Abstract

DIAZ RODRIGUEZ, Héctor Eduardo; SOSA CASTRO, Miriam  and  CABELLO ROSALES, Alejandra. Determinants of debt in Mexican households: a neural network analysis. Prob. Des [online]. 2019, vol.50, n.199, pp.115-140.  Epub June 19, 2020. ISSN 0301-7036.  https://doi.org/10.22201/iiec.20078951e.2019.199.67463.

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.

Keywords : financial debt; consumer credit; acquiring power; commercial banking; artificial neural networks.

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