INTRODUCTION

Why do consumers not contribute to company sponsored retirement plans? This question has been asked by researchers and journalists for many years. In a recent article published in 2020 by Heritage Capital LLC, they found that in 2018, approximately 30% of employees with access to a 401k plan in the private sector did not participate (Topoleski & Myers, 2021). In addition, they found that 20 percent of the employees who did participate failed to take full advantage of the 401k plans (Schatz, 2020). Schatz (2020) derived some of the reasons why participants did not enroll or take full advantage of their plans. Such reasons were identified as ignorance of the benefits and tax advantages of a 401k plan, priorities in building emergency savings versus investing for retirement, and inertia, which pertains to employees being auto enrolled into a plan with the minimal amount being contributed. These last items were viewed as employees taking a passive approach to their retirement and never considering that a higher contribution might allow them to reach their retirement goals sooner than originally expected (Schatz, 2020)

Further supporting the information culled by Schatz (2020), a survey conducted by the Pew Charitable Trust found that 45% of employees in the private sector participated in their 401k plan versus 55% that did not (Sunagel, 2018). Moreover, it was found that for households with income over $100,000, there was a higher participation rate compared to those who fell under that threshold (Sunagel, 2018). Additionally, Sunagel (2018) found that auto-participation is used less by small- to medium-sized firms in the private sector. The reason for this was that these firms felt that their employees would not like the opt-out approach. However, research has shown that this is not the case (Sunagel, 2018).

As the older generation moves closer to retirement and the younger generation enters their initial years of retirement planning, how does minority status, household income, age, gender, and education associate with one’s participation in an employer-sponsored retirement plan? Do non-minorities participate more in their 401k plans than others? Are there differences in socioeconomic, age, gender, and academic backgrounds among the groups? In this article, we explore the differences in these areas and how they are associated with participation in employer-sponsored retirement plans.

Using Financial Advisors

As the average lifespan of an individual increases, planning for retirement can be viewed as a more specialized approach than just retiring at 65 years of age and living off one’s investments (Hicks, 2021). Outside of participating in employer-sponsored plans, some consumers opt to work with financial advisors. This provides individuals with a holistic approach that covers all areas of financial planning, including but not limited to investments, retirement, insurance, estate and tax planning, and possibly long-term care (Hicks, 2021). However, some consumers view the use of a financial advisor as a service only available to the wealthy (Delfino, 2021). Even though the percentage of individuals who do not use an advisor for planning is declining, those individuals who choose not to use an advisor or participate in their employer plans continue to decrease their chances of obtaining sufficient funding for their retirement needs (McKenna, 2020).

Financial Planning And Minorities

Ethnic background (or minority status) can be seen as a barrier to retirement planning. Tyler (2012) published an article related to a small company in Colorado with 100 employees, 40 of whom were Spanish speakers. However, the company did not realize that language alone was a barrier to entry for these 40 employees. When information was provided to them, they were unable to interpret the information properly to make informed decisions. However, after inviting bilingual presenters to present information to their employees, the company was able to increase participation by 28% (Tyler, 2012). The results illustrate that proper education of the benefits of using an employer-sponsored retirement plan can result in an increase in participation within minority groups. However, access to an employer-sponsored plan can be problematic for minorities. Hence, the AARP Public Policy Institute noted that black, Asian, and Hispanic employees (minorities) have less access to employer-sponsored employees than white (non-minority) employees (Harvey, 2017). More specifically, when analyzing the ethnic group independently, 50% of blacks, 48% of Asians, and 34% of Hispanics are covered under an employer-sponsored plan versus 57% of whites.

Retirement Planning And Gender

When assessing the differences between men and women in retirement plan participation, a study conducted by Vanguard produced interesting findings. The study found that women are more likely to participate in retirement plans than men. In addition, women tend to save more into their employersponsored plans than men. However, the study also found that men tended to have higher account balances because their salaries were higher than their female colleagues (Nelson, 2021).

Retirement Planning And Age

When planning retirement, previous research has shown that patience is a key element in achieving this goal. Clark et al. (2019) found that individuals who are patient and take time to understand the timelines associated with retirement planning are more likely to achieve their financial goals. In addition, those who are more patient tend to save more in and outside their retirement plans (Clark et al., 2019). In a recent study published in the Journal of Economic Behavior and Organization, Burro et al. (2022) found that having patience is based on whether an individual is rich or poor. Hence, the more financially secure an individual is, the more patience they possess (Burro et al., 2022). Furthermore, it was found that age is positively related to the level of contributions when planning for retirement. Jiménez et al. (2019) found that as individuals become older, their disposable income increases. They are more likely to plan better and contribute more to their investments. Although inconclusive, age appears to be an important contributor to the retirement planning process.

Financial Planning And Education Level

Previous research has shown a positive association between educational level and retirement planning. Transamerica Institute (2016) surveyed over 4,000 workers and found that as educational attainment increased, so did the participation rates in retirement plans. In addition, there is a strong association between financial literacy (an understanding of basic financial terminology) and the level of planning for retirement. Additionally, Michelson and Schwartz (2018) examined academic faculty and their perception and ability to plan for retirement. The faculty were chosen because, in most cases, their educational and income levels were higher than the average individual. In addition, the faculty actively saved more for retirement than the average employee. However, the faculty’s ability to save the correct amount still may not have been sufficient for retirement. This is yet another important item to note; saving for retirement is only a part of the process. It is important to save a sufficient amount of money for retirement, regardless of one’s education.

Finra Based Research

Previous research, funded by the FINRA Foundation, utilized the 2018 National Financial Capability Study (NFCS) dataset with various findings. In October 2019, researchers established that investors (primarily women) who only invested through their employer-based retirement programs were less likely to be able to manage their investments. This contrasts with investors who have investment accounts outside their employer-sponsored plans (Fisch et al., 2019). Another study compared investor knowledge between men and women. It was found that 40% of the women culled from the 2018 NFCS study, were deemed to have low investment knowledge, compared to 8% who were viewed as possessing high investment knowledge (Global Financial Literacy Excellence Center & FINRA Foundation, 2020). Finally, another study conducted in 2019 provided updates to previous research on the financial well-being of veterans. Findings from this study state that veterans continue to struggle with credit card behavior but fare better overall in relation to managing other aspects of their personal finances (Mottola & Skimmyhorn, 2019). In addition, female veterans appear to manage their finances less than their peers, and black veterans appear to manage their finances better than their counterparts who identify as either white or “Other” relative to race/ethnicity (Mottola & Skimmyhorn, 2019). As evidenced by the FINRA Foundation-sponsored projects, NFCS data can be used to analyze various financial behavior patterns.

This study aims to assist practitioners and small-to-medium sized businesses (SMB). In doing so, the researchers aim to inform practitioners and SMBs about understanding associations tied to participation rates as they relate to minority group, age, household income, educational level, and gender.

This study does not intend to determine whether auto enrollment or opting into an employer-sponsored plan is effective. Furthermore, for the purposes of this study, nonminorities are categorized as white and non-Hispanic. All other ethnic groups are categorized as minorities.

Method

Based on previous research, ethnicity was found to be negatively correlated with participation in a retirement plan. In addition, age, education, and household income were all positively correlated with participation in a retirement plan. Previous surveys found that although women accumulated less in their retirement accounts than men, women were more likely to participate in their employer-sponsored retirement plans than men. As a result, the following research question was created for this study:

Research Question Do minority group, age, household income, gender, and education contribute to the participation in employer-sponsored retirement plans?

In conjunction with the abovementioned research questions, the following hypotheses were developed to address this question:

H1: Minority group is negatively associated with participation in employer-sponsored retirement plans.

H2: Household income is positively associated with participation in employer-sponsored retirement plans.

H3: Age is positively associated with participation in employer-sponsored retirement plans.

H4: Education is positively associated with participation in employer-sponsored retirement plans.

H5: Gender is positively associated with participation in employer-sponsored retirement plans.

To answer the research question and test the hypotheses, this analysis was performed based on secondary data analysis on a large dataset representative of the population in the United States.

Research Design

Frequency distributions, descriptive statistics, and binary logistic regression were used to analyze the dataset used in this study. For all pertinent survey questions culled from the dataset, those that contained unanswered or unknown responses were removed from the final dataset to provide researchers with data that were clear and concise when testing the hypotheses.

When testing the hypotheses within this study, a binary logistic regression analysis was conducted. This methodology was chosen because the dependent variable (participation in an employer-sponsored retirement plan) is dichotomous and can be tested against variables of various data types.

Population And Sample

This study utilized data from the 2018 NFCS. This survey consisted of approximately 27,091 adults aged 18 years or older who participated online. The NFCS estimates that, when including all states within the United States (including the District of Columbia), there is a representation of approximately 500 respondents per state. Participants in this study were offered incentives to participate (FINRA, 2018).

Data Collection

NFCS data were collected using non-probability quota sampling. This was done online with millions of potential participants solicited to participate in the study (FINRA, 2018). To verify the identification and demographic characteristics of the participants, the survey used Survey Sampling International (SSI), EMI Online Research Solutions, and Research Now as providers of sampling solutions for the study (FINRA, 2018). Overall, the dataset has an estimated margin of error of .05 (half a percent). It should also be noted that the data collection within the 2018 study replicates the 2009, 2012, and 2015 data in that it did not specifically target any specific household, for example, the head of household or the primary decision maker within a household (FINRA, 2018).

Analysis

An associational design was used to understand the relationships between the variables in this study. Each independent variable was derived from the 2018 NFCS study (see Appendix). These survey questions were non-overlapping and directly related to the independent variables. All analyses were conducted using IBM® SPSS.

Frequencies And Distributions

A data analysis was performed to understand the distribution of the data. Frequencies were performed on the predictor variable, retirement plan, and the independent variables gender, age, minority group, education, and household income.

Table 1 illustrates that the age groups appeared to be somewhat evenly distributed among the age brackets, with 18–24 representing the lowest, 2,388 (9.4%) and 65+ representing the highest, 5,361 (21.0%). When reviewing level of education, the frequencies revealed that more than half of the respondents did not have a college degree: 6,822 (53.8%) and 619 (2.4%) had no high school education. 5,619 (22.0%) had a bachelor’s degree while 6,152 (24.1%) had either an associate or a postgraduate degree. Household income levels

Table 1. Frequency Distributions

show that for those households earning more than $50,000, 13,811 (54.2%), 4,990 (19.6%) earn between $50,000 and $75,000 while 1,793 (7.0%) earned $150,000 or more. Finally, retirement plan participation illustrates that of the 25,490 respondents, 10,069 (39.5%) did not have a plan and 15,421 (60.5%) did have an employer-sponsored retirement plan.

Results

A binomial logistic regression model was used to test the hypotheses and the associations between the independent and dependent variables. The model correctly predicted nearly 76% of the cases with an R2 of .355 using the Nagelkerke measurement and had a significant association between the independent variables and employer-sponsored retirement plans (χ2(df = 5, N = 25,490) = 7744.51, p < .001). The unstandardized beta weight for the constant was B = -2.917, SE = 0.97, Wald = 909.828, p < .001.

The independent variables in the binomial logistic regression analysis were examined. The age group was found to positively contribute to the model. The unstandardized Beta weight for age groups was B = .051, Wald = 28.846, p < .001. In the model, every one-unit increase in the range of the age group would make it 1.05 times as likely that the respondent will participate

Table 2. Results of Binomial Logistic Regression

in an employer-sponsored retirement plan. Education level was also found to positively contribute to the model. The unstandardized Beta weight for educational level was B = .169, Wald = 221.829, p < .001. In the model, every one-unit increase in an individual’s level of education would make it 1.18 times as likely that the respondent would participate in an employersponsored retirement plan. Household income levels also contributed positively to the model. The unstandardized Beta weight for the household income level was B = .588, Wald = 4208.919, and p < .001. In the model, every one-unit increase in the range of household income level makes the odds 1.80 times as likely that the respondent will participate in an employer-sponsored retirement plan. Lastly, gender (p = .400) and minority groups (p = .518) did not appear to be significant contributors in predicting the likelihood of a consumer having an employer-sponsored retirement plan (see Table 2).

Note. Dependent variable is retirement plan.

Note. *Significant at the 0.05 level ** significant at the .01 level.