Week 38 Day 1: The Magic Number Myth: $1 Million Is Not What It Used to Be

In 1990, $1 million was a lot. At the 4% rule, it funded $40,000/year -- a comfortable middle-class lifestyle. In 2025, $40,000/year is tight. Inflation eroded the magic number. Your retirement number is personal: it depends on YOUR spending, YOUR timeline, YOUR other income (Social Security, pensions), and YOUR risk tolerance. Not a headline number.

Why the single number fails: (1) It ignores spending. Two retirees both have $1.5 million. Retiree A spends $50,000/year (3.3% withdrawal rate -- very safe). Retiree B spends $90,000/year (6% withdrawal rate -- will likely run out). Same number, wildly different outcomes. The number that matters is NOT your portfolio size -- it is your withdrawal rate. (2) It ignores timing. Retiring at 40 with $1.5 million means funding 50+ years. Retiring at 65 with $1.5 million means funding 25-30 years. The same number works for the 65-year-old but may be insufficient for the 40-year-old. (3) It ignores other income. If you will receive $25,000/year from Social Security, your portfolio only needs to fund the gap between total spending and Social Security. At $60,000/year spending, the gap is $35,000/year. At the 4% rule, you need $875,000 -- not $1.5 million. (4) It ignores healthcare. Before Medicare eligibility (65), health insurance costs $500-$1,500/month for a couple. That is $6,000-$18,000/year that disappears at 65. Your spending is not constant across retirement. The better framework: retirement readiness = (portfolio * withdrawal rate + Social Security + pension + other income) >= annual spending. If the left side exceeds the right side by a comfortable margin, you are ready. No single number needed.

The 'retirement number' concept oversimplifies a multi-dimensional problem. Milevsky (2006) identified the key stochastic variables: (1) investment returns (sequence risk), (2) inflation (purchasing power risk), (3) longevity (outliving savings risk), (4) healthcare costs (catastrophic expense risk), and (5) spending flexibility (the ability to reduce spending in bad years). A single number implicitly assumes fixed values for all five variables. In reality, each variable has a probability distribution, and the retirement outcome is the convolution of all five distributions. The proper framework is a Monte Carlo simulation (addressed in Week 45) that models the joint probability of all variables. Bengen's (1994) 4% rule was derived from historical U.S. data and represents the maximum withdrawal rate that survived every 30-year period in U.S. history. However, Pfau (2010) showed that the 4% rule is specific to the U.S. market; international data yields safe withdrawal rates of 3.0-3.5% for many countries. Additionally, the 4% rule assumes a fixed 30-year horizon; for early retirees (40-50 year horizons), a 3.0-3.5% initial withdrawal rate is more appropriate. The dynamic spending approach (Guyton and Klinger, 2006) provides a more sophisticated framework: rather than a fixed percentage, spending adjusts based on portfolio performance, with 'guardrails' that increase spending after strong returns and decrease spending after poor returns. This approach achieves higher sustainable spending rates (4.5-5.0%) by accepting spending variability, and better reflects how retirees actually behave.