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An Overview of Contemporary Financial Education Initiatives Aimed at Minority Populations

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Abstract

Minority groups, particularly Hispanics and Blacks, are less likely to use formal financial advice compared to their White counterparts and have lower levels of financial literacy on average. This gap in literacy may have important implications for savings, investing, and retirement planning. To better reach these groups and improve financial literacy, the literature recommends making access to financial education easier, targeting the education to the population, and delivering it through preferred methods. Although they have not been thoroughly evaluated for effectiveness, this chapter provides an overview of several promising, real-world financial education initiatives targeted toward minority populations.

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Notes

  1. 1.

     Chairman of the Federal Reserve Ben Bernanke posited this theory at a speech at Morehouse College, where he suggested, “[t]here needs to be a broader understanding in minority communities, which haven’t had that much exposure, about saving and building a credit record and being part of the mainstream economy” (Ahrens, 2009).

  2. 2.

     It is difficult to claim that financial education as a whole is either effective or ineffective. Education efforts take a variety of forms, some of which are likely to be more beneficial than others. Further research is needed on the relative effectiveness of different content and delivery methods.

  3. 3.

     Even among those skeptical of financial education’s broader value, certain types of formal, more personalized financial advice are seen as a potentially promising approach to improving financial behavior and well-being (Willis, 2009).

  4. 4.

     Readers should note that one potentially important variable not included in the regression is wealth, which may be an explanatory or response variable in this context. Wealthier individuals may be more likely to use formal advisors, and the differences seen in Table 6.1 along lines of race and ethnicity could therefore reflect disparate levels of wealth. However, at the same time, wealth may be a response variable if the use of formal financial advisors increases financial holdings (as we suggest).

  5. 5.

    The odds ratio for Black respondents is significant at p  <  0.05, and the odds ratio for Hispanic respondents is significant at p  <  0.10. Note that the odds ratio does not measure relative risk; in this instance, it specifically represents the ratio of the odds that a Black or Hispanic respondent will receive formal investment to the odds a White respondent will obtain this type of advice.

  6. 6.

    Moreover, minority groups may be particularly open to changing their savings behavior based on increased formal advice. According to the Ariel/Schwab Black Investor Survey (2008), 66% of Black respondents report that additional employer-provided advice would lead them to invest more in their defined contribution plan (compared with 43% of White respondents).

  7. 7.

     Ramirez (2005) notes other barriers that may prevent Hispanic consumers from joining traditional financial institutions, including lack of available income and savings, documentation problems, the use of inappropriate advisors, and poor previous experiences with banks in one’s home country.

  8. 8.

     The authors report similar discrepancies for retirement accounts; 58.2% of White, non-Hispanic respondents held this asset, while the comparable figure for non-White or Hispanic respondents was only 39.1%.

  9. 9.

    In many instances in this chapter, we combine Blacks and Hispanics in discussing financial literacy and education. However, this is not meant to imply that both groups share homogeneous obstacles, needs, and preferences. For example, as noted in the text, Rhine and Toussaint-Comeau (2002) show that preferences for both formal courses and informal sources are significantly higher among Hispanics, compared with Blacks, although both groups prefer these methods more than Whites.

  10. 10.

    In our analysis of the SCF data, we categorize financial advice provided through television and the Internet as public sources (see Appendix 1). Since the source of the information offered through these channels is not known, we cannot categorize them as formal sources for our analysis. However, this does not preclude providing high-quality, professional financial advice through these sources.

  11. 11.

    For more information on the structure of the SCF, as well as potential methodological concerns, see Lindamood, Hanna, and Bi (2007) and Kennickell (2009).

  12. 12.

    One important variable that is not in the public SCF data is the primary language spoken at home. Research indicates that overcoming language barriers is critical in increasing Hispanic participation in mainstream financial institutions (Braunstein & Welch, 2002 and Toussaint-Comeau, 2003). Another limitation is that the public data set does not include information on geographic location. This data is captured by the Federal Reserve for internal analyses of bank market structure, but it is not available to the public. As discussed in the paper, access to mainstream financial resources can differ based on the predominant racial and economic make-up of neighborhoods (Temkin & Sawyer, 2004).

  13. 13.

    Regression analysis in the SCF is complicated by the presence of implicates; specifically, missing data is filled in with multiple imputations rather than a single estimate, ultimately creating five separate data sets (Lindamood et al., 2007). The SCF Codebook includes a detailed description of the methodology used in creating the data set as well as instructions for obtaining accurate point estimates, standard errors, and t statistics (Kennickell, 2009). These guidelines, outlined in Kennickell (2009) as “MACRO MISECOMP,” were followed in creating the final estimates reported in Table A1. It also should be noted that weights are not used in this regression model, as the appropriateness of using weights in multivariate analyses of SCF data is debatable (Lindamood et al., 2007).

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Correspondence to Anya Olsen .

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Appendices

Appendix 1. Binary logistic regression on use of a formal advisor

Although this work is not intended to be a traditional research paper, we use data from the Survey of Consumer Finances (SCF) throughout. The SCF is a triennial survey of the balance sheet, pension, income, and other demographic characteristics of US families administered by the Federal Reserve Board along with the Statistics of Income (SOI) Division of the Internal Revenue Service. We use the SCF to analyze the use of formal sources of financial advice among minorities, as well as to examine the connection between the use of formal sources of financial education and different elements of savings behavior.Footnote 11

Our analysis relies heavily on the SCF variable asking respondents to list the sources of advice used in making saving and investment decisions. We classify the 26 responses to this question (covering individuals, organizations, and delivery methods) into five categories: “Formal Advisor,” “Informal Advisor,” “Public Sources,” “Other,” and “Not Receiving Advice.” The “Formal Advisor” category encompasses advice received from lawyers, accountants, bankers, brokers, financial planners, and insurance agents as well as materials from work/business contacts, investment clubs, investment seminars, or other institutional sources such as colleges or social service agencies. The “Informal Advisor” group includes advice received from a friend/relative, oneself, partner, spouse, or telemarketer. The “Public Sources” category refers to financial information obtained through calling around, magazines/newspapers, material in the mail, television/radio, online service/Internet, advertisements, other personal research, shopping around, or a store/dealer. The “Other” category includes advice that comes from past experience, another nonlisted source, as well as the answer “Don’t shop around; always use same institution.” The “Not Receiving Advice” category includes those answering “Do Not Save/Invest” and not answering positively in any of the other categories. We employ these categorizations in both descriptive and binary logistic regression analyses to better understand the issues raised by the literature regarding financial advice and minority groups. Our regression model uses the binary construct “Formal Advisor,” rather than original sources of advice question, as the dependent variable with dependent dummy variables for race/ethnicity, the presence of a banking relationship, savings behavior, income, education, age, and marital status.Footnote 12

Consistent with the research cited previously, Table A1 shows that Black and Hispanic respondents have lower odds of receiving formal investment advice, compared with Whites, holding the other variables in the model constant. The reported odds ratios are the ratios of the odds that a respondent with the listed characteristic will receive formal investment advice to the odds for a respondent in the designated reference group. As an example, the odds ratio for Black respondents below can be interpreted in the following way: The odds that a Black respondent will use formal investment advice are 0.77 times as large as the odds that a White respondent will obtain advice from a formal source.

Table A1 Logistic regression: use of formal investment advice by different socio-demographic categories, 2007

Appendix 2. Summary of contemporary initiatives that are providing financial education to minorities

Factors affecting the use of formal financial education by minorities

Contemporary initiatives to address these factors

Access

Private institutions can lower costs associated with minimum balances, fees, and opening an account or offer free checking accounts, free checks, and free transactions (price products below those of alternative service providers)

Private institutions can provide special services in a dedicated space at a regular branch

Bring services into the workplace and operate in locations frequented by employees

Offer convenient locations (workplace, community centers, churches, schools, and day care centers) and hours (evenings and weekends)

Pay employees to attend financial education sessions or allow employees to volunteer their time to serve as educators or trainers for financial education programs

Private institutions, community organizations, and schools should coordinate efforts to create financial education programs

Targeting

Use pretraining tests to assess the audience’s financial education needs, interests, and expected outcomes

Offer specific, goal-oriented programs, such as reducing debt or accumulating savings

Use teachable moments, such as buying a home or filing income taxes

Cover basic topics: budgeting, banking, credit, savings, and homeownership

Utilize relevant existing financial literacy curriculums

Delivery

When holding informal seminars or courses, have presenters who are culturally or ethnically/racially similar to the audience

When holding informal seminars or courses, provide baby-sitting services and other incentives for attending (food, gifts, free services, and prizes)

Separate the business aspect of your organization (if for-profit) from the financial education program being offered

Utilize ethnic newspapers, magazines, television channels, and radio stations

Tie financial literacy messages into entertaining programs on TV, the radio, and Internet or through videos and video games

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Olsen, A., Whitman, K. (2011). An Overview of Contemporary Financial Education Initiatives Aimed at Minority Populations. In: Lamdin, D. (eds) Consumer Knowledge and Financial Decisions. International Series on Consumer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0475-0_6

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