Mapping the Financial Well-Being of Brazilians: Socioeconomic and Demographic Variables in Focus

Abstract

Enhancing financial well-being has been a challenge for countries, especially due to its positive impacts on economic growth, quality of life, and the physical and mental health of citizens. This article’s main objective is to estimate the level of perceived financial well-being in the Brazilian population and investigate how socioeconomic and demographic variables influence this perception. Using a scale adapted for emerging countries, this study employed a large sample of 3,998 participants, covering all five regions of Brazil. The results reveal that a significant portion of the Brazilian population presents a level of perceived financial well-being below the ideal, reflecting a concerning financial insecurity that affects more than 60% of the respondents. Additionally, it was observed that certain groups, such as young people, black and brown individuals, members of the lower socioeconomic classes, with educational levels up to completed elementary school, and self-employed workers, are particularly vulnerable. These findings point to the need for more targeted attention from society and government agencies to mitigate disparities and promote the financial well-being of all strata of the Brazilian population.

Introduction

Financial well-being is a topic of growing importance in the economic and behavioral literature, especially in times of rapid change and global uncertainty (Sorgente et al., 2022, 2024). The Covid-19 pandemic, for example, exacerbated financial challenges, impacting global markets and individual financial conditions, resulting in job losses, declines in Gross Domestic Product (GDP), and increased inflation, with particularly intense effects in developing countries like Brazil (Kumar et al., 2023).

Originally conceptualized based on an individual’s income (Ghazali et al., 2020; Wilmarth, 2021), financial well-being has evolved to encompass broader aspects. Today, it is characterized by the ability to manage day-to-day finances, absorb financial shocks, achieve financial goals, build savings, and have financial freedom (Consumer Financial Protection Bureau, 2015), being intrinsically related to financial behavior, financial knowledge, and personal traits (Fan & Henager, 2022).

It is possible to observe in the literature different ways of measuring financial well-being, with an objective perspective that encompasses factors such as income and wealth, and a subjective perspective, which prioritizes emotional and cognitive assessments of one’s own financial situation (Sorgente et al., 2022). In this line, financial well-being is generally measured in a multidimensional way (Bashir & Qureshi, 2023; Kaur et al., 2021; Riitsalu et al., 2023; She et al., 2023; Vieira et al., 2023).

However, despite its relevance, most studies still focus on developed countries, leaving significant gaps in the understanding of financial well-being in emerging economies, such as Brazil (Kumar et al., 2023). In this sense, Brazil is experiencing an especially challenging financial context, with more than 78% of families in debt (Confederação Nacional do Comércio, de bens, serviços e turismo-CNC, 2024), persistent gender wage inequalities (Rodrigues, 2023), and occupational segregation by gender and race (Souza Silveira & Siqueira Leão, 2021).

In addition, there is also a research gap regarding differences in the perception of financial well-being in Brazil. The international literature points to the existence of significant differences for variables such as gender (Chatterjee et al., 2019; García-Mata & Zerón-Félix, 2022), marital status (García-Mata & Zerón-Félix, 2022; Hira & Mugenda, 1998), income (Adam et al., 2017; Botha et al., 2021; Chatterjee et al., 2019; Choi et al., 2020; García-Mata & Zerón-Félix, 2022; Hira & Mugenda, 1998; Michael Collins & Urban, 2020; Neman, 2020; Vera-Toscano et al., 2006), ethnicity (Husniyah et al., 2012), and age (Jhuremalani et al., 2022).

Thus, the objective is to identify the perceived financial well-being of Brazilians and the differences according to various socioeconomic and demographic variables. To this end, the level of perceived financial well-being will be constructed as proposed by Vieira et al. (2023).

The innovation of this study lies in its focus on the Brazilian context, an emerging economy, where research on financial well-being is still scarce. Additionally, due to the lack of evidence in the literature on the behavior of financial well-being according to social class, this variable will be given special emphasis among the studied variables, seeking to bring new evidence and contribute to this gap. Another distinguishing feature of this study is the sample, which includes Brazilians from all regions of the country and with different socioeconomic and demographic profiles.

This study contributes to understanding the dynamics of financial well-being in Brazil, offering valuable insights for public policies and interventions focused on improving the financial health of the population. Understanding disparities in financial well-being is essential for the development of more inclusive and effective strategies in financial literacy and economic support, especially in a post-pandemic recovery context, where such inequalities may have been exacerbated.

Theoretical Framework

The theories that have been widely used in financial well-being studies are the Theory of Planned Behavior, Social Identity Theory, and Family Financial Socialization Theory. The Theory of Planned Behavior (Ajzen, 1991) is the most widely used in the literature (Bashir & Qureshi, 2023). According to this theory, behavior is influenced by three factors: attitudes toward the behavior, perceived behavioral control, and subjective norms. Ajzen (1991) explained that attitudes reflect an individual’s personal evaluation of the behavior, perceived behavioral control refers to the ease or difficulty of performing the behavior, and subjective norms represent the social expectations surrounding the behavior. Thus, the Theory of Planned Behavior offers a framework for explaining financial well-being by linking individuals’ rationales to their financial behavior (García-Mata & Zerón-Félix, 2022).

In addition to the diversity of theories, there is no consensus on the concept of financial well-being. Among the most commonly used definitions is that of the Consumer Financial Protection Bureau (2015). Therefore, in this study, financial well-being refers to a state in which an individual has control over their finances, possesses sufficient resources to manage unexpected events, is on track to achieve their goals, and enjoys the financial freedom to make choices that enhance their life experience (CFPB, 2017; Mahendru, 2021). In addition to positively impacting the individual lives of people, good levels of financial well-being in a population help economies to prosper and function properly (García-Mata & Zerón-Félix, 2022).

To better understand the well-being of individuals, two strands stand out proposing to evaluate objective and subjective aspects (Sorgente & Lanz, 2017). The objective approach mainly encompasses the economic resources of individuals, such as wealth, income, financial ratios, and liquidity (Chatterjee et al., 2019). However, it was observed that people with similar financial levels can present differences in terms of feelings of joy, fulfillment, and happiness, leading to the development of studies focused on financial satisfaction (Xiao et al., 2009).

In view of this, subjective well-being encompasses contentment in various areas, including interpersonal, community, professional relationships, physical, psychological, and economic sensations (Prilleltensky et al., 2015). This feeling of happiness or satisfaction can be linked to a sense of security, the ability to meet personal needs, or the possibility of achieving a desired standard of living (Chatterjee et al., 2019).

In the subjective line, several scales have emerged seeking to measure financial well-being. From this, the Consumer Financial Protection Bureau (2015) developed an assessment model based on cognitive interviews, factor analysis, and psychometric tests. However, the scale has greater adherence to developed economies and needs to be readjusted to adapt to the different realities and sets of public policies of local contexts (Organization for Economic Co-operation and Development, 2018; Sorgente & Lanz, 2019). Thus, Vieira et al. (2023) developed a scale of perceived financial well-being adapted to the context of developing countries.

Regarding the antecedents of financial well-being, they can be broadly categorized into individual-related factors, family/household/peer-related factors, and community/societal-level factors. Among the individual factors are socio-demographic characteristics, traits, skills, attitudes, motivation, and life events (Bashir & Qureshi, 2023). In this study, the focus is on socio-economic and demographic characteristics. Table 1 presents a summary of the evidence for these characteristics.

Table 1.

Summary of the Relationship Between Socioeconomic and Demographic Variables and Financial Well-Being.

Variables	Observed differences	Authors
Sex	Men have higher levels of financial well-being.	Dickason-Koekemoer and Ferreira (2019), Fu (2020), Gonçalves et al. (2021), Lind et al. (2020), Strömbäck et al. (2020), Zyphur et al. (2015), Zhang and Fan (2024), Wijaya et al. (2024)
	Women exhibit lower financial literacy and consequently lower financial well-being.	Al-Bahrani et al. (2020), Gerrans et al. (2014), Gonçalves et al. (2021), Karakurum-Ozdemir et al. (2019)
	No differences were found between men and women.	Michael Collins and Urban (2020)
Age	Older individuals demonstrate higher financial well-being compared to younger ones	Brown et al. (2014), Michael Collins and Urban (2020), García-Mata and Zerón-Félix (2022), Kamble et al. (2024), Penn (2009), Plagnol (2011), Zhang and Fan (2024)
	Emerging adults (18–29 years old) show higher financial well-being than younger ones (18–24 years old).	Sorgente and Lanz (2019)
Dependents	Dependents at home negatively influence financial well-being.	Keese (2012), Kunkel et al. (2015), Penn (2009)
	Women, after becoming mothers, may sacrifice their careers and reduce their earnings, negatively impacting financial well-being.	Mogaji et al. (2021), Tekavc et al. (2020)
Marital Status	Married individuals have higher financial well-being.	Dickason-Koekemoer and Ferreira (2019), Iramani and Lutfi (2021), Kamble et al. (2024), Lee et al. (2020), Zhang and Fan (2024)
	Single individuals have higher financial well-being.	Gutter and Copur (2011)
	Single individuals exhibit lower financial well-being.	Fan and Henager (2022)
	Unmarried women have lower satisfaction with financial management compared to married women.	Fan and Babiarz (2019)
	Divorced women have lower financial well-being than divorced men.	Fan and Babiarz (2019)
Education Level	Individuals with higher levels of education tend to have higher financial well-being.	Kamble et al. (2024), Penn (2009)
	Individuals with lower levels of education tend to have lower financial well-being.	Plagnol (2011)
Race	White race has higher levels of financial well-being compared to other races.	Clark et al. (2021), Dickason-Koekemoer and Ferreira (2019), Lee et al. (2020), Mogaji et al. (2021)
Housing	Owning a home contributes to higher levels of financial well-being.	Vieira et al. (2021), Xiao and O’Neill (2018)
Occupation	Unemployed individuals or those without income have lower levels of financial well-being.	Dickason-Koekemoer and Ferreira (2019), Fan and Henager (2022), Lee et al. (2020), Roll et al. (2022)
	Having a stable career positively impacts financial well-being.	CFPB (2015), García-Mata and Zerón-Félix (2022), Mahendru (2021)
	Retired individuals have higher financial well-being compared to other occupations.	Chatterjee et al. (2019), Soepding et al. (2022), Xue et al. (2020)
Income	Individuals with higher income levels exhibit higher financial well-being.	Michael Collins and Urban (2020), Narges and Laily (2011), Dickason-Koekemoer and Ferreira (2019), Fu (2020), Iramani and Lutfi (2021), Kaur et al. (2021), Lee et al. (2020), Riitsalu and Murakas (2019), Vlaev and Elliott (2014), Zyphur et al. (2015), Wijaya et al. (2024)
	Wealthier families have higher financial well-being than poorer families.	Aubrey et al. (2022)

Source. Authors’ own compilation (2024).

It is observed that in Table 1, the social class variable does not appear, but studies have already identified differences for the income variable. Lee et al. (2020), Michael Collins and Urban (2020), Riitsalu and Murakas (2019), Zyphur et al. (2015) observed that the income variable has a positive correlation with financial well-being. Dickason-Koekemoer and Ferreira (2019) found that individuals with lower annual incomes have lower levels of financial well-being. In these studies, the income variable was treated as a quantitative variable (monetary values) or in classes divided according to the researcher’s interest.

However, we understand that instead of a statistical classification (by quartiles) or for convenience, a socioeconomic stratification is more promising, especially in developing countries. Socioeconomic status is important for market segmentation in developing countries because emerging economies tend to be more hierarchical and exhibit greater separation between social classes, giving class distinctions a greater role than in economically developed societies (Burgess & Steenkamp, 2006). And a particular social class tends to persist for many years and share a broad way of life, have a more or less defined culture, and have similar concerns (Cottrell & Roslender, 1986). Different socioeconomic strata can reflect differentiated values, attitudes, social norms, lifestyles, and consumption patterns (Kamakura & Mazzon, 2016).

Method

Sample and Data Collection

Considering a population of 190,755,799 Brazilians (Brazilian Institute of Geography and Statistics, 2010), a confidence level of 95% and a margin of error of 2%, the desired minimum sample size was 2,401 respondents. The project was approved by the Research Ethics Committee (CAAE no. 53589721.5.0000.5346) and the respondents signed the Informed Consent Form (TCLE).

Ten interviewers were previously trained by the researchers to conduct the survey. Data collection instruments were printed and administered by interviewers in public spaces across all regions of the country during the first half of 2023. Individuals aged 18 years or older were included based on the study’s inclusion criteria.

The data collection took place in 32 Brazilian cities, and the obtained sample was 3,998 respondents. Table 2 presents the profile of the respondents.

Table 2.

Profile of Respondents According to the Variables Sex, Age, Marital Status, Race/Ethnicity, Education Level, Housing Type, and Occupation.

Variables	Options	Frequency	Percentage
Sex	Male	1,623	40.9
	Female	2,344	59.1
Age	18–32 years	1,027	26.0
	33–44 years	953	24.2
	45–61 years	1,018	25.8
	Over 62 years	945	24.0
Marital status	Single	1,292	32.6
	Married or in a stable relationship	1,981	49.9
	Separated/divorced	409	10.3
	Widowed	263	6.6
	Other	23	0.6
Race/Ethnicity	White	2,818	70.9
	Black	355	8.9
	Brown/mixed-race	742	18.7
	Asian	26	0.7
	Indigenous	22	0.6
	Other	11	0.3
Education Level	Incomplete elementary education	565	14.4
	Complete elementary education	326	8.3
	Technical course	253	6.4
	High school	992	25.2
	Higher education	921	23.4
	Specialization or MBA	502	12.8
	Master’s or doctorate	377	9.6
Has Dependents	None	1,507	38.0
	1	1,250	31.5
	2	694	17.5
	3	298	7.5
	4 or more	213	5.5
Housing Type	Own	2,444	61.8
	Rented	861	21.8
	Borrowed	250	6.3
	Financed	283	7.2
	Other	115	2.9
Occupation	Public sector employee	1,043	26.6
	Salaried employee	1,354	34.5
	Self-employed professional	122	3.1
	Freelancer	602	15.4
	Business owner	239	6.1
	Unemployed	307	7.8
	Other	254	6.5
Social Class	A	150	3.8
	B	437	10.9
	C	1,428	35.7
	D	1,160	29.0
	E	823	20.6

Source. Survey data (2024).

According to Table 4, the sample is predominantly female, white, and with their own home, corresponding to 59.1%, 70.9%, and 61.8% of the sample, respectively. Regarding age, there is a balance between the age groups, with the average age of the sample being 46 years old. The most prevalent marital status of the respondents is married. Regarding education and occupation, individuals with high school or higher education who work as public employees or salaried employees predominate.

Instrument

In order to achieve the proposed objective, a survey research was carried out with a structured questionnaire composed of two blocks. The first block aims to collect sociodemographic and profile aspects of the respondents with nine questions related to age, gender, race, marital status, occupation, education, number of financial dependents, housing, and income.

The second block consists of 23 questions aimed at measuring perceived financial well-being as proposed by Vieira et al. (2023). The questions have response alternatives according to a five-point Likert scale, ranging from 1-never to 5-always. Perceived financial well-being is formed by four dimensions: financial security; financial tranquility; financial freedom; satisfaction with financial management.

Financial security is related to socioeconomic variables such as income, occupation, and psychological aspects (Chatterjee et al., 2019; Choi et al., 2020), and deals with the ability of individuals to meet all their current and future financial needs (Netemeyer et al., 2018) and to deal with financial setbacks (CFPB, 2015, 2017). Financial tranquility, on the other hand, is related to aspects related to the feeling of having the money one needs, paying bills on time (Organization for Economic Co-operation and Development, 2018), and being able to enjoy life without worrying about money (Netemeyer et al., 2018).

The financial freedom item, the third dimension evaluated, is related to the possibility of the individual having financial autonomy and having access to non-essential consumer goods and services (Michael Collins & Urban, 2020), in addition to having money left over after paying their main expenses (Kempson et al., 2017). Finally, satisfaction with financial management is connected to financial knowledge and the individual’s ability to adequately plan their finances (Organization for Economic Co-operation and Development, 2018; Zhao & Zhang, 2020) and manage their finances (Kempson et al., 2017).

Regarding reliability, the four dimensions showed Cronbach’s alpha values above .9 in the original scale development study by Vieira et al. (2023). In our study, the dimensions also demonstrated excellent internal consistency: Financial Security (0.831), Financial Tranquility (0.849), Financial Freedom (0.933), and Satisfaction with Financial Management (0.925).

Based on the evaluation of these four dimensions, the methodology proposed by Vieira et al. (2023) and adopted in this work, classifies financial well-being as follows: 1.00 to 1.99 very low; 2.00 to 2.99 low; 3.00 to 3.99 high; and greater than 3.99 very high.

Analysis Techniques

For the data analysis procedures, descriptive statistics, mean comparison tests, ANOVA for differences in means, Games-Howell post hoc test, chi-square test, and regression analysis were employed. Descriptive statistics were used to outline the profile of the respondents and their perceptions of financial well-being. The chi-square test was applied to assess the association between levels of financial well-being and demographic characteristics. ANOVA and post hoc tests were conducted to examine mean differences in perceived financial well-being across social classes. Finally, to identify the determinants and assess the strength of the relationship between sociodemographic variables and financial well-being, two regression models were estimated:

Model 1:

$$\begin{array}{c}\multicolumn{1}{c}{\mathrm{PFW}{B}_i={\mathrm{\beta }}_0+{\mathrm{\beta }}_1\mathrm{Ag}{e}_i+{\mathrm{\beta }}_2\mathrm{Se}{x}_i+{\mathrm{\beta }}_3\mathrm{Rac}{e}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_4\mathrm{Marital}\mathrm{statu}{s}_i+{\mathrm{\beta }}_5\mathrm{Occupatio}{n}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_6\mathrm{Education}\mathrm{leve}{l}_i+{\mathrm{\beta }}_7\mathrm{Dependent}{s}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_8\mathrm{Housin}{g}_i+{\mathrm{\epsilon }}_i}\end{array}$$

Model 2:

$$\begin{array}{c}\multicolumn{1}{c}{\mathrm{PFW}{B}_i={\mathrm{\beta }}_0+{\mathrm{\beta }}_1\mathrm{Ag}{e}_i+{\mathrm{\beta }}_2\mathrm{Se}{x}_i+{\mathrm{\beta }}_3\mathrm{Rac}{e}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_4\mathrm{Marital}\mathrm{statu}{s}_i+{\mathrm{\beta }}_5\mathrm{Occupatio}{n}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_6\mathrm{Education}\mathrm{leve}{l}_i+{\mathrm{\beta }}_7\mathrm{Dependent}{s}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_8\mathrm{Housin}{g}_i+{\mathrm{\beta }}_9\mathrm{Social}\mathrm{Class}{A}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_{10}\mathrm{Social}\mathrm{Class}{B}_i+{\mathrm{\beta }}_{11}\mathrm{Social}\mathrm{Class}{C}_i}\\ \multicolumn{1}{c}{+{\mathrm{\beta }}_{12}\mathrm{Social}\mathrm{Class}{D}_i+{\mathrm{\epsilon }}_i}\end{array}$$

where:

PFWB_i is the perceived financial well-being of individual i;

${\mathrm{\beta }}_0$ is the intercept;

${\mathrm{\beta }}_{1-12}$ are the covariates;

${\mathrm{\epsilon }}_i$ is the error term for individual i.

As observed in both models, the dependent variable is perceived financial well-being. As independent variables, age, sex, race, marital status, occupation, education, financial dependents, and housing are used in Model 1. In Model 2, social class dummies are incorporated. Table 3 details the independent variables.

Table 3.

Description of the Independent Variables in the Regression Model.

Variables	Description
Age	Age of the individual in years (continuous variable).
Dummy sex	1 = Male; 0 = Female.
Dummy race/ethnicity	1 = White; 0 = Black, Brown, Asian, Indigenous, Other.
Dummy marital status	1 = Married or in a stable relationship; 0 = Single, Widowed, Separated/Divorced, Other.
Dummy occupation	1 = Public sector employee, Salaried employee; 0 = Self-employed professional, Freelancer, Business owner, Unemployed, Other.
Dummy education level	1 = Higher Education (including undergraduate, postgraduate, MBA, master’s, or doctoral degrees); 0 = Incomplete or Complete Elementary Education, High School, Technical Course.
Dummy dependents	1 = Has dependents (e.g., children, elderly parents); 0 = Does not have dependentes.
Dummy housing	1 = Owns the property; 0 = Rented, Borrowed, Financed, Other.
Dummy social class A	1 = Belongs to Social Class A; 0 = Belongs to any other social class.
Dummy social class B	1 = Belongs to Social Class B; 0 = Belongs to any other social class.
Dummy social class C	1 = Belongs to Social Class C; 0 = Belongs to any other social class.
Dummy social class D	1 = Belongs to Social Class D; 0 = Belongs to any other social class.

Source. Authors’ own compilation (2024).

The individuals’ social classes were defined and adapted based on the Minimum Social Indicators (ISM), a segmentation by income proposed by Instituto Brasileiro de Geografia e Estatística (2010). The values included in each class can be observed in Table 4.

Table 4.

Social Class, Minimum Wage, and Corresponding Value.

Social class	Minimum wage	Value R$ (US$) a
A	Above 20	Over R$22,000.01(US$3,867.68)
B	10–20	Between R$11,000.01 (US$1,933.37) and R$22,000.00 (US$3,867.68)
C	4–10	Between R$4,400.01(US$773.35) and R$11,000.00 (US$1,933.36)
D	2–4	Between R$1,100.00(US$193.34) and R$ 4,400.00 (US$773.35)
E	Up to 2	Below R$1,100.00 (US$773.34)

Source. Brazilian Institute of Geography and Statistics (2010).

a

Note.Currency conversion was performed using an exchange rate of R$5.69 (Brazilian reais) per US$1.00 (United States dollar).

Due to the heteroscedasticity of the residuals, the HCCM (heteroskedasticity consistent covariance matrix) robust estimation proposed by White (1980) was used to calculate the regression model.

Presentation of Results

This section presents the analysis of responses from the 3,998 survey participants. It begins with descriptive statistics to illustrate participants’ perceptions across the four dimensions and their perceived financial well-being. Next, following the methodology proposed by Vieira et al. (2023), perceptions are classified into levels (very low, low, high, and very high), and associations between these levels and various socioeconomic and demographic variables are examined. Subsequently, the results of the analysis of variance for perceived financial well-being across social classes are presented. Finally, the findings of the multiple linear regression model are reported.

The initial step was to explore respondents’ perceptions of each item on the financial well-being scale. Table 5 presents the mean scores and the percentage distribution of responses for each option on the Likert-type scale.

Table 5.

Means and Valid Percentages of the Variables and Dimensions of the Perceived Financial Well-Being Scale.

Dimension	Variables	Mean	Percentage
			Never	Rarely	Sometimes	Often	Always
Financial security	I feel like I’m securing my financial future.	2.80	22.2	18.2	30.2	15.6	13.8
	I feel able to save enough money to last until the end of my life.	2.53	31.0	21.9	22.1	13.5	11.4
	I feel that I will be financially secure until the end of my life.	2.69	27.6	19.2	24.1	14.8	14.4
	I feel able to save money to make my dreams come true.	2.96	18.2	19.1	28.2	17.5	17.0
Financial tranquility	I have the money I need.	2.97	19.9	15.7	27.0	20.6	15.8
	I feel like I will have the things I want in life because of my financial situation.	2.83	18.9	19.8	32.8	16.5	12.0
	I feel that my financial life is under control.	3.51	9.1	13.3	24.1	24.1	29.3
	I deal with financial unforeseen circumstances with peace of mind.	2.94	19.0	18.1	29.0	18.0	16.0
	My financial situation makes me calm.	2.87	21.1	18.0	30.7	17.2	13.0
Financial freedom	My resources are sufficient for my lifestyle.	3.14	16.5	15.8	24.7	23.6	19.3
	I am able to cover expenses for a vacation trip.	2.82	25.0	17.1	24.2	17.7	16.0
	I have enough money to invest in my leisure.	3.07	16.0	16.6	28.7	21.5	17.1
	My financial situation allows me to have a comfortable life.	3.39	10.2	12.9	26.4	28.4	22.0
	I feel financially secure.	2.84	22.1	17.6	28.4	17.8	14.0
	My financial situation allows me to have the things I like.	3.23	9.9	14.8	34.2	25.0	16.0
	My finances allow me to enjoy life.	3.15	10.4	18.1	33.3	22.6	15.7
	My money is enough to satisfy my everyday needs.	3.70	6.7	10.3	20.9	30.6	31.6
Satisfaction with financial management	I feel satisfied with the way I manage my everyday finances.	3.35	10.9	13.0	28.8	24.9	22.5
	I feel satisfied with the way I spend my money.	2.98	18.5	16.0	31.5	17.1	17.0
	I feel satisfied with the way I use my credit options.	3.29	13.6	13.8	26.3	23.3	23.1
	I feel satisfied with the way I manage my money.	3.35	12.1	12.0	28.3	24.0	23.6
	I feel satisfied with my financial decisions.	3.32	10.7	13.0	30.5	25.1	20.6
	I feel satisfied with the control of my expenses.	3.31	12.4	13.5	28.3	22.9	22.9

Source. Survey data (2024).

Table 5 shows that, within the financial security dimension, three questions had the “Never” alternative as the most prevalent, pointing to the respondents’ inability to deal with unexpected adversities and build a reserve for their retirement. The results are consistent with what was observed by the World Bank, indicating that most Brazilians would not be able to get money in the short term to deal with unforeseen events (Demirgüç-Kunt et al., 2022).

In the financial peace of mind dimension, it is observed that in four of the five questions, the respondents mostly checked the “Sometimes” alternative, with the exception of the question about the feeling of being in control of their financial life, where they mainly indicated the “Always” alternative. The results point to a balance in perceptions, with a positive inclination regarding the feeling of being in control of their financial life.

Regarding financial freedom, the “Sometimes” alternative predominated again, being the most voted in five of the eight questions. The results indicate that the respondents feel that their money is not always enough for their daily needs and that, even when they manage to have some comfort, it is not enough to provide a vacation trip.

The individuals’ financial satisfaction is also in the middle ground, as the “Sometimes” alternative was the most checked in all the questions in this dimension. Nevertheless, the means of the questions were higher in this dimension than in the others, indicating that the respondents feel relatively satisfied with how they manage their resources. Based on the calculation proposed by Vieira et al. (2023), the four dimensions and the perceived financial well-being can be observed in Figure 1. And Table 6 provides more detailed information on the means and percentages of financial well-being and its dimensions.

Figure 1.

Frequency distribution of dimensions and the perceived financial well-being scale.

Table 6.

Means, Standard Deviations, and Classification of the Perceived Financial Well-Being Scale.

Dimension	Mean	Deviation standard	Percentage
			Very low	Low	High	Very high
Financial security	2.69	1.14	30.5	30.1	23.6	15.7
Financial tranquility	3.01	1.03	18.8	30.3	30.6	20.4
Financial freedom	3.16	1.05	16.3	28.9	32.2	22.6
Satisfaction with financial management	3.27	1.10	14.2	23.0	32.3	30.5
Perceived financial well-being	3.04	0.95	15.7	33.2	33.6	17.5

Source. Survey data (2024).

It can be observed in Figure 1 that the distribution patterns are not the same across all dimensions. The tails of the distribution of the security and freedom dimensions are denser to the left, indicating that these are the dimensions with the worst perceptions. On the other hand, the distribution of satisfaction is more flattened, indicating a more diverse perception among the population regarding their ability to properly manage their resources. However, for the perception of financial well-being, a relatively symmetric distribution is observed.

Also, according to Table 6, it can be concluded that, except for the Financial Security dimension, all other dimensions—as well as the consolidated perceived financial well-being—are close to the average score of three, which is considered a high level according to the classification proposed by Vieira et al. (2023).

Next, an effort was made to evaluate the role of socioeconomic and demographic variables in the perception of financial well-being. For this, chi-square tests were initially used to assess the association between the variables and the classification of the level of perceived financial well-being. Subsequently, using the quantitative measure of perceived financial well-being, a regression model was applied. Table 7 presents the initial assessment of the association of perceived financial well-being with the different sociodemographic characteristics of the interviewees.

Table 7.

Contingency Table: Perceived Financial Well-Being Versus Socio-Economic and Demographic Variables.

Perceived financial well-being		Very low	Low	High	Very high	Chi- square
Variables	Categories	% (row)	% (row)	% (row)	% (row)
Sex	Male	14.7	32.8	33.5	19.0	4.564
	Female	16.3	33.4	33.6	16.6
Social class	A	2.7	14.0	30.0	53.3	668.54*
	B	5.5	16.0	42.8	35.7
	C	9.9	29.5	40.0	20.6
	D	17.5	39.1	32.1	11.4
	E	30.7	43.9	20.4	5.0
Age	18–32 years	16.2	42.8	32.5	8.5	165.54*
	33–44 years	15.2	32.8	36.7	15.2
	45–61 years	16.1	31.1	32.6	20.1
	Over 62 years	14.0	24.8	33.5	27.7
Marital status	Single	19.0	40.3	30	10.8	154.34*
	Married or in a stable relationship	12.0	29.5	37.5	21.0
	Separated/divorced	19.6	35.5	27.9	17.1
	Widowed	18.3	20.9	32.7	28.1
Race/ethnicity	White	13.4	30.5	36.2	19.9	110.26*
	Black	23.7	37.5	27.6	11.3
	Brown/mixed-race/Asian	19	42	26.7	12.3
	Other	25.4	20.3	39	15.3
Education level	Incomplete elementary education	18.4	35.4	28.3	17.9	203.02*
	Complete elementary education	23.6	37.1	25.8	13.5
	Technical course	21.3	31.6	35.2	11.9
	High school	18.9	38	30	13.1
	Higher education	13.7	32.6	37.4	16.4
	Specialization or MBA	7.6	28.7	36.7	27.1
	Master’s or doctorate	7.7	19.6	44	28.7
Housing type	Own	13.0	30.0	35.1	21.9	162.63*
	Rented	21.4	39.0	29.7	9.9
	Borrowed	23.2	46.4	22.4	8.0
	Financed	13.4	31.1	39.2	16.3
	Other	20.0	33.9	38.3	7.8
Occupation	Public sector employee	8.7	26.0	38.4	26.9	226.04*
	Salaried employee	18.8	36.3	32.6	12.3
	Self-employed professional	13.1	33.6	41.0	12.3
	Freelancer	20.4	39.4	28.6	11.6
	Business owner	8.4	24.3	38.9	28.5
	Unemployed	22.4	33.6	28.0	16.0
	Other	15.7	37.8	31.9	14.6

Source. Survey data (2024).

*

p < .01 (statistically significant).

Table 7 shows that there is an association with financial well-being for all variables, except for gender. The results for social class demonstrate that the lower social classes predominantly have lower levels of perceived financial well-being. In contrast, the higher social classes observe the best levels of financial well-being. These results are in line with what has been observed in other countries for income, both in developed countries such as the United States (Choi et al., 2020) and in developing countries such as India (Chatterjee et al., 2019; Prakash et al., 2022).

Regarding the age of the respondents, it is possible to observe that a smaller percentage of young people have high levels of financial well-being compared to older individuals. These findings are supported by similar studies (Michael Collins & Urban, 2020), but contradict other findings that indicate there is no statistically significant association between age and financial well-being (Chatterjee et al., 2019) or even indicating a negative correlation in developing countries, such as Mexico (García-Mata & Zerón-Félix, 2022).

Regarding marital status, it is observed that widowed or married individuals predominate in the high and very high range of perceived financial well-being. It is possible to identify a global trend of better levels of financial well-being in individuals who are married or living with their partner, both in developed countries (CFPB, 2017) and in emerging economies (García-Mata & Zerón-Félix, 2022).

Individuals of white ethnicity had higher percentages of high perceived financial well-being. The results find broad support in the literature (Clark et al., 2021; Dickason-Koekemoer & Ferreira, 2019; Lee et al., 2020; Mogaji et al., 2021), in addition to observing that blacks have a lower probability of presenting high financial well-being indices compared to white individuals (Hudson et al., 2022).

Regarding education, it is possible to identify that individuals who have a college degree, specialization, master’s or doctorate have higher classifications of perceived financial well-being. The results obtained are in line with other studies, which point to this result mainly due to greater financial effectiveness (Chatterjee et al., 2019; Fan & Babiarz, 2019; Ghina & Sukarno, 2021).

Regarding the type of housing, individuals who own their own home or have a mortgage showed better levels of perceived financial well-being compared to others. It is observed that not having one’s own home increases the risk of indebtedness (Wong & Lynn, 2020), which in turn directly affects financial stress and financial well-being (CFPB, 2017; Fan & Henager, 2022).

Finally, business owners and civil servants showed the highest levels of perceived financial well-being. Notably, a stable job is associated with better financial well-being indices (Chatterjee et al., 2019).

Next, considering the lack of evidence in the literature for social class, it was decided to also use the analysis of variance to identify potential differences in the means of perceived financial well-being between social classes (Table 8).

Table 8.

ANOVA Test for Mean Differences Among Social Classes in Perceived Financial Well-being.

Constructs	Means					F-test value
	A class	B class	C class	D class	E class
Financial security	3.719	3.365	2.853	2.483	2.145	152.982*
Financial tranquility	3.890	3.672	3.219	2.797	2.444	192.566*
Financial freedom	4.156	3.842	3.457	2.936	2.415	286.953*
Satisfaction with financial management	3.806	3.574	3.381	3.227	2.909	45.140*
Perceived financial well-being	3.893	3.613	3.228	2.862	2.478	200.141*

Source. Survey data (2024).

Note. Heteroscedastic ANOVA test.

*

p < .01 (statistically significant). In all dimensions and in the perceived financial well-being, all mean differences are statistically significant at the 1% level, according to the Games-Howell post hoc test.

Table 8 shows that as social class increases, perceived financial well-being and all its dimensions also grow. In all dimensions, the highest means are in social class A, while the worst are in class E. When analyzing the social classes, it is observed that among the higher classes (A, B and C) the highest means are in the financial freedom dimension, while in the lower classes (D and E) the highest means are in satisfaction with financial management. Therefore, there is a wide discrepancy between the classes. The poorest class has the majority of means around a value of two, that is, they “rarely” feel financially secure, peaceful or free, and only “sometimes” feel satisfied with their financial management. On the other hand, the wealthiest have much higher means, indicating that for all dimensions they perceive that they “often” feel financially secure, peaceful, satisfied and free, that is, they perceive a high level of financial well-being. These results are in line with those obtained by Kamble et al. (2024), who conclude that poor Indians are more likely to have a low level of financial well-being than non-poor.

Finally, multiple linear regression was performed, as presented in Table 9, in order to identify the significance and intensity of the correlation of the observed independent variables with the individuals’ perceived financial well-being.

Table 9.

Values and Significance of Coefficients From Estimated Regression Models for Perceived Financial Well-Being.

Independent variables	Model 1				Model 2
	Coefficients	Chi-square Wald		VIF	Coefficients	Chi-square Wald		VIF
		Value	Sig			Value	Sig
Age	0.136	65.168	0.000	1.153	0.135	69.286	0.000	1.159
Dummy sex	0.030	3.713	0.054	1.001	0.020	1.791	0.181	1.002
Dummy race	0.083	28.130	0.000	1.044	0.036	5.880	0.015	1.071
Dummy marital status	0.110	40.923	0.000	1.157	0.041	6.424	0.011	1.205
Dummy occupation	0.049	9.053	0.003	1.084	0.024	2.419	0.120	1.092
Dummy education level	0.176	115.049	0.000	1.125	0.015	0.791	0.374	1.386
Dummy dependents	−0.061	13.126	0.000	1.140	−0.080	25.641	0.000	1.150
Dummy housing	0.128	63.665	0.000	1.125	0.106	48.331	0.000	1.131
Dummy class A					0.257	266.247	0.000	1.338
Dummy class B					0.358	362.308	0.000	1.738
Dummy class C					0.356	283.433	0.000	2.135
Dummy class D					0.158	68.409	0.000	1.784

Source. Survey data (2024).

In Model 1, it is observed that all variables are significant at the 1% level, except for gender. The coefficients indicate that white individuals, married individuals, public employees or salaried employees, the more educated (college degree or higher), those who own their own home, and those who do not have dependents perceive higher levels of financial well-being. These results are consistent with most of the evidence presented in Table 1.

In the second estimation (Model 2), it is observed that when adding the social class dummies to the model, the occupation and education level dummies became non-significant. On the other hand, the most representative positive coefficients refer to the social classes, showing that the higher social classes have a higher level of perceived financial well-being.

Another notable coefficient was age, showing, like Michael Collins and Urban (2020), that older individuals have a higher level of perceived financial well-being. The results again indicate that individuals of white race and without dependents have a higher level of financial well-being, confirming the findings of the international literature (Clark et al., 2021; Keese, 2012; Lee et al., 2020; Mogaji et al., 2021).

In turn, gender did not show statistical significance in either the Pearson chi-square test or the two linear regression models. Michael Collins and Urban (2020) also did not find statistically significant differences when evaluating gender and its correlation with financial well-being. Recently, Kumar et al. (2023), when evaluating a set of sociodemographic variables, also identified that gender, education, marital status and education level do not influence the financial well-being of Indians.

Discussion

The findings indicate that the average perceived financial well-being among Brazilians is three on a scale from 1 to 5, suggesting that, on average, individuals perceive themselves as experiencing financial well-being only “sometimes.” The distribution of responses around the mean was relatively symmetrical, highlighting significant variability within the population. While 48.9% of respondents reported low or very low levels of perceived financial well-being, 51.1% reported high or very high levels, underscoring the heterogeneity of experiences across different segments of the population.

Among the four dimensions assessed, the lowest mean score was observed for financial security. With an average of 2.69, and 60.1% of respondents reporting low or very low levels of perceived financial security, this result reflects a widespread sense of vulnerability. This finding may be attributed to the limited capacity of many Brazilians to save or engage in long-term financial planning. Supporting this interpretation, Vieira et al. (2023b) found that three out of four Brazilians have never calculated how much they need to save for retirement. This is particularly relevant given that the ability to plan for the future and protect oneself against financial shocks is a critical factor in achieving financial well-being (Estrada-Mejia et al., 2023).

In line with previous studies (e.g., García-Mata & Zerón-Félix, 2022; Kamble et al., 2024), the data show that younger individuals tend to report lower levels of financial well-being. One possible explanation is that more recent cohorts are more likely to experience heightened financial insecurity (Wijaya et al., 2024), possibly due to unstable labor market conditions, rising living costs, and growing debt levels.

The results also suggest that education plays a significant role in financial well-being, as higher levels of schooling were positively associated with greater perceived financial well-being. This may reflect the broader impact of formal education on individuals’ ability to understand financial concepts, make informed decisions, and navigate complex financial systems. Notably, in recent years, Brazil has made strides in integrating financial education into various educational levels. Such efforts are supported by the literature, which demonstrates that formal financial education not only directly improves financial literacy and promotes the use of financial technologies, but also indirectly contributes to positive financial behaviors and higher financial well-being (Zhang & Fan, 2024). Moreover, individuals with financial education are better equipped to understand tax systems, compare investment alternatives, and interpret financial regulations (Mahendru et al., 2022).

An important and innovative aspect of this study was the inclusion of social class as a determinant of financial well-being. The results confirmed the importance of this variable, as individuals from lower social classes consistently reported significantly lower scores across all dimensions. This finding supports the view that social class shapes financial behaviors, concerns, and perceptions, reinforcing the idea that public policies should be sensitive to class-based disparities. Given that a large share of the Brazilian population belongs to the D and E social classes, efforts to improve financial well-being must prioritize these groups.

Lastly, the analysis identified specific demographic profiles that are particularly vulnerable: young adults, Black and Brown individuals, those from lower socioeconomic classes, people with only primary education, and self-employed workers. These groups consistently reported lower levels of perceived financial well-being. This evidence highlights the urgent need for targeted social and economic policies aimed at reducing inequality and promoting inclusive financial well-being.

Final Considerations

Analyzes of individuals’ financial well-being have become an increasingly present and relevant topic, especially after financial shocks caused by the pandemic, financial crises and high inflation around the world. The topic becomes even more relevant when analyzed from the perspective of developing countries, as is the case of Brazil, where almost 80% of families are in debt (Confederação Nacional do Comércio, de bens, serviços e turismo-CNC, 2024).

The study explored the perceived financial well-being among Brazilians of different profiles, revealing critical nuances and significant differences that shape financial health in Brazil. Through a quantitative approach, it was evident how personal characteristics influence individuals’ financial well-being.

Therefore, this work reaffirms the complexity of financial well-being as a multidimensional construct that goes beyond the mere accumulation of financial resources, also encompassing aspects of financial security, peace of mind, freedom and satisfaction. By highlighting the determinants of perceived financial well-being and the existing disparities, this study provides a valuable basis for the development of more inclusive and effective public policies and educational interventions, aiming to promote financial health for all Brazilians, but focused especially on the lower socioeconomic strata, the population segment with the lowest levels of perceived financial well-being.

Promoting actions that increase the level of financial well-being of the population is essential not only to reduce financial problems such as the high rate of over-indebted families and lack of financial preparation for retirement, but also brings positive consequences for various health-related aspects such as reduced anxiety (Strömbäck et al., 2020), depression (Negash et al., 2021) and suicide (Adinkrah, 2020), as well as increased self-esteem (Hashmi et al., 2021). It also has positive impacts on quality of life, happiness and relationship quality (Brüggen et al., 2017). However, better results can be achieved if government agencies, financial and educational organizations adopt integrated and differentiated actions, considering socioeconomic and demographic issues (Singh & Malik, 2022).

Furthermore, given the ample evidence that financial literacy contributes effectively to retirement planning, reduction of over-indebtedness, improvement of family financial management, and is considered one of the main antecedents of financial well-being (Singh & Malik, 2022; Zaimovic et al., 2023), the expansion of financial literacy actions is a promising path. The inclusion of financial education as a cross-cutting theme in the school curriculum was an important initial step. Expanding digital financial literacy (DFL) strategies is also essential, as evidence indicates that DFL can increase financial well-being for both the poorest and the financially better-off groups (Kamble et al., 2024). However, for the country to effectively achieve better levels of financial education and, consequently, greater financial well-being, a broad joint effort by the government, organizations and civil society will be necessary.

This study, despite the great sample representativeness, is not exempt from limitations. The main one is based on the fact that it is a survey research, where individuals may not provide accurate responses or opt for more socially acceptable alternatives. In addition, the use of a cross-sectional approach limits the ability to infer causality between the studied variables.

Future research could address these limitations by using longitudinal designs to explore changes in financial well-being over time. It would also be relevant to investigate the impact of specific financial education interventions on the financial well-being of individuals, especially in the most vulnerable groups. Studies that delve deeper into the effects of social class, including the adoption of new proxies, are also promising.