Exploring differences in African-Americans’ financial well-being based on financial security factors C. W. Copelanda,*, John H. Younga, Crystal R. Hudsona aDepartment of Finance, Clark-Atlanta University, 223 James P. Brawley Drive, Atlanta, GA 30314, USA Abstract What impacts the financial well-being of African Americans, compared with other ethnic groups, has been a mystery beyond basic socio-economic factors. However, when explored through the lens of homeownership and employment, two variables that have been latent due to historical racism, African Americans fare far worse than other ethnic groups. This study utilized data from the 2016 National Financial Well-Being Survey (NFWBS) including the CFP Financial Well-Being Scale, and specifically targeted middle-income African Americans. Researchers found that when efforts are made to pull themselves up by their bootstraps through long-term savings, investing, and education, African Americans only show statistical significance if they are middle-income because student loans tend to create a drag on financial well-being levels. © 2022 Academy of Financial Services. All rights reserved. JEL classifications: I310 (General welfare; Well-being) Keywords: Financial well-being; General welfare; Living standards; Middle class; Middle income; Quality of life; Standard of living; Stress; Homeownership; Employment; Savings 1. Introduction Many African Americans enjoy a middle-class lifestyle, typically a result of a college education. A college education is a means to improve people’s professional status and eco- nomic stability (Blalock, 2017). Nevertheless, is this middle-class lifestyle built on wealth or simply income? In other words, if these African Americans lost their income, would they be able to maintain this lifestyle and live on the wealth that they have saved? Otherwise, what *Corresponding author: Tel.: +1-404-913-1413, fax: +1-404-880-8458. E-mail address: cwcopeland2@cau.edu 1057-0810/22/$ – see front matter © 2022 Academy of Financial Services. All rights reserved. Financial Services Review 30 (2022) 321–336 factors prevent them from experiencing this financial well-being? According to McIntosh et al. (2020), the benchmark of economic security includes employment, homeownership, sav- ings, retirement security, and financial literacy. This present study explores whether middle- class African Americans experience financial security or financial well-being compared with middle-class White Americans. African Americans do not generate as much wealth as the general U.S. population, and the Black-White wealth gap is widening (Kochhar, 2014). In 2013, White households had 13 times the wealth of African American households. This wealth gap had increased since 2010 when White households’ wealth was only 10 times that of African American house- holds (Kochhar, 2014). It is more alarming that African Americans have not generated enough wealth and have been unable to pass on that wealth to their children and grandchil- dren, which leaves them at an economic disadvantage (Pfeffer & Killewald, 2018). This transfer of wealth could be in the form of paying for their children’s college tuition or an outright lump sum of cash (Pfeffer & Killewald, 2018). 2. Financial well-being and wealth Financial behaviors, financial stressor events, and individual characteristics are functions of financial well-being. Financial well-being is also an outcome of financial behaviors (Kim et al., 2003). Whether we as researchers address financial well-being at the household or the individual level, it is apparent that the factors mentioned above affect the financial well- being of African Americans more than other racial or ethnic groups (irrespective of income). The distinction may not be as prevalent if individual characteristics across groups are accounted for; the issue is well recognized when we reduce the number of financial behav- iors and financial stressor events being addressed (as associated issues). One factor identified as an essential determinant of individual success in saving money is the ability to delay grat- ification and exercise self-control. Although economists like to assume that homo economi- cus can postpone short-term gratification for the sake of long-term need, prior research has proven the opposite (Brounen et al., 2016). Brounen et al. (2016) further support the premise with the empirical proof that these time preferences (short-term gratification/long-term need) can be partly transferred from one generation to the next. Financial discipline is—at least partly—the result of how parents raise their children. In other words, financial education and financial upbringing may well be two routes to the same destination—taking individual fi- nancial responsibility later in life. The premise of Wahla and colleagues’ (Wahla et al., 2019) study is that human beings do not act rationally. They tend to be involved in decisions based on heuristics and mental shortcuts. They could be frame-dependent due to their restricted ability to absorb excessive information in complex learning environments. The irrational approach of individuals could lead them to exercise negative investment behaviors. Negative investment behaviors by indi- viduals could also adversely influence their financial well-being. The obvious conclusion is that poor financial behaviors can lead to vulnerability due to a lack of resources in an emer- gency (also classified as a financial stressor event). According to Mello (2018), first, 322 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 consistent with previous research regarding the literature demonstrating widespread financial fragility among U.S. households, the results suggest that many households are underinsured against even small financial shocks. When faced with a traffic fine of less than $200, individ- uals accrue collections and delinquencies on their credit reports, suggesting their inability to cover an unexpected expense. Second, individuals exhibiting minimal distress at the baseline are mainly unaffected by nuisance fines, while those already facing several unpaid bills ex- perience the most significant declines in financial well-being (Mello, 2018). 3. Literature review 3.1. Discrimination in employment and homeownership Although it is easy to point the finger at the individual, numerous external forces play a piv- otal role in African Americans’ low level of financial well-being. Although the order hierarchy is random, the severity is felt across these external forces, for example, the lack of housing eq- uity and low employment prospects resulting from discrimination against African Americans. Some of the best evidence regarding the persistence of employment discrimination comes from audit studies conducted by the Urban Institute (Fix & Struyk, 1993). In these studies, White applicants were favored over Black applicants with identical qualifications 20% of the time. Thus, negative racial stereotypes of African Americans appear to play a role, both when individual employers evaluate potential applicants and when corporate decision-makers delib- erate about the possible locations of employment facilities (Fix & Struyk, 1993). There is a long-documented history of employment discrimination in the United States; how- ever, consumer-level discrimination can be equally damaging. If consumer discrimination exists, growth in consumer contact may help explain recent declines in Blacks’ relative earnings and employment [to Whites] (Holzer & Ihlanfeldt, 1998). Federal laws have been implemented over the years to combat racial discrimination by employers; however, how is the battle won when the discriminating group (i.e., customers) cannot be subjected to legislation? The discrimination experienced by Black workers due to the preferences of White customers is likely to have more negative effects on their wages and employment than any discrimination experienced by White workers due to Black customers, as Whites are more able to find employment in sectors without customer discrimination against them (Holzer & Ihlanfeldt, 1998). Stable employment is at the foundation of positioning oneself for wealth accumulation. Without it, the premise of homeownership and investment does not exist. Nevertheless, even when stable employment is legislated, barriers to homeownership may still exist. Because much of the wealth of most American families take the form of home equity, a substantial part of this race-based inequity in homeownership is linked to housing policies and institu- tional discrimination experienced in the past (Oliver & Shapiro, 2006). In an optimally func- tioning housing market, it could be assumed that each household selects the type of tenure that maximizes its utility. People who move frequently are highly risk-averse or dislike the responsibilities of homeownership would-be renters. People who desire to use small housing services rent because small housing units are not generally available for purchase. As C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 323 suggested by McDonald (1974), If it is presumed that Black and White Americans do not differ in their risk aversion and taste for the responsibilities of homeownership, some urban Black households rent but would own if they faced the same housing market Whites face. The White housing submarket is characterized by a higher relative number of single-family houses and less difficulty obtaining mortgage credit (McDonald, 1974). Despite U.S. policies to increase minority homeownership (or because of them), the hous- ing market and foreclosure debacle, fueled by lending discrimination, has further exacer- bated disparities in homeownership between Caucasians and minorities. In some cases, homeownership rates are worse than those that existed nearly 25 years ago (Williams, 2015). For these groups, the American Dream has become too elusive. Furthermore, lending discrimination has trajectorial effects on entire communities (Williams, 2015). Because of the operation of these large-scale societal processes, indicators of socioeconomic status are not equivalent across racial groups; this is true at the community, the household, and the individual levels. Because of residential segregation, Black and White neighborhoods dra- matically differ in the availability of jobs, family structure, opportunities for marriage, edu- cational quality, and exposure to conventional role models. They also differ in their quality of life and access to resources and amenities that sustain health (Williams, 1999). These two external forces alone have had a tremendous impact on African Americans’ financial well- being. Unfortunately, they have compounded the issue, leaving room for many external forces to thrive. 3.2. Savings and investing in the stock market African Americans do not invest in the stock market as much as White Americans. Furthermore, this could contribute to African Americans’ lack of accumulated wealth and the fact that they do not experience as much financial well-being as White Americans (Herring & Henderson, 2016; Kochhar, 2014). Moreover, African Americans do not save or replenish their savings as much as White Americans, which could again be a factor contrib- uting to African Americans’ limited wealth and financial well-being (Kochhar, 2014). Herring and Henderson (2016) explored possible reasons for the Black-White wealth gap and conducted Ordinary Least Squares analysis and quantile regression analysis of the Survey of Consumer Finances data. They found that African Americans had significant income, stock ownership, and business ownership disadvantages. The researchers also found that African Americans received lower returns on education, stock ownership, and business ownership than White Americans (Herring & Henderson, 2016). Similarly, Gutter and Copur (2011) examined the relationship between financial behaviors and financial well- being. The researchers used data obtained from 15,797 college students for this study and found that budgeting, saving, risky credit card behavior, and compulsive buying behavior were significantly related to financial well-being (Gutter & Copur, 2011). Stromback et al. (2017) investigated what psychological characteristics influenced indi- viduals’ positive financial behavior and financial well-being. The authors surveyed 2,063 participants from the Swedish population. They found that individuals with good self-control were more likely to save money from every paycheck, had better general financial behaviors, 324 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 felt less anxious about financial matters, and felt more secure in their current and future fi- nancial situations (Stromback et al., 2017). Sivaramakrishnan and Srivastava (2019) wanted to understand the influence of risk avoidance and financial well-being on investing in equity products. Sivaramakrishnan and Srivastava’s (2019) research team chose urban, retail, and middle-class investors from four cities in India. They found that financial well-being or the feeling of financial security did not embolden individuals to invest in the stock market. Instead, it proved to deter indi- viduals from participating in the stock market (Sivaramakrishnan & Srivastava, 2019). Moreover, Sabri et al. (2020) investigated the relations among financial management, sav- ings, investment behavior, and financial well-being. They surveyed 722 working women in the Malaysian public sector and used a multistage random sampling method. According to their study, 39.2% of the women indicated that their assets were more than their debts, and 44.3% said their salary was sufficient to meet their basic requirements (Sabri et al., 2020). Moreover, more than 80% practiced good financial management behaviors. The researchers found that the Malaysian working women had good financial management practices, which were indicated by their ability to engage in savings and investment behavior to manage their surplus money wisely to achieve a higher level of financial well- being (Sabri et al., 2020). 3.3. Financial literacy and education Evidence also shows a strong relationship between financial knowledge and the likelihood of engaging in desirable financial practices: paying bills on time, tracking expenses, budget- ing, paying credit card bills in full each month, saving out of each paycheck, maintaining an emergency fund, diversifying investments, and setting financial goals (Hilgert et al., 2003). Low financial literacy (an outcome of inadequate financial knowledge) is associated with poor financial decisions in equity investment, debt financing, as well as long-term retirement planning, and these decisions can lead to decrease in welfare (Chu et al., 2017). According to Chu et al. (2017), households with lower levels of financial literacy can also make suboptimal decisions when choosing loans or mortgages, as well as suffer from prob- lems, such as debt accumulation, bankruptcy, and foreclosure. Suboptimal decisions can clearly lead to not only lower amounts of wealth but perhaps even its absence. People’s atti- tudes toward money rely on different variables, such as individuals’ adolescence experien- ces, education, and economic and societal status. Depending on these variables, the attitudes toward money differ from person to person (Qamar et al., 2016). Studies on financial issues reveal that an individual’s attitudes toward money play a sig- nificant role in deciding one’s financial management and level of financial well-being (Shim et al., 2010). Based on the depth and consistency of research in this area, this leads to the conclusion that responsible financial behavior is strongly related to strong financial knowl- edge (Zakaria et al., 2012). Qamar et al. (2016) found that individual financial efficacy had a strong positive associa- tion with financial well-being. They tested this hypothesis: “There is a relationship between C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 325 financial efficacy and financial well-being” (1458). The conclusions from this research were in favor of the hypothesis. Shim et al. (2010) found that financial literacy alone was insuffi- cient to guarantee control over individual finances; financial self-efficacy was similarly im- portant. What is the difference between financial literacy and financial efficacy? While researchers have a good grasp of financial literacy, financial efficacy is a much less publi- cized concept. The most common definition of financial efficacy is a person’s perceived capability to control one’s personal finances (Lapp, 2010; Postmus, 2011). With this under- standing, it makes sense to move forward with the attitude that financial literacy and finan- cial efficacy must work in tandem to create a positive outcome; however, before closing the door on this discussion, a few other terms used in industry discussions can be explored. As noted by Brounen et al. (2016), financial knowledge involves understanding key financial terms and ideas needed to function day by day in society. They also state that the terms financial literacy, financial knowledge, and financial education have regularly been used interchangeably in both academic literature and the mainstream media. Financial education facilitates literacy, that is, mastery of finance-related knowledge and expertise, which are essential in undertaking daily transactions and wealth accumulation investments. It empowers people to manage their own finances and provide long-lasting financial security for themselves and their families (Sundarasen et al., 2016). Based on the latter two cited studies’ findings, the respondents who are financially interested, keep a tight household administration, have a strong locus of control, and have a positive economic outlook are all more prone to postpone immediate consumption for the sake of future needs. Households that save money share a certain set of personality varia- bles (Brounen et al., 2016). With theoretical and empirical support, the results of Sundarasen and colleagues’ (Sundarasen et al., 2016) study indicate that parental norms, socialization prox- ies, and financial literacy play a significant role in money management. 3.4. Conceptual framework and theory From the start, the life-cycle theory (see Figure 1) reports that individuals consume resources in various amounts throughout their lives based on income and family dynamics. In light of this theory, we can assume that individuals emphasize consumption to provide utility, leading to financial well-being. Variables such as financial knowledge and employ- ment seem to have an equal influence on financial behaviors and financial well-being. Additionally, financial behaviors such as home acquisition and savings are an expected part of the life-cycle and should positively influence financial well-being. Based on the life cycle theory, the researchers have put forward the following hypothesis: 4. Hypotheses H1: African Americans have lower levels of financial well-being compared with White Americans. H2: African Americans who are employed full time are more likely to have higher levels of financial well-being than African Americans who are not employed full time. 326 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 H3: African Americans who own their homes are more likely to have higher levels of fi- nancial well-being than African Americans who do not own their homes. H4: African Americans who are financially knowledgeable are more likely to have higher levels of financial well-being than African Americans who are not financially knowledgeable. H5: African Americans with savings greater than $5,000 and with investments are more likely to have higher levels of financial well-being than African Americans who have sav- ings of less than $5,000 and have no investments. 5. Methods 5.1. Data and sample selection This study explores the financial security of African American households with an income of $40,000 or more, based on the U.S. census’ median African American income of $45,438 in 2019 (Semega et al., 2020). The study’s target population consists of households belong- ing to the income baseline of $40,000 or greater, representing 68% of the sample set. The study sample comprised 4,339 respondents from the income range of $40,000 to $150,000 plus, divided into three ethnic groups. Of the 4,339 households, 3,070 (70.7%) identified themselves as White Americans, 407 (9.4%) as African Americans, and 862 (19.9%) as other Americans. This study used the 2016 National Financial Well-Being Survey (NFWBS) that the Consumer Financial Protection Bureau (CFPB) administers and releases. The NFWBS was designed to measure the levels and distribution of financial well-being among the U.S. adult population and to provide household characteristics, income levels, and employment characteristics, financial experiences, and financial behaviors, skills, and Fig. 1. This model was produced by Pettinger (2019), the Life-Cycle hypothesis. From Economicshelp.org (https://www.economicshelp.org/blog/27080/concepts/life-cycle-hypothesis/). C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 327 attitudes. Both descriptive and multivariate results were weighted according to the NFWBS study weights to represent the U.S. population. Table 1 exhibits the summary statistics of the dataset. 6. Measurement of variables [database] 6.1. Dependent variables A CFPB Financial Well-Being Scale score is a standardized number between 0 and 100 that represents the respondent’s underlying level of financial well-being. A higher score indi- cates a higher level of measured financial well-being, but there is no specific cutoff score for Table 1 Descriptive statistics of the weighted sample Overall sample (n = 4,339) Variables White Americans (n = 3,070) African Americans (n = 407) Other Americans (n = 852) Observations % Observations % Observations % Financial well-being (FWB) Low FWB 753 24.5 123 30.2 277 32.2 Average FWB 1,030 33.6 142 34.9 336 39.0 High FWB 1,287 41.9 142 34.9 249 28.8 Household income $40,000–49,999 268 8.7 55 13.5 107 12.4 $50,000–59,999 318 10.4 67 16.5 96 11.1 $60,000–74,999 425 13.8 51 12.6 118 13.7 $75,000–99,999 591 19.2 80 19.7 179 20.8 $100,000–149,999 755 24.6 79 19.5 183 21.2 $150,000 or more 713 23.3 75 18.2 179 20.8 Gender Male 1,505 49.0 164 40.3 448 52.0 Female 1,565 51.0 243 59.7 414 48.0 Age group 34 and under 862 28.1 133 35.5 382 44.3 35–54 1,071 34.8 161 39.7 310 36.0 55–69 767 25.0 83 20.4 134 15.5 70 and over 370 12.1 30 7.4 36 4.2 Marital status Unmarried 838 27.3 172 42.3 323 37.5 Married 2,232 72.7 235 57.7 539 62.5 Education level Some college or less 1,772 57.7 230 56.5 541 62.8 College degree 799 26.0 107 26.3 215 24.9 Post-graduate degree 499 16.3 70 17.2 106 12.3 Employment status Self-employed 193 6.3 21 5.2 74 8.6 Full-time 1,531 49.9 242 59.4 432 50.1 Retired 617 20.1 59 14.5 77 8.9 Other 729 23.7 85 20.9 279 32.4 328 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 a “good” or a “poor” score. The respondents were classified into three categories, namely low financial well-being (0–49.9), average financial well-being (50–60.9), and high financial well-being (61–100); (Consumer Financial Protection Bureau, 2015, 2017). In this study, financial well-being is the dependent variable. It was converted into an ordi- nal qualitative variable using the visual binning technique to identify appropriate cutoff points to break the variables into three approximately equal groups. Equal percentiles were used based on the scanned cases (equal intervals with two cutoff points). Thus, this study considered the dependent variable a multinomial ordinal-dependent variable (1 = low, 2 = average, and 3 = high; Lobos et al., 2016; Nielsen, 2015). 6.2. Independent variables The primary focus of this research was homeownership. The dataset comprised four hous- ing groups: owners, renters, neither, and refused to answer. The respondents were coded as 1 if they were homeowners and 0 otherwise. Four demographic characteristics were included as control variables in the analysis. Age group, education level, gender, and employment status were coded as several binary varia- bles: 34 and under, 35–54, 55–69, and 70 and over; some college or less, college degree, and post-graduate degree; self-employed, full-time, retired, and not employed, respectively. The 70 and over variable was the reference group for the age group; the post-graduate degree variable was the reference group for education level, and the not employed variable was the reference group for employment status. Gender was dichotomized and defined as male = 1 and female = 0. The financial security variables were defined to reflect the conceptual framework. Household savings was based on a single question, with the responses measured on a scale from 1 ($0 saved) to 7 ($75,000 or more). Student loan (the subjectively assessed probably have variable) was based on the responses yes = 1 and no = 0. Non-retirement investments (the subjectively assessed probably have variable) were based on a question with the responses yes = 1 and no = 0. Retirement investments (the subjectively assessed probably have variable) were based on a question with the responses yes = 1 and no = 0. The financial knowledge scale (the objectively assessed financial knowledge) was based on the number of correct answers to the nine questions formulated by Houts and Knoll (2020). 6.3. Model specifications A multinomial logistic regression model was used in this study. The financial well-being level was assumed to be a function of financial security factors, including financial knowl- edge, household savings, homeownership, and investments, as well as socioeconomic fac- tors, such as age group, marital status, education level, and employment status. Financial Wellbeing ¼ f financial security factors and socioeconomic factorsð Þ (1) C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 329 Logit rð Þ ¼ log r High Well Beingð Þ r Middle Well Beingð Þ � � ¼ b 0 þ b 1x 1 þ b 2x 2 þ � � � þ b k xk (2) Logit rð Þ ¼ log r Low Well Beingð Þ r Middle Well Beingð Þ � � ¼ b 0 þ b 1x 1 þ b 2x 2 þ � � � þ b k xk , (3) where b denotes a vector of coefficients to be determined, and x represents a vector of African Americans’ financial security factors and socioeconomic characteristics. 7. Results 7.1. Descriptive statistics Table 1 provides descriptive statistics of the survey sample set. The sample comprised 70.8% White Americans, 9.6% African Americans, and 19.6% other Americans. Surprisingly, at the middle (average) financial well-being level, White Americans had the lowest (33.6%) percentage compared with African Americans (34.9%) and other Americans (39%). Income levels between $100,000 and $149,999 were the highest represented group, with about 25% White Americans, 20% African Americans, and 21% other Americans. Females dominated the sample set, with 51% White Americans and 59.7% African Americans, except for (48%) other American households. The same pattern emerged in the 35–54 age group, while the other Americans (44.3%) had a higher share of the 34 and younger group. Most of the respondents were married, comprising 72.7% White Americans, 57.7% African Americans, and 62.5% other Americans. Regarding education levels across all groups, having some col- lege education was the most influential statistic. Full-time employment was evenly spread across the groups: approximately 50% White Americans, 60% African Americans, and 50% other Americans. Table 2 presents the multinominal logistical estimates of the likelihood of obtaining a low score in financial well-being by ethnicity group. When comparing the average-level respondents with the low-level respondents, no significant differences were discovered, with White Americans as the reference group. More interestingly, the African Americans’ financial well-being level was significantly related to the high level among White Americans compared with the low level among the reference families. However, when comparing the likelihood of obtaining a high score in financial well-being compared with a low score, African Americans comprised the most unlikely group (47.6%, p < .001) at the high level compared with White Americans. Other Americans comprised the next unlikely group (32.2%, p < .01) compared with White Americans. Therefore, ethnicity seems relevant in households classified as having a low level of financial well-being— African Americans to a large extent compared with White Americans. Based on the results, hypothesis H1 is not rejected (Table 2). 330 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 7.2. Multinomial logistic results The purpose of the second stage of the analysis was to isolate better the link between the financial well-being levels and financial security factors (e.g., full-time employment, home- ownership, financial knowledge levels, savings rate, and investor status). The multinomial logistic regression analysis results are presented in Table 3. 7.3. Average-level versus low-level financial well-being The first model (Table 3, low [column heading]) specifically investigated the differences between American households with low scores in financial well-being and those with aver- age scores across ethnic groups (White Americans, African Americans, and other Americans). An analysis of the education level showed that White Americans with a low level of financial well-being and some college education or less were 42.7% (p < .05) more likely than post-graduate respondents to have low scores in financial literacy. Surprisingly, the education level was not significant for African Americans and other Americans com- pared with post-graduate respondents. Retired respondents were less likely to be classified as having a low level of financial well-being compared with respondents who had average- level scores. More specifically, White American retirees (52.5%, p < .01) and African Americans (80.2%, p < .05) were less likely to be included in the group with a low level of financial well-being. Other Americans’ scores were not significant when compared with the average level scores. Other Americans (22.4%, p < .05) comprised the only group affected by the financial knowledge scale, indicating an unlikelihood of being classified in the low- level financial well-being group compared with the average-level group. Financial knowledge levels were not significant for White Americans and African Americans. Household savings of less than $5,000 appeared to be the most impactful factor for Americans’ likelihood of being classified as belonging to the group with a low level of fi- nancial well-being. White Americans (261.6%, p < .001), African Americans (467.1%, p < .001), and other Americans (122.2%, p < .001) were more likely to be included in the group with a low level of financial well-being. Only African American respondents (91.3%, p < .05) Table 2 Multinominal logistical analysis of the likelihood of financial well-being levels among ethnic groups Financial well-being levels (n = 4,339) Average High b Exp(b ) b Exp(b ) Intercept 0.314 0.536 Ethnicity group: Reference category = White Americans African Americans �0.121 0.886 �0.647*** 0.524 Other Americans �0.167 0.846 �0.388** 0.678 Notes. The exponentiated coefficient minus one and times 100 gives the percentage increase or decrease due to a one-unit change in the independent variable. The reference category for the model is the low financial well- being group. **p < .01, ***p < .001. C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 331 T ab le 3 M u lt in o m in al lo g is ti ca l an al y si s o f th e li k el ih o o d o f fi n an ci al w el l- b ei n g le v el s (fi n an ci al se cu ri ty v ar ia b le s) F in an ci al w el l- b ei n g le v el s (n = 4 ,3 3 9 ) P ar am et er es ti m at es W h it e A m er ic an s (n = 3 ,0 7 0 ) A fr ic an A m er ic an s (n = 4 0 7 ) O th er A m er ic an s (n = 8 6 2 ) L o w H ig h L o w H ig h L o w H ig h b E x p (b ) b E x p (b ) b E x p (b ) b E x p (b ) b E x p (b ) b E x p (b ) In te rc ep t �1 .9 1 1 0 .6 9 7 �1 .1 2 4 2 .2 5 5 �2 .7 9 9 0 .7 5 7 A g e g ro u p : R ef er en ce ca te g o ry = 7 0 an d o v er 3 4 an d u n d er 0 .3 5 4 1 .4 2 5 �0 .0 9 0 0 .9 1 4 �0 .2 9 3 0 .7 4 6 �0 .4 0 5 0 .6 6 7 0 .8 9 8 2 .4 5 4 �1 .0 7 3 0 .3 4 2 3 5 – 5 4 0 .3 2 7 1 .3 8 7 �0 .5 5 9 * * 0 .5 7 2 �0 .5 8 6 0 .5 5 7 �0 .8 5 8 0 .4 2 4 0 .8 8 8 2 .4 3 0 �1 .0 0 1 0 .3 6 7 5 5 – 6 9 0 .2 5 8 1 .2 9 4 �0 .3 3 5 0 .7 1 5 �1 .0 3 0 0 .3 5 7 �0 .8 4 5 0 .4 3 0 1 .0 8 8 2 .9 7 0 �0 .6 5 6 0 .5 1 9 M ar it al st at u s: R ef er en ce ca te g o ry = U n m ar ri ed M ar ri ed �0 .0 3 7 0 .9 6 4 0 .0 5 4 1 .0 5 6 0 .3 9 2 1 .4 8 0 0 .3 1 3 1 .3 6 7 0 .2 0 1 1 .2 2 3 0 .0 0 7 1 .0 0 7 E d u ca ti o n le v el : R ef er en ce ca te g o ry = P o st -g ra d u at e d eg re e S o m e co ll eg e o r le ss 0 .3 5 6 * 1 .4 2 7 �0 .1 3 0 0 .8 7 8 �0 .2 8 1 0 .7 5 5 �0 .6 7 2 0 .5 1 1 0 .0 3 5 1 .0 3 6 0 .3 0 1 1 .3 5 2 C o ll eg e d eg re e 0 .2 0 0 1 .2 2 2 0 .0 0 0 1 .0 0 0 0 .1 3 9 1 .1 4 9 �0 .8 5 4 * 0 .4 2 6 0 .1 3 2 1 .1 4 1 �0 .3 2 4 0 .7 2 3 E m p lo y m en t ty p e: R ef er en ce ca te g o ry = N o t em p lo y ed S el f- em p lo y ed 0 .1 9 6 1 .2 1 7 0 .3 3 5 1 .3 9 8 �1 .1 2 2 0 .3 2 6 �1 .3 9 3 * 0 .2 4 8 0 .1 2 9 1 .1 3 8 0 .1 2 6 1 .1 3 4 F u ll -t im e 0 .0 9 8 1 .1 0 3 0 .0 4 7 1 .0 4 8 �0 .5 7 9 0 .5 6 1 �0 .6 1 7 0 .5 3 9 0 .3 9 3 1 .4 8 1 0 .3 6 7 1 .4 4 4 R et ir ed �0 .7 4 4 * * 0 .4 7 5 0 .6 4 5 * * * 1 .9 0 7 �1 .6 2 1 * 0 .1 9 8 �0 .7 5 7 0 .4 6 9 �0 .0 0 1 0 .9 9 9 0 .4 4 4 1 .5 6 0 F in an ci al k n o w le d g e sc al e: R ef er en ce ca te g o ry = S ca le : �2 .0 to 1 .5 K n o w le d g e sc al e 0 .0 0 0 1 .0 0 0 0 .4 2 3 * * * 1 .5 2 7 �0 .3 0 2 0 .7 3 9 0 .1 0 2 1 .1 0 8 �0 .2 5 3 * 0 .7 7 6 0 .2 8 5 * 1 .3 2 9 H o u se h o ld sa v in g s: R ef er en ce ca te g o ry = $ 5 ,0 0 0 o r m o re $ 0 – 4 ,9 9 9 1 .2 8 5 * * * 3 .6 1 6 �0 .7 9 3 * * * 0 .4 5 3 1 .7 3 5 * * * 5 .6 7 1 �0 .5 2 6 0 .5 9 1 0 .7 9 8 * * * 2 .2 2 2 �0 .9 3 0 * * * 0 .3 9 4 H o m eo w n er sh ip st at u s: R ef er en ce ca te g o ry = H o m eo w n er N o n -h o m eo w n er 0 .0 8 5 1 .0 8 9 �0 .4 1 8 * * 0 .6 5 8 0 .6 4 9 * 1 .9 1 3 �0 .5 8 3 0 .5 5 8 0 .4 1 9 1 .5 2 1 �0 .0 5 4 0 .9 4 8 In v es tm en ts (r et ir em en t an d n o n -r et ir em en t) : R ef er en ce ca te g o ry = Y es N o 0 .4 7 8 * * * 1 .6 1 3 �0 .2 7 3 * 0 .7 6 1 0 .1 6 8 1 .1 8 3 �0 .1 5 0 0 .8 6 0 0 .8 1 4 * * * 2 .2 5 8 0 .1 2 2 1 .1 2 9 N o te s. T h e ex p o n en ti at ed co ef fi ci en t m in u s o n e an d ti m es 1 0 0 g iv es th e p er ce n ta g e in cr ea se o r d ec re as e d u e to a o n e- u n it ch an g e in th e in d ep en d en t v ar i- ab le . T h e re fe re n ce ca te g o ry fo r th e m o d el is th e av er ag e fi n an ci al w el l- b ei n g g ro u p . * p < .0 5 , * * p < .0 1 , * * * p < .0 0 1 . 332 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 who were not homeowners had a score significant enough to be included in the group with a low level of financial well-being compared with the average level. Homeownership was not significant for White Americans and other Americans. Not having an investment account (retirement and non-retirement) was significant for White Americans (61.3%, p < .001) and other Americans (125.8%, p < .001), indicating their membership in the group with a low level of financial well-being. Surprisingly, not having an investment account was not signifi- cant for African Americans. Unexpectedly, the age group and marital status had no significant impact on the respondents’ financial well-being levels compared with the average-level and the low-level financial well-being. 7.4. Average-level versus high-level financial well-being The second model (Table 3, high [column heading]) in the multinomial logistic analysis estimated the likelihood that a person would belong to the average-level financial well-being group compared with the high-level financial well-being group. An analysis of Americans’ age groups and financial well-being revealed that the relation between these variables was only significant for White Americans with high-level financial well-being compared with the average group. White respondents in the 35–54 age group were 42.8% (p < .01) less likely to be classified in the high-level financial well-being category than the respondents aged 70 and older. The scores of African Americans and other Americans were not signifi- cant enough to be in the range of high-level financial well-being. Conversely, when review- ing high-level financial well-being, education level played a significant role solely for African Americans; college-graduate respondents were 57.4% (p < .05) less likely to be classified as having a high level of financial well-being than post-graduate respondents. As expected, White retired respondents were 90.7% (p < .001) more likely to be included in the high-level financial well-being group than their unemployed counterparts. However, self- employed African American respondents were 75.2% (p < .05) less likely to be members of the said group than their unemployed counterparts. Employment levels were not significant for the other Americans. Interestingly, the respondents with savings of less than $5,000 were less likely to belong to the high-level financial well-being group than the respondents with more than $5,000 in savings (White Americans at 54.7%, other Americans at 60.6%, and not significant for African Americans). Surprisingly, financial knowledge level (52.7% more likely, p < .001), homeownership (34.2% less likely, p < .01), and investment account status (23.9% less likely, p < .05) were significant solely for White Americans in the high-level financial well- being group when compared with the reference groups. Furthermore, marital status did not appear to significantly affect the respondents’ financial well-being at a high level. 8. Discussion Consistent with past studies (Herring & Henderson, 2016; Kochhar, 2014), this study found that high-level financial well-being was unlikely associated with African Americans. C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 333 Regarding savings of $5,000 or greater, the findings suggest that compared with savers with less than $5,000 in savings, African Americans had a stronger association with financial se- curity and financial freedom of choice. This saving gap may be because African Americans lack trust in the financial markets or the banking system, which delivers limited financial knowledge, such as interest on savings, inflation, bond prices, and risk diversification. Limited financial knowledge coupled with non-homeownership occurs at the stage of life when African Americans are working and are less likely to adhere to financial planning for long-term goals. Compared with demographic factors (formal education level and employ- ment status), each financial well-being level examined in this study (low, middle, or average, high) showed a relatively small association with objective African American financial well- being. This finding implies that understanding one’s financial situation and financial capabil- ity can address financial wellness deficiencies for all households, regardless of their levels of financial well-being. This study’s findings that financial well-being had a positive association with the self- reported savings level and the self-reported homeownership status underscore the impor- tance of shaping trust in the financial sector’s impact on African Americans’ upward finan- cial mobility. Interestingly, savings of $5,000 or greater had a tremendous positive impact on self-reported savings, suggesting that ethnicity affects whether an individual is exposed to stocks versus savings at a young age. Such lack of exposure plays a fundamental role in African Americans’ financial well-being gap. This finding corroborates past studies’ results showing that savings at the expense of investing have a critical influence on children’s lives as they grow up and continue to influence the wealth-building gap of their own children when they become adults (Asli & Elif, 2019; Jorgensen & Savla, 2010). 9. Conclusion and implications This research found that African Americans who had a post-graduate degree, owned a home, and had savings of over $5,000 were more likely to have a higher level of financial well-being than African Americans who lacked these characteristics. Therefore, most of the financial security variables in this study proved to have impacts on African Americans’ fi- nancial well-being. The only financial security variables that had no effect were financial knowledge and investing in the stock market. The implications for financial institutions are enormous. African Americans are willing to save because of the sense of financial security associated with that behavior. The more edu- cated cohort of this ethnic group tends to save at higher rates and has more satisfaction from the activity. Financial institutions have a chance to leverage multiple products to satisfy this cohort because there is an underlying desire to transition from “saving” to “investing.” The implications for policy-makers are also looming; as African Americans become more finan- cially literate, their capacity to become homeowners increases, which positively impacts the tax base of the municipalities where they reside. The implications for researchers intensify as we understand the differences in financial behavior of the various financial cohorts of African Americans and their contrasts with other ethnic groups. 334 C. W. Copeland et al. / Financial Services Review 30 (2022) 321–336 References Asli, E. A., & Elif, A. S. (2019). An investigation of financial literacy, money ethics and time preferences among college students: A structural equation model. 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