Jack VanDerhei

Social Security investment accounts: lessons from participant-directed 401(k) data

Abstract Newly available 401(k) participant investment data may have implications for individual Social Security account (IA) proposals. We found that women with wages between

How Would Target-Date Funds Likely Impact Future 401(K) Accumulations?

25,000 and

Why Does Retirement Readiness Vary:Results from EBRI’s 2014 RetirementSecurity Projection Model®

50,000 have a significantly greater probability of investing a small percentage of their 401(k) in equities than their male counterparts, but those with salaries over

The Impact of Leakages on 401(K) Accumulations at Retirement Age

75,000 have a smaller probability. Hence, women’s less aggressive investment behavior may be primarily due to younger cohorts and may not apply above a threshold wage. However, overall, 28.4% of men and 33.8% of women are conservative investors, suggesting the possible risk low IA accumulations under some proposals.

Retirement Savings Shortfalls

As part of EBRI’s 2008 analysis of the likely impact of the Pension Protection Act’s safe harbor automatic enrollment and automatic escalation provisions, we developed a stochastic simulation model to project future 401(k) balances as a function of various plan design variables as well as assumptions with respect to various employee behavioral responses. In this paper I report on the results I obtained using the EBRI simulation model to determine how target-date funds (TDFs) would likely impact 401(k) participants assumed to be automatically enrolled. I realize that TDF use in 401(k) plans is not limited to those automatically enrolled; however, based on our simulation results, it appears that this 401(k) auto-enrollment will represent the majority of TDF use in the future and hence I will concentrate my analysis on those results. Results are reported both at the time of retirement as well as at the time of job change for those who are assumed to cash out. Several scenarios are presented in terms of alternative rates of return as well as several different types of target date funds.

Measuring Retirement Income Adequacy: Calculating Realistic Income Replacement Rates

In this article, the author describes and applies a model that finds that retirement income adequacy improved slightly in 2013. Because of increases in financial market and housing values, the probability that Baby Boomers and Generation Xers would not run short of money in retirement as measured by the EBRI Retirement Readiness Ratings (RRR), rose between 0.5 and 1.6 percentage points. Model simulations find that eligibility for participation in an employer-sponsored defined-contribution (DC) plan remains one of the most important factors for retirement income adequacy. Future Social Security benefits make a very large difference for the retirement income adequacy of some households, especially Gen Xers in the lowest-income quartile. In addition, longevity risk and stochastic health-care risk are associated with huge variations in retirement income adequacy. A great deal of the variability in retirement income adequacy could be mitigated by appropriate risk-management techniques. For example, the annuitization of part of DC plan and IRA balances may substantially increase the probability of not running short of money in retirement. Moreover, a well-functioning market in long-term care insurance could help control the volatility of long-term health care expenditures, especially for middle-income households.

Can America Afford Tomorrow's Retirees: Results from the EBRI-ERF Retirement Security Projection Model

The simulation results for this testimony suggest that, assuming no participant behavior change for participation, contribution or asset allocation resulting from reduced access to 401(k) balances, retirement balances from 401(k) plans, and IRA rollovers originating in 401(k) plans, may be increased substantially for young employees with thirty or more years of eligibility if cashouts at job turnover, hardship withdrawals (and the accompanying suspension of contributions) and plan loan defaults were substantially reduced or eliminated. However, this analysis needs to be accompanied by a very strong caveat that, prior to policy making, there are clear data gaps that will need to be filled. For example, Holden and VanDerhei (2001) found that participants in plans with a loan option have higher contribution rates than those without such access, cet. par. It is likely that a similar relationship exists with respect to the availability of hardship withdrawals. The potential reduction in participation and contribution rates from reducing or eliminating access to cashouts at job change would likely be even greater; however, since this is not a plan design variable that be controlled by the plan sponsor, there is no way to quantify the likely impact based on historical data.

The Impact of Auto-enrollment and Automatic Contribution Escalation on Retirement Income Adequacy

An article in the Spring 2014 issue of The Journal of Retirement focused on the probability that households will not run short of money in retirement. This article expands the earlier analysis by analyzing the size of the deficits that retired households are simulated to incur. These retirement savings shortfalls (RSSs) are reported by age cohorts, marital status, gender, and years of future eligibility for defined contribution plan participation. The results demonstrate the extreme importance of longevity risk and nursing home and home health care costs in simulating RSSs. Analysis of the potential of a generic auto-IRA proposal to decrease retirement deficits is also included. The baseline aggregate national retirement deficit number is estimated to be

The EBRI Retirement Readiness Rating:™ Retirement Income Preparation and Future Prospects

4.13 trillion for all U.S. households whose heads are between ages 25 and 64, inclusive. This value decreases to

Defined Benefit Plan Freezes: Who's Affected, How Much, and Replacing Lost Accruals

3.86 trillion with auto-IRAs and no opt outs.