living in poverty in 2018. Despite the economic, social, and cultural impacts on Indigenous people, there has been scant literature addressing the determinants of Indigenous poverty in Mexico, while studies on the Guerrero Mountain Region (GMR) are scarcer still. Purpose This study aims to identify the socioeconomic and contextual determinants of income and multidimensional poverty in the GMR, one of the poorest regions in Mexico and Latin America, inhabited primarily by Indigenous people. Methods and approach We use data on 989 individuals in the GMR, collected during the 2018 Socioeconomic Conditions Module of Mexico's National Household Income and Expenditure Survey. To examine the main determinants of individual poverty, we use Bayesian logistic regression (BLR), which allows us to use the data to update information about the parameters and evaluate their distributional properties. The method simplifies multi‐causal elements by classifying them into categories of well‐being that incorporate more than economic factors. Findings The income‐poor population is also multidimensionally poor. Education helps to reduce poverty as households that spend more on schooling are less likely to be poor. Households with many members, those with high dependency ratios, and those with members living with disability all tend to be poor. Households with access to landlines and the internet are less likely to be poor. Policy implications More diagnosis of poverty is needed. This should consider overlapping vulnerabilities (institutional, socioeconomic, environmental, and sociocultural) in this region for each Indigenous group. Public policies need to be monitored for performance.

Date: 2024
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