Determinants of debt in Mexican households: A neural network analysis

Abstract

In recent years, consumer credit in Mexico has grown in significant ways. Credit cards, which represent 52% of credit in the country, grew by 19% from 2011 to 2018, while the average debt per card increased by 62%. This increase generates problems of over-indebtedness in Mexican households. Using microdata from the National Income and Expenditure Survey (NIES), this research seeks to identify the factors that affect over-indebtedness in households, and to offer an explanation of said phenomenon using a neural network methodology. The principal determinant of over-indebtedness in Mexican households is the existence of bank credit, given that this indicates a long-term transfer of family income to the financial sector.