# Should You Stop Believing in a ‘Safe' Withdrawal Rate for Retirement? Even the 4% Rule Presents Risk

Is the idea of the “safe” withdrawal rate nothing more than the Tooth Fairy of the retirement planning industry – mere fiction?

Some financial experts are calling the methods used to calculate safe withdrawal rates, including Monte Carlo analysis, into question. In a recent column written for Advisor Perspectives, retirement income strategist and author David Macchia went as far as to proclaim: “There is no safe withdrawal rate.”

While withdrawal rate calculations are a critical component of the retirement planning process for so many, we took a closer look at the recent criticisms.

What Is a Safe Withdrawal Rate?

A safe withdrawal rate is the maximum amount of money a retiree can take out of his portfolio each year while practically ensuring he won’t run out of assets in retirement.

The 4% rule, pioneered by financial advisor William Bengen in the 1990s, dictated that a retiree could safely withdraw 4% of his portfolio in his first year of retirement and then adjust for inflation in subsequent years. Doing so, the rule stipulated, retirees would maintain a high probability that their savings would last at least three decades.

Bengen has since updated his rule of thumb, adjusting the safe withdrawal rate to 4.5%.

Over the years, other financial analysts and firms have produced research on safe withdrawal rates. In 2021, Morningstar published an analysis suggesting new retirees looking to stretch a balanced portfolio 30 years should aim for a 3.3% withdrawal rate. Like Bengen, Morningstar has since amended its guideline to 3.8% in light of increasing bond yields and lower equity valuations.

Using a safe withdrawal rate as a starting point, a person can work backward and calculate how much money he’ll need to save for retirement.

Spotlight on Monte Carlo Simulations

Safe withdrawal rates are often calculated using Monte Carlo simulations, a mathematical technique pioneered in the 1940s. Put simply, Monte Carlo analysis is used to predict the probability of various outcomes, including the longevity of an individual portfolio.

Monte Carlo simulations that calculate safe withdrawal rates are heavily reliant on capital market assumptions (CMAs) or projected returns across asset classes, according to retirement experts Massimo Young and David Pfau. The two chartered financial analysts (CFAs) authored a recent study on Monte Carlo analysis in Advisor Perspectives, calling attention to some of the potential pitfalls of the technique.

The problem? Capital market projections often vary across the financial services industry. Minor differences in predicted returns can have major implications in a Monte Carlo simulation, Young and Pfau said.

A 2022 Horizon Actuarial Services survey of 40 “credible” investment firms offered a wide range of projected equity returns over the next 20 years. The probability that a given withdrawal rate will be successful may depend on the CMA that an advisor uses in his Monte Carlo analysis.

For example, Young and Pfau set out to test withdrawal rates for a hypothetical retiree named Jane: a 65-year-old who wants her \$1 million portfolio (60% stocks, 40% bonds) to last 30 years. Young and Pfau found safe spending levels varied greatly depending on which equity projection they used in the Monte Carlo simulation.

When basing their calculations on the most optimistic prediction in the Horizon report, Young and Pfau found the retiree could safely withdraw \$51,000 from her portfolio in her first year of retirement and have an 80% chance of stretching her money the full 30 years. However, when using the most conservative of equity projections in the survey, Jane could only withdraw \$33,000 initially and still maintain her 80% chance of not running out of money.

“Put differently, if her advisor plays it safe and uses the lowest return prediction, Jane could be underspending by 56%” if the most bullish return prediction turns out to be the right one, Young and Pfau wrote. “Alternatively, if her advisor aligns with the most bullish forecast, she may be overspending by 36% and have a good chance of running out of money early” if the lowest return forecast comes to pass.

The longevity of Jane’s portfolio also varies greatly depending on which CMA is used in the Monte Carlo simulation.

When testing the efficacy of the 4% rule, Young and Pfau found that Jane’s portfolio would run out of money nearly 40% of the time if the most pessimistic equity projections were to become reality. However, when using the most optimistic CMAs, the two researchers determined Jane’s portfolio would have a 95% probability of success over 30 years.

“Our results suggest that probabilities of success, and more generally ‘safe’ withdrawal rates based on Monte Carlo analysis, depend heavily on the accuracy of CMAs,” they wrote. “Even relatively small errors in the inputs – 1 or 2 percentage points – will generate meaningful differences in what advisors might consider a ‘safe’ withdrawal strategy.”

Is There an Alternative?

Macchia, the retirement income expert who called safe withdrawal rates “fiction,” is a proponent of annuities despite the reluctance of some registered investment advisors (RIAs) to embrace them.

“I remind advisors of these two important principles: 1. No retiree stops needing income,” he wrote in his Advisors Perspectives column on Jan. 31. “2. In retirement it’s your income, not your wealth, that creates your standard-of living.”

Young and Pfau pointed to time segmentation and income-flooring as potential alternatives to probability-based retirement income strategies like the 4% rule. The former calls for investment buckets that will be tapped at various stages, while income-flooring relies on bond ladders and annuities to generate cash flow in retirement.

“While these approaches have their pros and cons, they do have the advantage of not relying as much on forecasts of future returns,” Young and Pfau wrote.

Bottom Line

Research from Massimo Young and Wade Pfau shows that Monte Carlo simulations can produce a wide range of safe withdrawal rates, potentially undercutting their reliability as a retirement income strategy. Monte Carlo simulations rely heavily on capital market assumptions (CMAs), which if inaccurate, can skew the results of the analysis and lead retirees astray.

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