Long Horizon Optimization, Uncertainty
The Retirement Timing
The Retirement Timing is a Long Horizon Optimization and Uncertainty scenario. The core lesson: Optimize for expected healthy years remaining, not total years. You're 58. You can retire at 60 with 75% of your full pension, or work to 63 for 95%. DecisionPlay maps the players, payoffs, and equilibrium dynamics that shape how this situation typically resolves.
The situation
You're 58. You can retire at 60 with 75% of your full pension, or work to 63 for 95%. Your health is good now but uncertain. Your spouse has a 20-year travel dream. The work is still meaningful but increasingly tiring.
Background
Retirement timing is a classic optimization problem where the inputs, health trajectory, longevity, spouse preferences, and the subjective value of time, are all deeply uncertain. Most people optimize for income security while underweighting the expected value of healthy, mobile years that have a biological expiration date.
What this reveals
Healthspan vs. lifespan: optimize for mobile years, not total years
Standard retirement planning optimizes for income security over a projected lifespan. It almost never optimizes for expected healthy, mobile years, the years in which you can actually do what retirement is for. These two optima are different. Financial planning tools don't have a field for 'years of good knees remaining,' but that variable is often the binding constraint on what retirement actually looks like.
How to counter it: Before finalizing any retirement date, ask: what do I want to do in retirement that requires health and energy? When does the window for that close? Then back-calculate whether your current plan actually gets you there in time.
A question to sit with
If you knew you had exactly 5 years of healthy mobility left starting today, would that change how you think about work?
Frequently asked questions
- What game theory concept does The Retirement Timing illustrate?
- The Retirement Timing illustrates Long Horizon Optimization, Uncertainty. Optimize for expected healthy years remaining, not total years.
- What is the situation in The Retirement Timing?
- You're 58. You can retire at 60 with 75% of your full pension, or work to 63 for 95%. Your health is good now but uncertain.
- What does The Retirement Timing reveal about how people decide?
- Healthspan vs. lifespan: optimize for mobile years, not total years. Standard retirement planning optimizes for income security over a projected lifespan. It almost never optimizes for expected healthy, mobile years, the years in which you can actually do what retirement is for. These two optima are different. Financial planning tools don't have a field for 'years of good knees remaining,' but that variable is often the binding constraint on what retirement actually looks like.
- How do you avoid the trap in The Retirement Timing?
- Before finalizing any retirement date, ask: what do I want to do in retirement that requires health and energy? When does the window for that close? Then back-calculate whether your current plan actually gets you there in time.
- What is the research behind The Retirement Timing?
- Retirement timing is a classic optimization problem where the inputs, health trajectory, longevity, spouse preferences, and the subjective value of time, are all deeply uncertain. Most people optimize for income security while underweighting the expected value of healthy, mobile years that have a biological expiration date.
- How long does The Retirement Timing take to play?
- About 11 min, at advanced difficulty, across 4 decision points. It runs in your browser with no account and no sign-in.
Keep exploring
More Personal Decisions scenarios, or browse all scenarios. New to this? Start with how DecisionPlay works or the game theory glossary.
Topics: retirement, long-horizon, healthspan, uncertainty