Characterizing uninsured population in Mexico: a multinomial analysis

José González-Nuñez, Salomón Domínguez and Karl J. Zimmermann

Review of Behavioral Finance, 2024, vol. 17, issue 1, 83-99

Abstract: Purpose - This research highlights the importance of understanding the characteristics of the uninsured population in Mexico, as it is closely related to economic growth. Those characteristics that are not economic but behavioral are especially important to incentivize insurance purchases in the population with sufficient resources. Design/methodology/approach - Considering the main reason for not having insurance, this research classifies the Mexican adult population into four categories using a multinomial logit model and the National Survey of Financial Inclusion (2021). Findings - The adult Mexican population can be divided into four categories: No money, Not aware or does not trust, No need, Other; this division allows comparisons between categories at 95% confidential level. The statistically significant variables were Mobile phone-ownership, Education level, Age, Financial behavior and Locality, while the variables, Financial literacy and Gender, were not. The variables that strongly characterize the uninsured population with sufficient resources (42.1%) are associated with economic factors (mobile phone ownership) and people’s behavior (Education level, Age, Financial behavior and Locality). This presents an excellent opportunity for policymakers to develop public policies encouraging insurance purchases. Originality/value - Various empirical studies have focused on determining the economic, demographic and institutional factors that determine insurance tenure. Still, no empirical evidence has been found to characterize the uninsured population. This study aims to help policymakers develop public policy for the uninsured population to encourage them to purchase insurance. This research contributes to empirical theory in three ways: First, it identifies a large market in Mexico; the uninsured population in this country is about 80%. Second, it segments the adult population into categories to analyze better. Third, the characteristics of the population that has sufficient resources to take out insurance but has none can be found.

Keywords: Insurance; Behavioral economics; Behavioral finance; Multinomial logistic model; National financial inclusion survey; G41; D91; C51; G10 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:rbfpps:rbf-11-2023-0313

DOI: 10.1108/RBF-11-2023-0313

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