Effect of Race on Married Women s Retirement Planning

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Department of Economics, Andrew Young School of Policy Studies, Georgia State University, P.O. Box 3992, Atlanta, GA 30302-3992; E-mail: kandam1@gsu.edu; pferraro@gsu.edu; 404-651-1372

Effect of Race on Married Women’s Retirement Planning

Kwaw S. Andam Paul J. Ferraro

In response to an aging population, U.S. policymakers and businesses are increasingly calling for greater use of individually controlled, voluntary retirement accounts. The success of such

retirement accounts rests on the financial literacy of potential participants. Some data suggest variability in financial literacy along racial lines, which might lead to variability in participation along racial lines. We seek to detect evidence of such variability by analyzing the participation of married women in individual retirement accounts and employer-sponsored pension plans. Our analysis indicates that, holding other relevant factors constant, married black women have a substantially lower rate of participation in retirement saving than married white women. Our results suggest that a shift toward individual retirement saving may have differential impacts on subgroups of the U.S. population, a point that is often ignored in the recent debate over pension reform.




The number of retirees in the United States is projected to rise dramatically over the next decade. This rise is expected to have large effects on the sustainability of the Social Security system. In response, greater attention is being paid to private retirement saving and the promotion of “individually controlled, voluntary personal retirement accounts” (President's Commission to Strengthen Social Security, 2001). Pension systems have been shifting from defined benefit plans, which place most of the burden for action and investment on the employer, toward defined contribution plans, which place most of burden for action and investment on the employee. By 1999, workers were contributing more than employers to pension plans (U.S.

Department of Labor, 2004).1

However, the success of personal retirement accounts rests on the financial literacy of the potential participants. Concern has been raised by academics and policymakers that such literacy is not uniformly distributed in the American population (Economist, 2006). In particular, concern has been raised about financial literacy among minority groups. For example, according to Beck (1984), black men are less likely to receive training in personal retirement planning. A more recent survey commissioned by Operation HOPE, Inc. (Mandell, 2005) found that blacks have lower financial literacy compared with whites, and that these differences in financial literacy are not related to income levels. Given that blacks already tend to have lower retirement wealth than whites (DeViney & Solomon, 1995; Gregoire et al., 2003; Mitchell et al., 2000), could the shift to individually controlled accounts result in even lower economic security for minorities? The answer depends crucially on the relative participation of minorities in personal retirement plans.

In this paper, we determine if there are racial differences in the participation of married women in individual retirement accounts (IRAs) and employer-sponsored pension plans (ESPs).

We do not know of any research that has looked at this topic. We focus on black women because they are an especially vulnerable group. First, black women have to make up for the low retirement incomes of their spouses. Pienta (2003) shows that women must work longer when their spouses have lower retirement incomes, and black men are more likely to have low retirement income. Second, women make a larger contribution to the retirement wealth of black households than they do in white households (Honig, 2000). Finally, black women are more likely to be divorced at retirement than white women, and consequently are more likely to experience the poor retirement outcomes associated with divorce (DeViney & Solomon, 1995;

Gregoire et al., 2003). Thus, the participation of black women in personal retirement accounts warrants special consideration when forecasting the effects of changes in U.S. pension policies.

While most previous research has compared retirement income for different races, little attention has been paid to racial differences in retirement planning. Studies of retirement planning behavior that include demographic attributes have tended to ignore race. For example, Kokrda and Cramer (1996) found that there are disparities in retirement saving levels among women with different work and family characteristics, but they did not include race as a variable in their analysis. The few studies that have included race in their analysis have found mixed

1 Similar shifts have taken place in Britain.



results. Dietz et al. (2003) found that women are generally less likely than men to use employer- sponsored plans, but did not find that race affects the likelihood of participation. Yuh et al.

(1998) found no race differences in retirement saving at the household level. In contrast, Mitchell et al. (2000) found that married black households were more likely to have projected shortfalls in retirement savings than married white households, although there was no such difference for the unmarried households in their sample. Thus the question of racial differences in retirement plan participation is important but unresolved.


To test for racial differences in the use of retirement plans, we examine the participation of married women in individual retirement accounts. We restrict our sample to married women for two reasons: (1) we do not wish to pool single and married women in one model because they may differ in unobservable characteristics that affect retirement plan participation and (2) the retirement plan decisions of married women is a particularly important social issue because of the high rate of divorce in the United States and the evidence that divorced women have much lower retirement income than divorced men (see Gregoire et al., 2003). Retirement accounts are not held jointly by the couple, but rather in the name of an individual. Although married women may view the funds in retirement accounts as joint income for retirement, divorce destroys the joint nature of these funds. A woman can claim a share of her husband’s accounts, but doing so requires substantial effort, an understanding of the value of these accounts, and legal expertise and a willingness to force the judicial system to consider the division of these funds (a divorce decree that includes a QDRO and transfer incident language related to retirement assets).2 Most investment advice texts for women encourage married women to avoid depending on their husband for retirement and to have their own accounts.

We use data on the retirement plan participation of married women ages 18-64 from the U.S. Census Bureau’s Survey of Income and Program Participation (SIPP). We construct a data set from the 1996-1999 SIPP panel. We eliminated 81 observations from the sample because of discrepancies in the household income reported by husbands and wives. In 141 cases, husbands’

responses to the household income question are used, because the women did not respond to the income question in the survey. Descriptive statistics on all variables are presented in Table 1.

We construct two models: (1) a Probit model that estimates the likelihood of a married woman having her own Individual Retirement Account (IRA) in 1997 and (2) a Probit model that estimates the likelihood of a married woman having her own Employer-Sponsored Pension Plan (ESP) in 1997. Note that before 1998, a nonworking spouse could make tax-deductible contributions up to $2000 to an IRA. Roth IRAs were not yet available. To test for differences in retirement saving of black and white married women, we create dummy variables for black women (Black) and for women of other non-white demographic groups (Other Race). We also estimated a recursive bivariate Probit model that portrays the decision to participate in an IRA

2 As noted in many investment books and websites for divorcing women, QDROs (Qualified Domestic Relations Order) take substantial expertise to execute in a manner that will ensure the wife receives an equitable share of the husband’s retirement accounts (and an “equitable” share as determined by the courts is not necessarily an “equal”

share). If not done correctly the transfer of retirement assets can be subject to taxes and early distribution penalties.



and an ESP as a simultaneous decision, but we cannot reject the null that there was no correlation of the errors across the models (chi2 = 0.001). Thus, we present the results from the two

univariate Probit models and note the conclusions are not altered in the context of a bivariate Probit model. Running the bivariate model does not change the coefficient on Black and the standard error is reduced, which strengthens our results.

Based on previous analyses of retirement plan participation (Clark et al., 2000; Even &

Macpherson, 1994; Hrung, 2004; Van Derhei & Copeland, 2001), we control for other relevant covariates: high school dropout (Dropout), college educated (College), age (Age), household income (Income), and the number of children under 18 in the household (Children). In the model of ESP participation, we also control for the size of the company (Large Firm, Medium Firm), the number of hours worked per week (Hours Worked), and job tenure (Job Tenure). Firms are categorized as Small if they employ less than 25 workers, Medium if they have between 25 and 99 workers, and Large if they employ more than 99 workers.In both models, we control for the length of marriage (Months) and, based on previous research, we add squared terms for age, income, and job tenure.

We also specify alternative models for IRA and ESP participation that include characteristics of the husband that could influence the woman’s decision to participate in retirement plans – whether the husband is a high school dropout (Husband-Dropout), college educated (Husband-College), has a job (Husband-Job), participates in an ESP (Husband-ESP), and participates in an IRA (Husband-IRA). We also examine whether the models could be improved by including interaction terms by Black, the rationale being that personal, family and work characteristics might affect the participation decision differently for blacks and whites. We do not include interaction terms in the final models, because none of the interaction terms are significant, and as a group, the interactions do not have a significant influence on participation in an IRA or an ESP.


Results are presented in Table 2. Both IRA and ESP models indicate that, controlling for other relevant factors, race has a statistically significant and economically substantial effect on the decision to participate in retirement savings plans. In the IRA models, the marginal effects of Black are negative and significantly different from zero. Married black women are less likely to participate in IRAs than married white women with similar income, education, age, and family characteristics (husband characteristics, length of marriage, and number of children). In the ESP models, the marginal effects of Black are again negative and significantly different from zero.

In both models, the effects of Black are substantial. When all non-racial covariates are held at median levels, a married white woman’s annual household income would have to decline by more than 47 percent from the median income level to have an effect on IRA participation close to that of being black. For ESP participation, a married white woman’s annual household income would have to decline by more than 20 percent from the median income level to have an effect close to that of being black. Note also that being black rather than white has an effect on plan participation that is comparable to the effects of dropping out of high school or having a



college education, which are consistently cited in the investment literature as two of the most important factors affecting investment behavior.

In Table 2, the signs of the marginal effects predicted by theory or previous empirical work are in parentheses adjacent to the variable label. Most of the marginal effects are significantly different from zero in all models and every sign is as predicted, except for Husband-Dropout and Husband-College in Model 2B (both of which are not statistically

different from zero). The conclusions are the same whether one computes marginal effects at the means, computes average marginal effects (the average of partial and discrete changes over the observations; i.e., the delta method) or if one simply examines the Probit model coefficients.


We find that married black women have a substantially lower rate of participation in retirement saving plans than married white women. More specifically, we find that holding an array of individual and household characteristics constant, black married women are

substantially less likely to participate in individual retirement accounts (IRAs) and employer- sponsored pension plans (ESPs). Our results are congruent with some previous findings that race influences retirement savings for married people (Mitchell et al., 2000). Yet they contrast with results in Yuh et al. (1998) and Dietz et al. (2003), which find no racial differences in retirement planning. However, Dietz et al. (2003) include unmarried individuals in their sample and do not distinguish blacks from other minorities, as we have done.3 If the signs and magnitudes of the coefficients of the other variables in our models were unusual, we might be concerned about our ability to draw conclusions about racial differences from our sample. However, our coefficients exhibit the predicted signs and relative magnitudes that have been identified in previous studies.

Before discussing the policy implications of our findings, we address some alternative explanations for our results. One possible reason for the lower participation of black women in retirement plans is that there are alternative investment options that black women use for retirement planning. While we control for income in both models, we are unable to control for other forms of saving such as home ownership. However, including home ownership in

particular would not likely change our overall results because black women are less likely than white women to own a home at retirement (Butrica & Iams, 2003). This logic would hold for most other alternative forms of retirement saving. Another alternative explanation for our results is that black women have a higher discount rate or are less risk-averse than white women,

holding other factors constant. While we know of no data that supports or rejects this conjecture, we know of no plausible reason why this would be the case. As described in the Introduction, a more satisfactory explanation for our results is that married black women have lower financial literacy than married white women. Although Dietz et al. (2003) find that financial literacy is unrelated to gender differences in retirement saving, racial disparities in financial knowledge may account for the racial differences in retirement saving that we detect in our study.

3 Combining all minorities into one dummy variable in our analysis substantially lowers the marginal effects in all models (25-50 percent) without substantially changing the standard errors, and renders the effect insignificantly different from zero in Model 2B at the 5 percent level (Dietz et al. use a 5 percent level cutoff).



Our findings have implications for retirement policy. It is widely assumed that workers will “increase their work effort and saving” (CBO, 2003, p. 5) to make up for reductions in Social Security benefits. However, our study suggests that responses to Social Security reform could vary among demographic groups, and therefore some groups could be substantially less prepared than others for the future. Of course, financial literacy and planning are endogenous to the status quo pension system and thus we cannot use our data to predict with certainty the investment behavior of married women under pension reform. Yet our results do highlight a potentially undesired effect of the trend toward personalized retirement savings: the gap in retirement income between white and black households could grow even wider. If policymakers were concerned about this potential effect, reforms that stress individually controlled accounts could be accompanied with targeted information campaigns to increase personal retirement saving among demographic groups with historically low participation rates.


Beck, S. H. (1984). Retirement Preparation Programs: Differentials in Opportunity and Use.

Journal of Gerontology 39(5): 596-602.

Butrica, B. A., & Iams, H. M. (2003). The Impact of Minority Group Status on the Projected Retirement Income of Divorced Women in the Baby Boom Cohort. Journal of Women and Aging 15(2/3): 67-88.

CBO. (2003). Baby Boomers' Retirement Prospects: An Overview. Washington, D.C.: CBO.

Clark, R. L., Goodfellow, G. P., Schieber, S., & Warwick, D. (2000). Making the Most of 401(k) Plans: Who's Choosing What and Why? In O. S. Mitchell & P. B. Hammond & A. M.

Rappaport (Eds.), Forecasting Retirement Needs and Retirement Wealth (pp. 95-183).

Philadelphia: University of Pennsylvania Press.

DeViney, S., & Solomon, J. C. (1995). Gender Differences in Retirement Income: A Comparison of Theoretical Explanations. Journal of Women and Aging 7(4): 83-100.

Dietz, B. E., Carrozza, M., & Ritchey, P. N. (2003). Does Financial Self-Efficacy Explain

Gender Differences in Retirement Saving Strategies? Journal of Women and Aging 15(4):


Economist, The. (2006). Caveat investor. The Economist 378(8460): 71-72.

Even, W. E., & Macpherson, D. A. (1994). Employer Size and Compensation: the role of worker characteristics. Applied Economics 26(9): 897-907.

Gregoire, T. K., Kilty, K., & Richardson, V. (2003). Gender and Racial Inequities in Retirement Resources. Journal of Women and Aging 14(3/4): 25-39.

Honig, M. (2000). Minorities Face Retirement: Worklife Disparities Repeated? In O. S. Mitchell

& P. B. Hammond & A. M. Rappaport (Eds.), Forecasting retirement needs and retirement wealth (pp. 235-252). Philadelphia: University of Pennsylvania Press.

Hrung, W. B. (2004). Information, the Introduction of Roths, and IRA Participation.

Contributions to Economic Analysis and Policy 3(1): Article 6:1-17.

Kokrda, E., & Cramer, S. (1996). Factors Affecting Retirement Savings of Women in the 50s Age Cohort. Journal of Women and Aging 8(1): 33-44.

Mandell, L. (2005). The state of financial literacy of young African-American adults in America (pp. 1-25): Operation HOPE.



Mitchell, O. S., Moore, J. F., & Phillips, J. W. (2000). Explaining Retirement Saving Shortfalls.

In O. S. Mitchell & P. B. Hammond & A. M. Rappaport (Eds.), Forecasting Retirement Needs and Retirement Wealth (pp. 139-163). Philadelphia: University of Pennsylvania Press.

Pienta, A. M. (2003). Partners in Marriage: An Analysis of Husbands' and Wives' Retirement Behavior. The Journal of Applied Gerontology 22(3): 340-358.

President's Commission to Strengthen Social Security. (2001). Charter. Retrieved July 10, 2005, from the World Wide Web: http://www.csss.gov/

U.S. Department of Labor, (2004). Private Pension Plan Bulletin: Abstract of 1999 Form 5500 Annual Reports (Number 12). Employee Benefits Security Administration, Washington, D.C.

Van Derhei, J., & Copeland, C. (2001). A Behavioral Model for Predicting Employee

Contributions to 401(k) Plans: Preliminary Results. North American Actuarial Journal 5(1): 80-94.

Yuh, Y., Montalto, C., P., & Hanna, S. (1998). Are Americans Prepared for Retirement?

Financial Counseling and Planning 9(1): 1-13.


7 Table 1. Descriptive Statistics

Variable Range Mean Standard Deviation

Individual Retirement Account (IRA) Participation

0-1 0.217 0.412 Employer-Sponsored Pension Plan (ESP)


0-1 0.384 0.486

Black 0-1 0.055 0.228

Other Race 0-1 0.041 0.198

Age 18-64 39.966 10.465

Length of Marriage (Months) 1-564 180.980 135.537 Number of Children under 18 in home 0-10 1.167 1.221

High School Dropout 0-1 0.098 0.298

College Educated 0-1 0.271 0.444

Income in thousands of dollars 1.1-150 49.228 21.967

Firm Size (Large=1) 0-1 0.566 0.496

Firm Size (Medium=1) 0-1 0.036 0.187

Job Tenure in months 0-432 62.417 83.294

Hours Worked per week 0-99 24.689 19.054

Husband is High School Dropout 0-1 0.110 0.313

Husband is College Educated 0-1 0.295 0.456

Husband has a Paid Job 0-1 0.922 0.268

Husband has an ESP 0-1 0.561 0.496

Husband has an IRA 0-1 0.258 0.437

Notes: “Other Race” includes all other non-white individuals. Reference group for race variables is white. Reference group for firm size variables is Small.



Table 2. Married women’s retirement plan participation – Marginal effects from Probit Individual Retirement Account

(IRA) Participation

Employer-sponsored Pension Plan (ESP) Participation Covariates

(Predicted Sign)

Model 1A Model 1B Model 2A Model 2B Black (-) -0.122***







(0.031) Other Race (-) -0.017


-0.001 (0.026)

-0.017 (0.041)

-0.022 (0.041)

Age (+) 0.009**




0.010 (0.007)

0.009 (0.008)

Age2 (-) -2.3 x 10-5

(5.0 x 105)

-7.4 x 10-5 (5.0 x 10-5)

-1.4 x 10-4 (9.0 x 10-5)

-1.3 x 10-4 (1.0 x 10-4) Length of Marriage (?) 1.1 x 10-4*

(6.0 x 10-5)

4.3 x 10-5 (6.0 x 10-5)

1.0 x 10-4 (1.1 x 10-4)

9.2 x 10-5 (1.2 x 10-4) Children (-) -0.021***




-0.011 (0.008)

-0.012 (0.009) Dropout (-) -0.140***







(0.035) College (+) 0.123***







(0.026) Income (+) 0.006***







(0.002) Income2 (-) -2.8 x 10-5***

(1.0 x 10-5)

-2.9 x 10-5***

(1.0 x 10-5)

-2.1 x 10-5 (2.0 x 10-5)

-2.8 x 10-5* (2.0 x 10-5)

Husband-Dropout (-) -0.049***


0.008 (0.036)

Husband-College (+) 0.013


-0.021 (0.023)

Husband-Job (-) -0.034


-0.040 (0.047)

Husband-ESP (?) -0.021*




Husband-IRA (?) 0.403***


0.029 (0.023)

Large Firm (+) 0.306***




Medium Firm (+) 0.210***




Job Tenure (+) 0.004***

(3.3 x 10-4)


(3.4 x 10-4)

Job Tenure2 (-) -8.5 x 10-6


-9.0 x 10-6***


Hours Worked (+) 0.011***




McKelvey and Zavoina's R2 0.324 0.462 0.771 0.774 Wald Chi2 763.27*** 1492.17*** 1054.27*** 1002.38***

Sample size 5833 5461 4055 3794

Notes: *, **, and *** indicate significance at 10%, 5%, and 1% respectively. Marginal effects for dummy variables are for discrete changes from 0 to 1. Standard errors are in parentheses.




Related subjects : Number of ever-married women