Determinants of Financial Literacy: Analysis of the Influence of Socioeconomic and Demographic Variables^*,^**

ABSTRACT

Financial literacy helps individuals make more assertive and efficient decisions in the monetary context of their lives. This study has as its central axis developing a model that explains the individuals' financial literacy level through socioeconomic and demographic variables. The sample consists of 1,400 individuals living in Rio Grande do Sul, Brazil, and data analysis was performed by using descriptive statistics and multivariate analysis techniques. As an indicator of the financial literacy level, a measure with three constructs was adopted: financial attitude, financial behavior, and financial knowledge. Logit and probit models were estimated from these explanatory variables: gender, marital status, dependent family members, occupation, age, educational level, father's educational level, mother's educational level, individual income, and family income. Marginal effects (incremental propensity) were positive and statistically significant at the usual levels for these variables: gender (9.56%), educational level (2.54%), individual income (6.32%), and family income (3.73%). The marginal effects (incremental propensities) were negative and statistically significant for the dummy dependent family members (-7.51%), indicating that men who do not have dependent family members and have higher educational and both individual income and family income levels are those who are more likely to belong to the group with high financial literacy levels. Furthermore, it was found that most respondents (67.1%) were classified as having a low financial literacy level. These findings confirm the urgency and need for devising effective actions to minimize the issue of financial illiteracy. It is particularly suggested that major efforts are undertaken to achieve women having dependent family members and low educational and income levels. Such a study is justified by the need to create a model that allows identifying the Brazilians' financial literacy level from socioeconomic and demographic variables. This identification may be useful, for instance, in assisting the various economic player to design financial strategies and products suitable to the customers profile. From the government viewpoint, it may enable, for instance, identifying the most vulnerable groups and thus focus on actions to improve the financial literacy level of these specific groups.

Keywords:
financial literacy; forecasting models; socioeconomic variables; demographic variables