T. Rowe Price's Glide-Path Design Framework

Glide‑path design happens at the intersection of financial and behavioral economics. This is because retirement outcomes depend not only on investment returns, but also on the saving and spending behaviors and attitudes of investors. Therefore, an effective approach to life‑cycle investing must rely on a deep understanding of markets and investor behavior, including how both factors evolve and interact over extended time horizons and a wide range of market and economic cycles.

In order to properly assess the impact and interaction of these elements, T. Rowe Price employs a structural model for glide‑path design and evaluation. The primary benefit of our model is the consistency of our approach.

We recognize that while individuals may be skillful at using intuition and judgment to solve complex problems, they may not be as effective at applying these skills consistently or on a broad scale. By contrast, our structural model allows us to apply our insights consistently across the range of glide‑path problems that we seek to solve.

Our evaluation framework is based on a utility model that incorporates key variables of glide‑path design and provides a consistent mechanism for assessing different potential outcomes based on varying assumptions about plan sponsor and participant preferences and objectives.

Key Design Factors

The first step in understanding how we apply our framework is to understand the primary factors that can influence glide‑path design.

There are three categories of relevant factors (Figure 1). Capital markets and demographics are assumptions about asset class returns and the funded status of the investors for whom the glide path is being designed. Behavioral preferences capture biases and goals pertaining to risk, avoiding wealth depletion, time horizon, and consumption.

• Capital markets: These are assumptions about expected future asset class returns, which are informed by economic variables such as growth, inflation, and interest rates.
• Demographics: Demographic assumptions are crucial to modeling projected investor cash flows, such as income, savings, and expenditures. Our model includes variables such as earnings (which are dependent on career progression and the state of the economy), income‑dependent savings rates, employer‑match formulas, and expected Social Security benefits, as well as mortality rates and behaviorally representative patterns of retirement spending.
• Behavioral preferences: Behavioral preferences determine how investors rank and compare investment decisions and outcomes. These preferences reflect investors’ attitudes toward uncertainty, wealth depletion, and the timing of consumption.

Modeling behavioral preferences allows us to intuitively capture investors’ unique tastes, construct objective criteria, and apply a consistent investment evaluation process across a variety of retirement goals and expectations. Our framework focuses on two categories of behavioral preferences: innate preferences and objective preferences.

Innate Preferences

Innate preferences are those ingrained for a chosen individual, which cannot be easily changed and are not objectives to be set. In our model, we assume two innate preferences: the degree of risk aversion and the degree of wealth depletion aversion.

• Risk aversion describes an individual’s willingness to trade a level of expected consumption for its greater certainty. More risk‑averse investors typically are willing to forgo some potential income in exchange for a higher likelihood of attaining a more modest income goal.
• Wealth depletion aversion captures an individual’s willingness to forgo current consumption in order to try to maintain their current wealth. This inclination to try to preserve wealth is not entirely driven by the need to fund future consumption. Rather, greater wealth is its own distinct source of satisfaction in our model.

Academic research suggests that investors’ risk aversion is inherent and does not change over their lifetimes. Given the challenges in correctly eliciting risk aversion preferences¹ and our goal of representing diverse participant populations,² we model risk aversion not as an oversimplifying single parameter but as a distribution of potential values. This allows us to consider a range of potential investor preferences in our decision‑making process.

Aversion to wealth depletion is the other key innate preference parameter in our framework. An investor with no aversion to wealth depletion and a known retirement horizon typically would be expected to consume all their wealth over their lifetime. However, empirical research has shown that many retirees decumulate assets slowly, if at all.³ Potential explanations for such behavior are worries about longevity risk, a desire to self‑insure against possible medical and long‑term care expenses, a bequest motive, or a general difficulty in transitioning to “decumulation mode.”

The depletion aversion parameter explicitly characterizes this observed penchant for liquidity. Furthermore, it seeks to prevent the hypothetical participants in our model from “blindly running into a brick wall” and depleting all their wealth, which can happen under naive spending rules.

Risk aversion significantly influences the level and shape of the designed glide path. Unsurprisingly, higher risk aversion tends to cause the glide path to shift downward—i.e., the desired equity allocation tends to decline (Figure 2).

Greater depletion aversion tends to lead to less aggressive decumulation of wealth through retirement. Because it lowers postretirement spending levels and, thus, raises the funded status, a greater wealth depletion aversion also can result in a relatively lower equity glide path, all other things being equal.