It would be so much easier for us to win the Retirement Game and determine how much we could afford to spend each year in retirement if we just knew up front how long we would live and what future returns on our invested assets would be. Unfortunately, most of us don’t know these things, and, in many cases, they are unknowable. So, we have to make best-estimate assumptions about the future and adjust when our assumptions prove to be inaccurate.
We generally invest some portion of our assets in risky investments (equities) because we expect to earn a higher rate of return on these investments. However, as discussed in our post of February 21, 2018, there are no guarantees that expected returns on risky assets will be realized. Even over long-periods of time, the actual returns on risky assets can be much higher than we expect, or they can be much lower than we expect.
Our inability to predict the future, however, hasn’t stopped individuals from coming up with approaches that they believe can “safely” be used to spend down retirement savings which are significantly invested in risky assets. The 4% Rule is a classic example of such an approach. Our readers know that we are not big fans of the 4% Rule, or any other “static” safe withdrawal rate (SWR) approach. In his 2008 paper, “The 4% Rule—At What Price?”, Nobel Laureate William Sharpe and his co-authors said about the 4% Rule, “Supporting a constant spending plan using a volatile investment policy is fundamentally flawed.”
We favor dynamic approaches that require periodic (typically annual) “actuarial valuations” to keep spending on track and consistent with a retiree’s spending goals. We acknowledge that, under a dynamic approach, returns on risky assets will fluctuate from year to year and these fluctuations may increase or decrease how much we can afford to spend.
In his February 20, 2019 post, “The Extraordinary Upside Potential Of Sequence Of Return Risk In Retirement,” Michael Kitces does a little bit of complaining about the 4% Rule. According to Mr. Kitces, because of the way it was designed, the 4% Rule has this bad habit of leaving too much money on the table at the end of the Retirement Game. He believes that it is generally too safe, but points to the paucity of alternative software solutions. Michael states:
“So what’s the alternative? To plan, in advance, for retirement spending strategies to be more dynamic…at minimum, to have a ratcheting plan in place to lift a low initial spending rate higher if the sequence is favorable (or at least, is not unfavorable), and for those who are willing to be more flexible in their retirement spending, to set guardrails in advance to know both when to cut spending in a bad sequence, and when to lift it higher in a more favorable one.
Unfortunately, modern retirement planning software is very limited in its ability to model such dynamic spending strategies, with only a few recent solutions emerging that can help to illustrate the benefits of planning in advance for making at least some mid-course spending adjustments.”
Unfortunately, modern retirement planning software is very limited in its ability to model such dynamic spending strategies, with only a few recent solutions emerging that can help to illustrate the benefits of planning in advance for making at least some mid-course spending adjustments.”
We thank Mr. Kitces for teeing this one up for us. We believe employing the Smoothed Actuarial Budget Benchmark (Smoothed ABB) discussed in our post of November 6, 2018 is just the dynamic planning process he is looking for, and he should be checking out our Actuarial Budget Calculator software.
The Smoothed ABB:
- Employs an annual actuarial valuation process to automatically adjust spending to reflect emergence of bad sequences and good sequences of returns.
- It also incorporates a smoothing algorithm that mitigates year-to-year spending fluctuations.
- And because it employs assumptions consistent with inflation-adjusted annuities to value spending liabilities, it tends to “err on the conservative side” by increasing spending resulting from those higher expected returns on risky assets as they realized—and not before.