Abstract
Purpose
Needs change as people get older. Procuring resources to satisfy them can generate anguish and insecurities in consumers due to their financial situation. This study aims to analyze the relationship between age and financial stress among Mexican adults and estimate the age of their maximum financial stress.
Design/methodology/approach
This study is based on constructing a financial stress indicator using the confirmatory factor analysis and linear regression models with a quadratic term, employing data from the National Survey on Financial Inclusion 2021.
Findings
Results show that the relationship between age and financial stress follows a quadratic pattern, with a maximum level at age 56, which varies according to sex, marital status, number of dependents, education and regions. These findings interest financial product designers and policy developers who aim to improve consumers' well-being.
Research limitations/implications
Longitudinal studies and indicators, such as financial fragility, are needed to facilitate refining models over time.
Originality/value
There is no evidence of studies that have addressed the age of maximum financial stress in Latin America. Doing so is relevant because identifying the stages in life when adults are most vulnerable to financial stress helps assess its causes more precisely, thus mitigating its adverse effects.
Keywords
Citation
García Mata, O. (2023), "At what age do Mexicans suffer the most financial stress?", Journal of Economics, Finance and Administrative Science, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEFAS-04-2023-0087
Publisher
:Emerald Publishing Limited
Copyright © 2023, Osvaldo García Mata
License
Published in Journal of Economics, Finance and Administrative Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Financial stress can be defined as the feeling of anguish and insecurity that people experience because of their financial situation. According to Prawitz et al. (2006), it refers to the set of negative feelings at one end of a particular continuous emotional state, which flows to another extreme, this one positive, called financial well-being. Financial well-being or its lack thereof, explains a part of general well-being related to life satisfaction, self-esteem and a sense of belonging (Netemeyer et al., 2018). As time goes by, individuals face fluctuating decisions and situations that affect their level of financial stress, therefore, impacting their health, perception of self-accomplishment and the way they relate to others (Arber et al., 2014; Díaz-Fernández et al., 2019; Warmath, 2021).
Financial stress changes with age and the individual's context (Collins and Urban, 2020). For example, when people get older, they accumulate more wealth, making it easier to achieve their financial goals (Binswanger and Carman, 2012). Nevertheless, their financial prowess and ability to adapt, especially to technological changes, get diminished; consequently, their levels of well-being are affected (DeLiema et al., 2020). Furthermore, some decisive events in people's lives, for example, marriage, parenthood and retirement, cause alterations that significantly influence their financial well-being (Salignac et al., 2020; Arrondo et al., 2021). According to O’Connor et al. (2019), financial vulnerability can affect equally the poor and the wealthy; factors such as unemployment, economic activity and poverty can affect consumers' financial situation, thus shaping their financial stress.
The problem addressed in this study regards the lack of consensus about the stage in life when people are most vulnerable to financial stress. Worldwide, some authors have found that its counterpart, financial well-being, is more persistent among older adults (Collins and Urban, 2020; de Bruijn and Antonides, 2020; Fu, 2020). Others point out that the relationship between age and financial well-being follows an inverted U-shaped pattern, with the young and the oldest being the most advantaged (Riitsalu and Murakas, 2019; Xiao and Porto, 2017). A third group warns that these two variables have no apparent relationships (Strömbäck et al., 2020; Rahman et al., 2021). If so, most agree that the definition of financial well-being can change radically with age (Riitsalu et al., 2023).
Therefore, this study aims to analyze the relationship between age and financial stress among Mexican adults and estimate the age of their maximum financial stress. For this purpose, it follows a quantitative, transactional, descriptive and correlational method, supported by constructing a financial stress indicator and simple linear regression models with a quadratic term based on data from the National Survey on Financial Inclusion, NSFI 2021 (INEGI, 2022).
Identifying the stages in life at which adults are most vulnerable to financial stress helps make a more accurate analysis of its causes, thus facilitating the development of initiatives focused on mitigating its adverse effects. These findings interest professionals in charge of designing and marketing financial products in private institutions and developers of public policies aiming to improve consumers' general well-being.
2. Literature review
2.1 Macroeconomic regional approach to financial stress
Several researchers have investigated financial stress from a macroeconomic point of view. In this sense, Valerio Roncagliolo and Villamonte Blas (2022, p. 69) refer to it as “the periods in which economic agents are exposed to extreme uncertainties leading to negative expectations of financial markets.” Therefore, predicting the occurrence of these episodes and analyzing their determinants has been a central concern in alleviating their consequences and economic impacts at international, regional and national levels (Illing and Liu, 2006; Cardarelli et al., 2011; Park and Mercado, 2014).
When a macroeconomic system gets stressed, families suffer, too (Friedline et al., 2021; Cardona-Montoya et al., 2022). Households fear or experience job instability, over-indebtedness and economic hardship, among other problems (Cardarelli et al., 2011; Choi et al., 2020). For instance, in Colombia, an inverse relationship was observed between workers' financial stress and preparedness; this last measured as the self-perception of financial endowment, the holding of investments and savings, the use of budget and the sufficiency of household's income to overcome the COVID-19 crisis (Cardona-Montoya et al., 2022). Also, in the United States of America, Choi et al. (2020) proved that job insecurity directly influences workers' financial stress.
In Mexico, several studies have associated financial fragility with low-income monoparental families led by women and those in which income is generated only by men (Ibarra López, 2019; Martínez and Ferraris, 2021). Others have noticed that limited female participation in formal labor markets adds extra pressure on households with low-educated members (Félix-Verduzco and Inzunza-Mejía, 2019; Montoya, 2019).
Culture and institutions can facilitate or restrain economic opportunities. In highly populated countries, contrasting socioeconomic conditions affect financial literacy and inclusion, thus impacting financial stress (Raccanello and Sundaram, 2018). This study analyzes financial stress considering individual characteristics and a regional approach based on the six-region classification employed by INEGI in NSFI 2021 (see Table 1).
The most populated regions are R5 East and South-Central and R3 West and Bajío, with 30.2–21.2% of Mexico's total population, respectively. In 2021, both regions contributed to gross domestic product (GDP) by 19.9% each. In 2020, the population in moderate and extreme poverty fluctuated from 27.7% in R1 Northwest to 62.2% in R6 South. Meanwhile, unemployment remained low in R6 (3.0%) but high in R4 Mexico City (7.3%) and labor informality varied from 42.0% in R1 to 70.7% in R6 by the second quarter of 2021. Since 2005, salaries in the Mexican formal sector have increased economic growth, while unemployment has impacted it negatively; these facts, in turn, have affected families' financial conditions (Reyna, 2021).
Furthermore, financial inclusion is also a contrasting indicator. While in the North more than 75% have access to at least one formal financial product, in the South no more than 62% do. In Mexico, according to Díaz et al. (2023), holding a savings account or a formal credit reduces consumers' financial vulnerability, while having a standing informal credit increases it.
2.2 Age and financial stress
This study analyzes financial stress from a consumer's perspective, following the emotional continuum ranging from subjective financial well-being to its negative opposite, financial stress, as indicated by Prawitz et al. (2006). Moreover, it adheres to the remarks made by Friedline et al. (2021, p. S43) regarding the discomfort and distress often experienced by family providers “when they do not have adequate income, wealth, or debt to afford economic hardship”.
According to Ruggeri et al. (2020), subjective well-being is the combination of factors that make people feel good and function well. It has emotional and practical components that extend far beyond happiness and satisfaction with life. Analogously, subjective financial well-being can be defined as feeling good about one's financial situation and being able to finance a decorous lifestyle now and in the future (Riitsalu et al., 2023). Furthermore, it refers to the perception of satisfaction caused by the possession, utilization or consumption of material and immaterial resources (Xiao and Anderson, 1997). Hence, financial well-being is the opposite of financial stress in this work, assuming they are part of the same conceptual construct.
Empirical research concerning the relationship between age and financial well-being has had contrasting results. In the first group are those scholars who have established that financial well-being increases with age. For example, Fu (2020) found that adults from 11 emerging and developed nations perceive their financial condition favorably at older ages. Another example is provided by Collins and Urban (2020), who observed that financial well-being gets its lowest among people aged 18–24 and peaks after age 75, in the United States of America. They explained this pattern by the accumulation of goods and savings that come with age. Similarly, in the Netherlands, de Bruijn and Antonides (2020) found that levels of financial worry decline as people age.
A second group of researchers argues that financial well-being in early adulthood is high but declines to a minimum at midlife, which rises again as people age. In line with this idea, Riitsalu and Murakas (2019) confirmed that Estonian adults aged 18–29 show the highest level of financial well-being, which subsequently reaches its minimum between 30 and 59, to improve again after 60. Another example is offered by Xiao and Porto (2017), who found that the lowest level of financial satisfaction occurs between 45 and 54, while the highest satisfaction befalls before 25 and after 65, among a sample of more than 26,000 Americans.
Finally, researchers such as Rahman et al. (2021) observed that age is unrelated to financial stress in Malaysia. Similarly, Strömbäck et al. (2020) concluded that age is not significant in explaining financial well-being among a sample of students from Sweden. Although they warned that their sample was very homogeneous regarding age, thus their conclusion should not be extrapolated.
For all the above and assuming that financial stress is the counterpart of subjective financial well-being, this study puts to the test the following hypotheses applicable to Mexican adults:
Age is related to financial stress following a nonlinear pattern.
The maximum financial stress occurs around midlife.
3. Method
3.1 Research design/model
This research is based on the National Survey on Financial Inclusion, NSFI, conducted in Mexico during the second quarter of 2021 (INEGI, 2022). It comprises a database of 13,554 records corresponding to one adult from each household in the sample, representing more than 90 m Mexican adults. Of these, 36 who did not report their age and 204 who did not answer the questions necessary to estimate financial stress were discarded. Analogously, those aged 83 years and over were grouped into a single category because the punctual frequency associated with each age above 83 was shallow and could bias the results. In this way, age is configured as an independent variable fluctuating from 18 to 83, with 83 representing adults between 83 and 97.
This research's methodological design follows the linear regression models with one quadratic term employed by Finke et al. (2016) concerning the age of maximum financial knowledge and Easterlin (2006) regarding the maximization of life-cycle happiness. In both, age and age squared are independent variables.
3.2 Data and variables
The construction of the dependent variable financial stress was based on four NSFI items consistent with those used by the USA Consumer Financial Protection Bureau (2017a) and Netemeyer et al. (2018). To adapt these questions to measure financial stress rather than financial well-being, they were coded so that a higher value represents more financial stress, as indicated in Table 2.
Since the responses follow an ordinal scale, an indicator of financial stress was constructed after performing a confirmatory factor analysis. Previously, several indicators were estimated: the Cronbach’s alpha coefficient to evaluate items' internal consistency, the Kaiser–Meyer–Olkin coefficient, KMO, to validate the suitability of the sample size, the Bartlett sphericity coefficient to test if the data were suitable for factor analysis and the inflation factor of the variance, VIF, to check for multicollinearity. The acceptance criteria used for them are alpha≥0.7 (Hair et al., 2014), KMO>0.6 (Kaiser, 1974), p < 0.05 for the sphericity coefficient (Bartlett, 1937) and VIF<2.5, respectively.
The factor analysis was based on the technique of principal component factors with retention of those that presented eigenvalues greater than 1.0, according to the Kaiser criterion, varimax rotation and an explained variance greater than or equal to 50%. Subsequently, values for the financial stress indicator were estimated using the weights that resulted from the factor analysis. Equation 1 shows how the values for this indicator were calculated for each observation i in the database. In it, FSx refers to the financial stress indicator, wk to the weights derived from the factor analysis and Xk, k = 1 … 4, to the variables employed to measure financial stress:
Later, FSx was transformed to fit on a scale ranging from 0 to 100, where 0 was associated with the absence of stress and 100 with the maximum financial stress. Equation 2 shows how the values for this indicator (FSi) were transformed for each observation i in the database.
Next, for each age, the average financial stress (FSage) was calculated by adding up the values FSk of all people who are age years old and dividing the sum by the number of them (n), as shown in Equation 3:
3.3 Analytical procedures
This average is the dependent variable in a multiple linear equation in which age and age-squared functions as independent variables and sex, marital status, number of dependents and education level functions as control variables (see Table 3).
Finally, several regression models with a quadratic term were constructed to explain financial stress as a function of age and different values of sex, marital status, dependents, education and region, as shown in Equation 4:
R1 is omitted due to its collinearity with other regions, and error represents the residual. Two linear regression models with a quadratic term are constructed: one including only age and age2 and another including them and all control variables.
4. Results
4.1 Factor analysis for financial stress
Several indicators were calculated to determine whether the variables are susceptible to being processed by factor analysis. The adequacy coefficient of the sample KMO = 0.66 indicates that it is mediocre but acceptable. Bartlett's sphericity test registers a p < 0.05, sufficient to confirm that the data are suitable for factor analysis (see Table 4).
Furthermore, there were no multicollinearity problems between the variables because each presents a VIF<2.5; overall, they register VIF = 1.44. However, Cronbach's alpha coefficient registers a value of 0.614, which is insufficient to accept the four variables. Moreover, when estimating the effect of omitting each of these variables in the alpha coefficient, it was noticed that the factor analysis would benefit if the variable X1 is omitted because the remaining three variables register an alpha equal to 0.745, which is acceptable. Therefore, X1 was omitted for the rest of the process and so were the records of those who responded did not know or did not respond to X2, X3 or X4.
After performing factor analysis, the remaining three variables explain 67.5% of the variance, with a single retained factor presenting an eigenvalue greater than 1.0. Likewise, the three variables included in the construction of the retained factor have weights greater than 0.7, sufficient to justify their inclusion in the construct (see Table 5).
4.2 Descriptive statistics
After factor analysis, the average financial stress was estimated for each age. There were 13,314 observations, corresponding to one adult for each household in the sample, representing 88,359,714 Mexicans. The average financial stress score was 54.0, with a standard deviation of 35.3 (see Table 6).
Financial stress is critical between ages 43 and 62, with a lower incidence among those under 33 and over 83. Similarly, women and married people suffer significantly greater financial stress than men and singles (p < 0.001). Moreover, financial stress increases with each additional economic dependent (p < 0.001). In addition, the most contrasting difference is observed between those who at most completed nine years of education, with an average score of 59.9 and those with 13 or more school years, whose average score is 44.9.
4.3 Econometric analysis of financial stress
Two econometric models with a quadratic term were constructed after estimating values for financial stress using factor analysis. Both include age and age-squared as independent variables: Model 1 excludes control variables and Model 2 includes sex, marital status, number of dependents and years of education.
4.3.1 Age and financial stress among Mexican adults
The results in both models confirm that age is a significant variable associated with financial stress, both alone and squared (p < 0.001). Therefore, there is sufficient evidence not to reject H1: age is related to financial stress following a nonlinear pattern. Besides, it is worth noticing that women, singles, the head of larger families and the less educated are more predisposed to financial stress. Furthermore, Model 2 shows the relevance of age in explaining financial stress. Compared to control variables, age and age-squared exhibit beta coefficients equal to 0.852 and −0.775, respectively, while the East and South-Central region and education show the subsequent highest absolute betas with 0.188 and −0.156, respectively (see Table 7).
According to Model 1, the age at which Mexicans suffer the most financial stress is 56. At this age, they reach a maximum financial stress score of 60.8. In contrast, the minimum score is 39.5 at 18. Their level of financial stress exceeds the overall average of 54.0 between ages 38 and 73. From 38 to 56, financial stress increases at an average rate of 0.83 points per annum. Thus, these data are enough to confirm that (H2) the maximum financial stress occurs around midlife (see Figure 1).
These results are consistent with those found by Riitsalu and Murakas (2019) in Estonia and Xiao and Porto (2017) in the United States of America, indicating that younger and older adults experience higher financial well-being than middle-aged adults. In contrast, Easterlin (2006) observed that, in the United States of America, life-cycle happiness reaches its maximum at 51; however, its financial satisfaction domain records its lowest at 36, at some point in between adults' midlife, which is consistent with the results found in this study.
4.3.2 Age and financial stress by sex
Throughout most of their adult life, women suffer a more financial stress than men. While females reach their maximum financial stress level at 52, men experience it at 62; they present scores of 63.1 and 58.9, respectively (see Table 8).
However, at 68, this pattern is reversed and men become more prone to suffer higher financial stress than women until the end of their lives (see Figure 2).
4.3.3 Age and financial stress by marital status
On average, singles show less financial stress than married people. However, being married or living with a partner helps retard financial stress for consumers between 22 and 61. Married people reach their maximum financial stress at 60, while singles at 53 (see Table 9).
At 62, married and single consumers exhibit the same level of financial stress. However, after 62, financial stress decreases rapidly for singles, at a rate of 0.73 points per annum, while for married people, this rate is barely 0.27. Therefore, singles present lower financial stress at older ages than married adults (see Figure 3).
These facts suggest that, during working ages, partners in life help ease financial stress, while in retirement, remaining alone is a better way to reduce financial stress. Another explanation is that couples are more prone to having children; thus, coping with family expenses becomes a priority over retirement savings.
4.3.4 Age and financial stress by economic dependents
Regarding financial stress, the more is not always, the merrier. For an economic provider, a large family means more reasons to get financially worried. The number of dependents among Mexican adults is related to increased financial stress. Consumers with no dependents reach their maximum financial stress level at 59, those with one or two reach their maximum at 57, having three or four dependents is related to a financial stress peak at 56 and those with five or more reach their maximum at 61 (see Table 10).
In this sense, individuals with more dependents have more extended periods of financial stress above average. For example, zero dependents extend financial stress among adults for 36 years, between ages 42 and 77; in contrast, being responsible for five or more descendants causes high financial stress for 50 years, from 34 to 83 (see Figure 4). These results are consistent with those obtained by Hurst et al. (1998) in the United States of America, who explained that families with more children tend to save less and are more likely to have economic difficulties than families without children. Given the previous results, childless couples are expected to show lower financial stress, while single women in charge of five or more children present a higher financial stress.
4.3.5 Age and financial stress by education level
Education is a critical factor related to financial stress. For example, consumers who attended at least one year of college present a maximum financial stress level at age 51, similar to those between 10 and 12 years who record their maximum at 50. In contrast, adults who completed up to the ninth grade got their highest peak at 54. Their maximum financial stress scores are very dissimilar: 65.2 for the least educated, 57.2 for those between 10 and 12 years and 48.2 for those who completed at least 13 school years (see Table 11).
The age-financial stress relationship follows an inverted U-shaped pattern for the three groups. From 18 to the age of maximum financial stress, adults who at most completed the ninth grade showed an increased rate of 0.60 points per annum in their score. This rate is 0.56 for those who registered in 10–12 grades and 0.29 for consumers who went beyond the 12th grade (see Figure 5).
4.3.6 Age and financial stress by region
Financial stress varies from region to region, following a concave pattern. The Northern regions show the lowest financial stress, averaging 46.6 for the Northwest and 45.4 for the Northeast. Practically, they exhibit the same financial stress pattern according to age, which is lower than that of any other region for each age. On the contrary, the East and South-Central regions show the highest financial stress, scoring 62.0. Unlike other regions, the West and Bajío show the highest age of maximum financial stress; however, this is associated with a prolonged stage of financial stress above average, from 36 to 91 years old (see Table 12).
For all regions, an inverted U-shaped pattern is observed. The younger are the least financially stressed and stress peaks at mid-age; nevertheless, one can obstbns (see Figure 6).
5. Discussions
5.1 Theoretical implications
Financial stress changes with age. From a theoretical point of view, this study confirms that age and financial stress have a nonlinear relationship, following a pattern resembling an inverted U. Accordingly, younger adults and older adults register the lowest levels of financial distress and concern. This result is consistent with those found by Riitsalu and Murakas (2019) in Estonia and Xiao and Porto (2017) in the United States of America, who observed that financial well-being reaches its bottom at some point in midlife, between 30 and 59 in the first case and between 45 and 54 in the second. Likewise, in Mexico, according to this research, people suffer the most financial stress between ages 38 and 73, with a maximum level at 56.
In the United States of America, a similar observation addressing the stages in life when financial satisfaction hits the bottom is provided by Easterlin (2006). He estimated a minimum of financial satisfaction at age 31, implying that financial satisfaction increases for most of an adult's life. This fact assumes that, as time goes by, consumers accumulate wealth and experience, which help them cope economically and emotionally with adversities.
This growing trend was also observed in other works regarding age and financial well-being (Collins and Urban, 2020; de Bruijn and Antonides, 2020; Fu, 2020). However, the present study provides evidence that contradicts this cumulative pattern. Instead, in Mexico's case, it suggests that financial stress rises because of life events until the middle of adulthood, which varies from person to person and is influenced by the environmental and inherent conditions related to every individual. Regional differences regarding the institutional context and culture are related to financial stress. Therefore, countries with unequal socioeconomic conditions, such as Latin American nations, are more predisposed to experience contrasting levels of financial stress.
5.2 Managerial/policy implications
Different events accentuate or alleviate financial stress throughout life, for example, getting married, having children or graduating from school. In this sense, marrying or living with a partner helps mitigate financial distress due to factors such as financial socialization, the consolidation of wealth and the solidarity of the spouse in case of contingencies. Among Mexicans, the advantage for couples extends up to age 62 but increases rapidly afterward in favor of singles for whom financial stress decreases. This outcome is congruent with similar observations recorded by the CFPB (2017b) for adults in the United States of America; as retirement approaches and afterward, some couples tend to rely on a single income or pension, adding more pressure to their household's financial situation.
Similarly, a significant difference is observed between women's and men's financial stress. Throughout their productive age, females show higher levels of financial stress than males. However, this difference in men's favor in Mexico ends at age 68 and remains like that. One explanation is that women's participation in the labor market often includes hiring schemes that generate lower incomes, such as seasonal and part-time jobs, in contrast to men, who occupy most of the full-time positions.
Additionally, female participation in the labor market is strained by childbearing, traditionally regarded as a female responsibility. When women assume the role of family caregivers, their participation in the labor market is usually limited, and with this, their access to formal financial markets is reduced; consequently, financial learning in practice becomes more complex, not because of a lack of skills but of time, which is the result of their activities prioritization (Struckell et al., 2022).
Moreover, the most formally educated people tend to have a more stable financial life than the less educated. In this context, education refers to general schooling and not only to financial training but also the former is concerned with preparing intelligent consumers, the second with skillful financial customers. As a result of education, people are better equipped to face economic uncertainty and have better control of their emotions. These findings are consistent with those registered by Kempson et al. (2017), Fu (2020) and Riitsalu and Murakas (2019) concerning education and financial well-being. Also, this result concurs with the remarks pointed out by Cardona-Montoya et al. (2022) regarding how, in Colombia, the most financially educated workers are better prepared to handle economic adversities, thus showing lower probabilities of experiencing financial fragility and financial stress.
Furthermore, it is worth noticing that the regional context is associated with consumer's financial stress. In Mexico, the Northern regions, which present the lowest levels of financial stress, have the highest access rate to financial products and the lowest rates of poverty and labor informality. On the contrary, the Southern regions, which present the first and the third highest rates of financial stress, have the lowest access rate to financial products and the highest levels of poverty and labor informality. Mexico City, the region with the second highest level of financial stress, experienced the highest unemployment rate among all regions.
Therefore, identifying the structural conditions and life events that affect the population's financial stress is critical for enhancing policies and strategies to improve financial well-being. The results obtained in this research imply that financial inclusion and education policies must focus on at least four general issues. First, government programs must mitigate the financial fragility gap between monoparental and biparental families and attend couples in retirement that depend on a single income or pension. Second, the policy must be oriented to improving and expanding labor opportunities for women to access the benefits offered by the formal financial system. Third, promoting financial education as an integral part of the pre-university curricula is necessary for aspiring to accomplish results in the long run, especially in schools located in marginalized areas. Finally, public policy must also address the gap reduction of regional inequalities when mitigating financial stress.
5.3 Limitations and future research agenda
In line with the recommendations made by Mahendru (2021), this study explores the stages in life when people experience the most financial stress and the mechanisms to allay it, ultimately improving consumer satisfaction. However, its main limitations are the need for longitudinal studies that facilitate refining models over time and the absence of indicators such as financial fragility.
Future research must consider analyzing the determinants of financial stress at a consumer's level and including other indicators related to households' financial well-being. Also, investigating the causality effects of financial literacy and financial inclusion over financial stress and financial well-being, with age as a moderating variable, is a topic worth considering. Finally, another subject that can be included in a future research agenda is comparing consumer behavior in critical (i.e. extreme poverty and insecurity) and non-critical (i.e. buoyant economy) economic contexts.
6. Conclusions
The relevance of this study lies in proposing a model to estimate the stages in life when Mexican adults are more likely to suffer financial stress. While there are similar works concerning the age of maximum happiness, satisfaction with life or financial knowledge, especially in developed economies, during this research, no other studies addressing the age of maximum financial stress in Latin America were found. This study aims to inspire more research on financial stress, especially in regions where socioeconomic and working conditions cause additional financial stress among people.
In emerging economies, transitioning from policies promoting financial inclusion to those focused on the population's financial health and well-being remains challenging. Making formal financial services available to a broader population is not enough for families to take advantage of these resources or to alleviate their financial fears and concerns. Therefore, public policy must emphasize alleviating disadvantaged households, particularly female-led monoparental families with three or more children and those led by low-educated middle-aged adults from Southern regions. This research provides evidence contributing to a better understanding of financial stress throughout adult life. Hence, it is of interest to financial product designers and policy developers aiming to improve consumers' well-being.
Figures
Economic characteristics by region
| Region states | National population 2020 (%) | Contribution to GDP 2021 (%) | Poverty 2020 (%) | Unemployment 2021-Q2 (%) | Labor informality 2021-Q2 (%) | Access to financial products 2021-Q2 (%) |
|---|---|---|---|---|---|---|
| R1 Northwest Baja California, Baja California Sur, Chihuahua, Durango, Sinaloa, Sonora | 12.8 | 15.5 | 27.7 | 3.2 | 42.0 | 75.7 |
| R2 Northeast Coahuila, Nuevo León, San Luis Potosí, Tamaulipas | 12.1 | 17.3 | 30.4 | 4.0 | 42.8 | 77.0 |
| R3 West and Bajio Aguascalientes, Colima, Guanajuato, Jalisco, Michoacán, Nayarit, Querétaro, Zacatecas | 21.2 | 19.9 | 36.9 | 3.9 | 53.2 | 69.3 |
| R4 Mexico City Ciudad de México | 7.3 | 15.3 | 32.6 | 7.3 | 47.1 | 74.2 |
| R5 East and South-Central Estado de México, Hidalgo, Morelos, Puebla, Tlaxcala, Veracruz | 30.2 | 19.9 | 53.9 | 4.8 | 64.7 | 62.0 |
| R6 South Campeche, Chiapas, Guerrero, Oaxaca, Quintana Roo, Tabasco, Yucatán | 16.5 | 12.1 | 62.2 | 3.0 | 70.7 | 60.1 |
Source(s): Author's elaboration with data from INEGI (2023a, b) and Coneval (Consejo Nacional de Evaluación de la Política de Desarrollo Social) (2023)
Items to measure financial stress
| Item | Code/answer | |
|---|---|---|
| To what degree or extent do you agree or disagree with the following statements … ? | ||
| X1 | Inflexibility. Managing your income and expenses controls your life | (0) Never |
| (1) Sometimes | ||
| (2) Always | ||
| X2 | Frustration. Given your economic situation, you feel that you will get the things you want | (0) Agree |
| X3 | Insufficiency. You have enough money to cover all your expenses | (1) Not agree, nor disagree |
| X4 | Uneasiness. You feel relieved that your money is enough to get what you need | (2) Disagree |
Source(s): Author's selection from NSFI (INEGI, 2022) based on CFPB (2017a) and Netemeyer et al. (2018)
Variables description and analytical model
| Dependent variable | ||
| Financial stress for each age FSage | Continuous variable equal to the average financial stress indicator values corresponding to all people at a certain age. It ranges from 0.0 (absence of stress) to 100.0 (maximum level of financial stress). FSage ϵ [0, 100]; age ϵ [18, 83] | CFPB (2017a), Netemeyer et al. (2018) |
| Independent variables | ||
| Age | Ordinal variable that fluctuates between 18 and 83. The latter value includes people aged 83–97. age ϵ [18, 83] | Author's proposal |
| Age2 | Ordinal variable resulting from age*age, which ranges between 324 and 6,889. age2 ϵ [324, 6,889] | |
| Control variables | ||
| Sex | Dichotomous variable equal to 1 for women and 0 for men. Sex ϵ [0, 1] | Author's proposal |
| Marital status (MS) | Dichotomous variable equal to 1 for married or living with a partner and 0 for any other case. MS ϵ [0, 1] | |
| Dependents (Dep) | Ordinal variable indicating the number of economic dependents; it fluctuates between 0 and 6 (for people with six or more dependents). Dep ϵ [0, 6] | |
| Education (Educ) | Ordinal variable that refers to the years of education. It ranges from 0 to 20+. Educ ϵ [0, 20] | |
| Region (R1 … R6) | Set of binary variables such that R1+R2+R3+R4+R5+R6 = 1 | |
Source(s): Author's elaboration based on the sources indicated in the table
Internal consistency for the construction of a financial stress indicator
| Variable | VIF | Alpha |
|---|---|---|
| X1 (inflexibility) | 1.75 | 0.745 |
| X2 (frustration) | 1.71 | 0.525 |
| X3 (insufficiency) | 1.29 | 0.402 |
| X4 (uneasiness) | 1.01 | 0.416 |
| Total | 1.44 | 0.614 |
| KMO = 0.660 | ||
| χ2 (6) = 9,999.9 | p = 0.000 | |
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Factor analysis for financial stress
| Factor | Eigenvalue | Difference | Proportion | Accumulated variance |
|---|---|---|---|---|
| 1 | 2.024 | 1.416 | 0.675 | 0.675 |
| 2 | 0.608 | 0.241 | 0.203 | 0.878 |
| 3 | 0.368 | 0.123 | 1.000 |
| Retained factor after varimax rotation | |
|---|---|
| Variable | Factor 1 |
| X2 | 0.749 |
| X3 | 0.862 |
| X4 | 0.849 |
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Descriptive statistics on financial stress among Mexican adults
| Variable | Observations | Financial stress | ANOVA p-value | |||
|---|---|---|---|---|---|---|
| Sample | Population | % | Mean | St. Dev | ||
| Age | 56.7*** | |||||
| 18–22 | 1,311 | 11,328,025 | 12.8 | 40.9 | 33.1 | |
| 23–32 | 2,839 | 19,469,133 | 22.0 | 49.6 | 33.4 | |
| 33–42 | 2,840 | 17,349,766 | 19.6 | 55.4 | 35.2 | |
| 43–52 | 2,336 | 15,699,312 | 17.8 | 61.2 | 35.3 | |
| 53–62 | 1,830 | 11,997,063 | 13.6 | 60.0 | 34.8 | |
| 63–72 | 1,320 | 7,940,352 | 9.0 | 56.7 | 36.2 | |
| 73–82 | 618 | 3,378,093 | 3.8 | 54.4 | 35.7 | |
| 83+ | 220 | 1,197,970 | 1.4 | 52.8 | 38.6 | |
| Sex | 53.1*** | |||||
| Men | 6,112 | 41,709,480 | 47.2 | 51.5 | 35.2 | |
| Women | 7,202 | 46,650,234 | 52.8 | 56.1 | 35.2 | |
| Marital status | 37.9*** | |||||
| Single | 5,511 | 34,837,293 | 39.4 | 51.7 | 35.3 | |
| Married | 7,803 | 53,522,421 | 60.6 | 55.4 | 35.2 | |
| Dependents | 10.8*** | |||||
| 0 | 1,640 | 4,090,407 | 4.6 | 48.4 | 36.5 | |
| 1 | 2,591 | 12,862,553 | 14.6 | 52.7 | 35.9 | |
| 2 | 2,808 | 17,414,318 | 19.7 | 52.9 | 35.5 | |
| 3 | 3,042 | 21,187,207 | 24.0 | 53.6 | 34.7 | |
| 4 | 1,775 | 14,750,683 | 16.7 | 54.3 | 34.7 | |
| 5 | 782 | 8,226,030 | 9.3 | 57.8 | 35.2 | |
| 6+ | 676 | 9,828,516 | 11.1 | 56.9 | 35.0 | |
| Education | 217.6*** | |||||
| 0–9 years | 7,313 | 46,939,386 | 53.1 | 59.9 | 34.9 | |
| 10–12 years | 3,023 | 21,347,099 | 24.2 | 49.5 | 34.2 | |
| 13+ years | 2,978 | 20,073,229 | 22.7 | 44.9 | 34.6 | |
| 13,314 | 88,359,714 | 100.0 | 54.0 | 35.3 | ||
Note(s): ***p-value<0.001
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Econometric analysis for the relationship between age and financial stress
| Variable | Model 1 | Model 2 | ||||
|---|---|---|---|---|---|---|
| Coefficient | Std. Error | Beta | Coefficient | Std. Error | Beta | |
| Age2 | −0.015*** | 0.000 | −0.669 | −0.017*** | 0.000 | −0.775 |
| Age | 1.666*** | 0.001 | 0.792 | 1.792*** | 0.001 | 0.852 |
| Sex | 3.776*** | 0.007 | 0.053 | |||
| Marital status | −1.343*** | 0.008 | −0.019 | |||
| Dependents | 1.401*** | 0.002 | 0.066 | |||
| Education | −1.209*** | 0.001 | −0.156 | |||
| Region (northwest) | ||||||
| R2 Northeast | −1.621*** | 0.014 | −0.015 | |||
| R3 West and Bajío | 3.506*** | 0.013 | 0.040 | |||
| R4 Mexico City | 10.978*** | 0.016 | 0.086 | |||
| R5 East and South-Central | 14.382*** | 0.012 | 0.188 | |||
| R6 South | 5.171*** | 0.014 | 0.053 | |||
| Constant | 14.36 | 0.025 | 457.83 | 0.030 | ||
| Observations | 88,090,849 | 88,090,849 | ||||
| P > F | 0.000 | 0.000 | ||||
| Adjusted R2 | 0.034 | 0.094 | ||||
Note(s): ***p-value<0.001
Source(s): Author’s elaboration with Stata (StataCorp, 2017)
Age and financial stress among Mexican adults, by sex
| Variable | Women | Men | ||
|---|---|---|---|---|
| Coefficient | Std. Error | Coefficient | Std. Error | |
| Age2 | −0.018*** | 0.000 | −0.011*** | 0.000 |
| Age | 1.909*** | 0.002 | 1.381*** | 0.002 |
| Constant | 13.089 | 0.034 | 15.954 | 0.036 |
| Observations | 46,551,121 | 41,539,728 | ||
| P > F | 0.000 | 0.000 | ||
| Adjusted R2 | 0.034 | 0.038 | ||
| Average financial stress (FS) | 56.1 | 51.5 | ||
| Age of maximum FS | 52 | 62 | ||
| Period of FS above average | [33, 71] | [41, 83] | ||
Note(s): ***p-value<0.001
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Age and financial stress among Mexican adults, by marital status
| Variable | Married | Single | ||
|---|---|---|---|---|
| Coefficient | Std. Error | Coefficient | Std. Error | |
| Age2 | −0.011*** | 0.000 | −0.019*** | 0.000 |
| Age | 1.379*** | 0.002 | 2.022*** | 0.002 |
| Constant | 19.225 | 0.042 | 8.820 | 0.034 |
| Observations | 53,383,778 | 34,707,071 | ||
| P > F | 0.000 | 0.000 | ||
| Adjusted R2 | 0.022 | 0.050 | ||
| Average financial stress (FS) | 55.4 | 51.7 | ||
| Age of maximum FS | 60 | 53 | ||
| Period of FS above average | [39, 81] | [30, 76] | ||
Note(s): ***p-value<0.001
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Age and financial stress among Mexican adults, by number of dependents
| Variable | 0 | 1–2 | 3–4 | 5+ | ||||
|---|---|---|---|---|---|---|---|---|
| Coeff. | St. Err. | Coeff. | St. Err. | Coeff. | St. Err. | Coeff. | St. Err | |
| Age2 | −0.011*** | 0.000 | −0.014*** | 0.000 | −0.016*** | 0.000 | −0.012*** | 0.000 |
| Age | 1.312*** | 0.006 | 1.591*** | 0.002 | 1.823*** | 0.002 | 1.532*** | 0.003 |
| Constant | 12.961 | 0.160 | 13.483 | 0.045 | 10.906 | 0.039 | 19.720 | 0.053 |
| Observations | 4,070,270 | 30,170,599 | 35,839,228 | 18,010,752 | ||||
| P > F | 0.000 | 0.000 | 0.000 | 0.000 | ||||
| Adjusted R2 | 0.013 | 0.030 | 0.043 | 0.050 | ||||
| Average financial stress (FS) | 48.4 | 52.8 | 53.9 | 57.3 | ||||
| Age of maximum FS | 59 | 57 | 56 | 61 | ||||
| Period of FS above average | [42, 77] | [37, 77] | [34, 78] | [34, 83] | ||||
Note(s): ***p-value<0.001
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Age and financial stress among Mexican adults, by years of education
| Variable | 0–9 years | 10–12 years | 13+ years | |||
|---|---|---|---|---|---|---|
| Coeff. | Std. Err. | Coeff. | Std. Err. | Coeff. | Std. Err. | |
| Age2 | −0.017*** | 0.000 | −0.017*** | 0.000 | −0.009*** | 0.000 |
| Age | 1.817*** | 0.002 | 1.745*** | 0.003 | 0.912*** | 0.003 |
| Constant | 16.216 | 0.039 | 13.551 | 0.050 | 25.029 | 0.056 |
| Observations | 46,834,162 | 21,305,199 | 19,951,488 | |||
| P > F | 0.000 | 0.000 | 0.000 | |||
| Adjusted R2 | 0.027 | 0.032 | 0.007 | |||
| Average financial stress (FS) | 59.9 | 49.5 | 44.9 | |||
| Age of maximum FS | 54 | 50 | 51 | |||
| Period of FS above average | [37, 71] | [30, 70] | [32, 70] | |||
Note(s): ***p-value<0.001
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Age and financial stress among Mexican adults, by region
| Variable | Northwest | Northeast | West and Bajío | |||
|---|---|---|---|---|---|---|
| Coeff. | Std. Err. | Coeff. | Std. Err. | Coeff. | Std. Err. | |
| Age2 | −0.014*** | 0.000 | −0.017*** | 0.000 | −0.007*** | 0.000 |
| Age | 1.540*** | 0.003 | 1.807*** | 0.003 | 0.902*** | 0.003 |
| Constant | 10.774 | 0.070 | 3.633 | 0.072 | 27.803 | 0.055 |
| Observations | 11,340,625 | 10,751,866 | 18,165,982 | |||
| P > F | 0.000 | 0.000 | 0.000 | |||
| Adjusted R2 | 0.026 | 0.033 | 0.017 | |||
| Average financial stress (FS) | 46.6 | 45.4 | 51.0 | |||
| Age of maximum FS | 54 | 53 | 63 | |||
| Period of FS above average | [34, 74] | [34, 73] | [36, 91] | |||
| Variable | Mexico City | East and south-central | South | |||
|---|---|---|---|---|---|---|
| Coeff. | Std. Err. | Coeff. | Std. Err. | Coeff. | Std. Err. | |
| Age2 | −0.011*** | 0.000 | −0.019*** | 0.000 | −0.019*** | 0.000 |
| Age | 1.227*** | 0.004 | 2.092*** | 0.002 | 2.083*** | 0.003 |
| Constant | 27.281 | 0.093 | 12.087 | 0.043 | 5.472 | 0.060 |
| Observations | 7,331,476 | 26,811,389 | 13,689,511 | |||
| P > F | 0.000 | 0.000 | 0.000 | |||
| Adjusted R2 | 0.015 | 0.058 | 0.055 | |||
| Average financial stress (FS) score | 56.2 | 62.0 | 53.6 | |||
| Age of maximum FS | 55 | 56 | 54 | |||
| Period of FS above average | [34, 75] | [35, 77] | [33, 75] | |||
Note(s): ***p-value<0.001
Source(s): Author's elaboration with Stata (StataCorp, 2017)
Category: Empirical, scientific or clinical research.
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