30 November 2020 / INVESTMENT INSIGHTS
Beyond Averages: A More Robust Approach to Glide-Path Design
Key Inputs Should Reflect Diversity of DC Plan Populations.
- T. Rowe Price believes that failing to account for the heterogeneity of defined contribution participant populations in glide‑path design may lead to poor retirement outcomes.
- Many target date providers use simple averages to represent key participant characteristics and behavioral preferences in their glide‑path models.
- By using distributions of values within plan populations instead of averages, T. Rowe Price seeks to produce more robust target date offerings for all participants.
Many target date providers use averages as the primary population inputs when designing glide paths for defined contribution (DC) plans. We believe this method is not effective given that target date strategies are designed to be used by broad, diverse populations. These populations are not homogeneous—just the opposite, in fact. Plan participants may exhibit a variety of demographic characteristics and differing investment preferences.
We believe that not accounting for the heterogeneous nature of DC participants when designing and implementing target date glide paths ultimately may lead to retirement outcomes that fall wide of the mark for many plan participants.
Our research and insights into DC populations and participant behaviors suggest that glide‑path models that use distributions of the key participant characteristics as design inputs instead of simple averages potentially can do a better job of capturing the diversity of participant characteristics within DC plan populations.
In solutions customized at the participant level, such as managed accounts, the problem of heterogeneity is avoided entirely, as glide paths can be designed based on each participant’s specific circumstances, objectives, and preferences. However, use of managed accounts as the default option is neither typical nor necessarily desirable among DC plans due to a number of potential downsides, including potentially higher costs and the need for participants to engage and provide personalized inputs in order for the benefits to be achieved.
At T. Rowe Price, our glide‑path work draws on our recordkeeping database of over 2 million DC plan participants. Based on aggregate, depersonalized data from this source, we have developed inputs that reflect the key demographic attributes and behavioral preferences of a real‑world universe of actual plan participants. In our view, this approach represents a more practical, lower‑cost alternative to individually customized solutions while avoiding the inherent limitations of a design methodology based on simple averages.
The role of asset accumulation within DC plans as a critical lever in retirement planning emphasizes how important it is for plan sponsors and their investment advisors to understand the implications of different target date design approaches. In our view, plan sponsors would be well served by selecting target date strategies with glide paths that are based on realistic assumptions about participant demographics and preferences and, thus, seek to improve retirement outcomes for the entire plan population.
The Importance of Preferences
There are a number of factors that need to be taken into account when designing target date glide paths for DC plans. A sound methodology for modeling the expected demographic characteristics (such as earnings levels and contribution rates) of participant populations is obviously critical.
However, T. Rowe Price also believes that glide‑path providers should seek to understand and model a range of investment preferences, such as tolerance for risk and the relative importance placed on potentially conflicting objectives (for example, how the goal of consumption replacement during retirement is prioritized relative to the goal of mitigating balance variability at or near retirement).
By including these preferences as inputs in our design models along with key participant demographic characteristics, T. Rowe Price seeks to offer glide paths that are more robust and have the potential to improve retirement outcomes across diverse plan populations.
Designing Glide Paths for Diverse Populations
Target date strategies provide DC plan participants with appropriately diversified portfolios designed to pursue long‑term retirement investment objectives. By moving along preset glide paths, target date asset allocations can reflect the evolving needs and risk tolerances of participants as they pass through the accumulation phase of their investment life cycle and into retirement.
However, DC plan populations inevitably include a range of individuals with differing demographic characteristics—such as age, current and expected earnings, and savings behavior—and risk preferences. Yet, many investment providers seek to design their glide paths based on inputs that reflect a single “average” participant.
With this as the backdrop, consider the mathematical definition of “average”—the result obtained by adding multiple quantities together and then dividing the total by the number of quantities. While simple averages are easy to understand and likely adequate for many uses, we believe using them as inputs in the glide‑path design is a vast oversimplification.
Given the impact that glide‑path design can have on long‑term retirement outcomes, we believe the use of oversimplifying assumptions can create significant downside risks for plan sponsors and participants.
We can illustrate these risks by taking a closer look at two key participant demographic inputs that are integral to glide‑path modeling:
- expected earnings levels
- savings behavior
Each of these inputs has substantial influence in glide‑path design—in particular, in setting the appropriate allocation between equity and fixed income assets at any given point on the path, both before and after retirement.
However, the ranges of salaries and contribution rates within a DC plan population may be quite wide. A design methodology based on simple averages may result in suboptimal asset allocations and retirement outcomes for a significant number of participants.
Take, for example, the hypothetical income groups in Figure 1, which displays both their plan participation rates and their projected income replacement from Social Security. The lower‑income cohorts (such as the participants in the second quintile) have less discretionary income and, thus, may not be able to save as large a share of their earnings as the middle‑ and higher‑income cohorts. The lower‑income groups are likely to need more growth from their DC plan accounts to mitigate their relatively low saving rates and close the gap between their expected Social Security benefits and their consumption needs in retirement.
(Fig. 1) Lower and Higher Income Groups Are Both Likely to Need More Portfolio Growth
Social Security Replacement1 and Retirement Plan Access by Income2
As of April 2019
Our model for glide‑path design has evolved to emphasize the role of nondiscretionary consumption in the spending model in a systematic manner. Recognizing that the share of total expenses dedicated to discretionary spending tends to be lower for lower‑earning participants, we tie this observation to a preference for avoiding balance depletion that is a feature of our behavioral spending model.1 Namely, lower income reflects a lower share of discretionary spending and, thus, a lower preference for avoiding depleting assets. Likewise, higher income reflects a larger share of income devoted to discretionary spending, greater ability to save, and a reduced focus on immediate consumption—resulting in a higher preference for avoiding the depletion of assets.
Next, consider a participant who falls somewhere in the middle of the earnings distribution (in the fourth quintile in Figure 1, for example) but also has a relatively low savings rate. This individual is likely to experience an even larger shortfall in his or her ability to cover consumption needs in retirement because Social Security benefits will close less of the gap. This example illustrates the potential pitfalls in relying on simple averages when seeking to design optimal glide paths, which may miss the mark in terms of serving the entire plan population well.
Longevity Risk Is an Increasingly Critical Design Factor
Savers face many risks throughout the course of financially preparing for retirement. These may include market risks (such as price volatility and the erosion of real portfolio values by inflation) as well as behavioral risks (such as insufficient savings or failed attempts to time the market). We believe that longevity risk—a shortfall of funds during retirement—has become one of the most important risks that must be addressed in retirement planning.
Americans now are living longer, which means a career’s worth of savings might need to fund a retirement lasting many decades. For example, recent actuarial estimates indicated that for a hypothetical male‑female couple, both 65 years old, at least one member had an 80% probability of living to age 85, or another two decades, a 60% probability of living to age 90, or two and a half decades, and a nearly 33% chance of living to 95—three full decades of retirement (Figure 2).
Our modeling approach reflects these considerations by thinking of glide‑path optimization as a planning problem. Namely, we allow each individual to have a specific retirement planning horizon, which is tied to a timing preference in our behavioral spending model. The mortality discount that we apply to each time period scenario in our analysis is conditional on an individual living until their specific plan horizon, rather than simply living until retirement age. In practice, we calibrate these planning horizons to the preferences of plan sponsors, allowing us to incorporate sponsors’ views into our glide‑path design in a systematic manner.
(Fig. 2) Today’s DC Plan Participants Can Expect Lengthy Retirements
Actuarial Estimates of Expected Survival Rates at Age 651
Sources: DrinkerBiddle, BNY Mellon, Cannex Financial Exchange, and Society of Actuaries.
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