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City Retirement Calculator

Can you retire on $1M in Austin? $500K in Chiang Mai? Compare up to three cities side by side with detailed cost-of-living breakdowns and portfolio projections.

Total portfolio value at retirement
Your current annual spending (US national average context)
Where you plan to retire
Optional comparison
Optional comparison
How many years your portfolio needs to last

Your money in Austin, TX

Lasts 30+ years

Adjusted spending: $44,350/yr ($3,696/mo)

Austin, TX
$44,350/yr
Austin ending
$1,690,929

Balance Projection

How it works

Methodology

This calculator adjusts your baseline annual spending by a city-specific composite cost-of-living index. The composite is a weighted average of six categories: housing (35%), food and groceries (15%), healthcare (15%), transportation (10%), utilities (10%), and taxes (15%). Each category index is relative to the US national average, where 1.0 means average cost.

The balance projection uses your adjusted annual spending and a real return rate (nominal return minus inflation) to model year-by-year portfolio drawdown. Under the fixed strategy, your withdrawal amount stays constant in real terms. Under the flexible strategy, you withdraw a fixed percentage of your current balance each year.

When comparing cities, each line in the projection chart represents one city's trajectory. The category breakdown chart shows where the cost differences actually lie — useful for identifying whether a city's high cost is driven by housing, taxes, or another factor.

All calculations run entirely in your browser. No data is sent to any server.

Common questions

FAQ

Where does the cost-of-living data come from?

Our COL indices are compiled from public sources including the Bureau of Labor Statistics Consumer Expenditure Survey, the Council for Community and Economic Research (C2ER), and Numbeo's crowdsourced data for international cities. Each city's index is relative to the US national average (1.0). We weight six categories — housing (35%), food (15%), healthcare (15%), transportation (10%), utilities (10%), and taxes (15%) — to produce a composite score.

How are the COL indices calculated?

Each category index represents how much more or less expensive that category is compared to the US national average. A housing index of 1.5 means housing costs 50% more than average. The composite index is a weighted average of all six categories, with housing weighted most heavily at 35% because it is typically the largest retirement expense.

Does this account for state income taxes?

Yes. The taxes category uses each state's effective income tax rate relative to the national average. States with no income tax (Texas, Florida, Tennessee, Nevada, etc.) show a 0.0 tax index. For international cities, the tax index represents a general estimate of the tax burden on retirement income rather than a precise rate.

How accurate are the international city estimates?

International COL indices are approximate and assume you are spending in local currency at current exchange rates. They do not account for currency fluctuation risk, visa costs, international health insurance, or country-specific tax treaties. Use them as directional guidance, not exact budget figures. For detailed expat retirement planning, consult a cross-border financial advisor.

What is the difference between fixed and flexible withdrawal?

A fixed withdrawal strategy takes the same inflation-adjusted dollar amount each year regardless of portfolio performance. This provides stable income but risks portfolio depletion in bad markets. A flexible strategy withdraws a fixed percentage of your current portfolio balance each year. Your income varies with the market, but the portfolio theoretically never reaches zero.

How often is the data updated?

The COL dataset is reviewed and updated periodically as new BLS and C2ER data becomes available. Because relative cost differences between cities change slowly, the indices remain useful for planning purposes even between updates. The calculator's methodology and projections are not affected by data freshness.

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