How it works

The whole calculation, the order it runs in, and — at the bottom — everything it gets wrong. If a number here surprises you, this page should explain why.

The question

Most comparisons stop at income tax, which is why they so often mislead. “Texas has no income tax” is true and frequently irrelevant: Austin homes cost more than Chicago homes, so the median Austin owner pays more property tax than the median Chicago owner despite a lower rate. A move can also mean going from no car to two, which no cost-of-living index captures.

So this site computes one thing: what you actually have left at the end of the year, in each city, and the difference between them.

in your pocket  =  gross salary
                 −  federal income tax
                 −  state income tax
                 −  local income tax
                 −  Social Security and Medicare
                 −  housing (rent, or mortgage + property tax)
                 −  cars and transport
                 −  food, utilities, healthcare, everything else
                 −  sales tax on what is taxable

answer          =  in your pocket THERE  −  in your pocket HERE

The answer can be negative, and often is. That is the point — a cheaper city and a pay cut pull in opposite directions, and only the arithmetic settles it.

The order matters

Each step feeds the next, and getting the sequence wrong is the most common way a relocation calculator produces a confident wrong answer.

Social Security and Medicare, from salary alone.
Housing — which produces your property tax and first-year mortgage interest.
State income tax.
Local income tax. Yonkers charges a percentage of your state tax, so it has to come after it.
Federal income tax — which uses steps 2 to 4, because state and property tax are deductible. That decides whether itemising beats the standard deduction, which changes what you owe.
Living costs, re-priced for the local area.
Sales tax on the taxable part of that spending.

Computing federal tax first — the obvious way to write it — would ignore the deduction and overstate federal tax in every high-tax state.

Federal tax and Social Security are the same everywhere

They are federal, so they do not vary by state. If you see them change between two cities in your result, it is because the salary changed, not the location. The detailed table shows a middle column at your current salary precisely so this is visible.

One real exception: federal tax can differ between cities at the same salary, for people who itemise. State and property tax are deductible, so a high earner with a mortgage in New York pays less federal tax than an identical earner in Texas. Most households take the standard deduction and never see this.

Housing

Every housing field is pre-filled and editable. If you rent, we use your rent. If you own, we amortise a 30-year fixed mortgage, add property tax at the effective rate — what is actually paid, after assessment ratios, homestead exemptions and caps — and compute first-year interest for the itemisation test.

The rent we start you with is sized to your household and scaled to your income, and both parts matter more than they sound.

Size. The obvious figure to use is the metro’s median rent, and it was the wrong one: it is a median across every rented unit in the area, so a single person and a family of four were quoted exactly the same rent. We now use the local median for the number of bedrooms your household implies — one for the adults, another for every two children.
Income. That median is paid by a household earning roughly the local median income, and renters earn less than that. On a $150,000 salary it worked out at 11% of pay in Chicago, which nobody at that income pays. So the local figure is scaled by a national curve built from what renters in each income band actually spend on rent. The curve crosses 1.0 near $55,000 — about the typical renter’s income — and rises more slowly than income above it, because housing takes a falling share of a rising income.

Buying works the same way. The metro median home value is what the median owner owns, so a high earner was being quoted a cheaper house than they would buy — and, because property tax is charged on the price, a smaller tax bill too. The starting price now scales with income as well.

Both scalings are anchored to the local median owner or renter income, and this detail matters more than it sounds. A single national multiplier looks right until you apply it somewhere expensive: San Francisco’s median home is already owned by high earners, so scaling it by “what a $150,000 buyer purchases nationally” put that household at $1.5m — a third above the local median, while earning below the local median owner. Anchoring locally makes the multiplier exactly 1.0 for the household the median actually describes, which is the only value it can correctly have.

What stays national is the elasticity — how sharply housing spending rises with income, which is a behavioural regularity rather than a local fact. The local price is left completely untouched, so the difference between two cities, which is the one thing this page exists to measure, survives at full strength.

Mortgage principal counts as money out. It builds equity rather than vanishing, but the headline is cash in your pocket, and principal is cash that left it. This makes owning look slightly worse than it is in wealth terms.

Cars

This is the piece most comparisons miss. A cost-of-living index measures prices, not quantities. Moving from Manhattan to Austin does not make your car cheaper — it makes you buy two. Petrol being cheaper in Texas is irrelevant if you went from zero cars to a pair.

So transport is built from a car count, not a price index. The default comes from how many vehicles per adult a place actually has, multiplied by the adults in your household, and you can change it. Each car costs what US households actually spend per vehicle — purchase, fuel, insurance, maintenance and finance charges — at your income level.

Everything else you spend

Food, utilities, healthcare and the rest come from what US households at your income actually spend, then re-priced for each city using federal regional price levels.

Two adjustments are worth knowing about, because both were bugs before they were features:

Your basket travels with you. It is chosen once, from your current income, and simply re-priced in the new city. Choosing it separately per city let the survey’s income-band boundaries leak into the answer, producing a phantom five-figure “saving” on food and healthcare that was an artefact of where the statisticians drew a line.
It is scaled to your household size. Households in the $150k–$200k band average 3.1 people, so a single person was being charged for a family of three. Scaling uses the square-root rule that the OECD uses: needs grow with household size, but not proportionally — two people do not need two fridges.

Sales tax

The taxable base is much smaller than total spending. Forty states exempt groceries and several more tax them at a reduced rate; services are broadly untaxed everywhere. So food splits — restaurant meals at the ordinary rate, groceries at whatever the state does to food. Expect this line to be small: a few hundred dollars a year, not thousands.

Pack, stay, or too close to call

The one-word verdict is the sign of that final difference, and nothing more. It is about money only — this calculator knows nothing about the job, the people, or whether you want to live there.

There is a third answer, and it is the honest one more often than you would think. Every cost here is a median for the local area, and real households scatter widely around every one of them. So when the difference is smaller than 1.5% of the salary you are paid today — $2,250 a year on $150,000 — neither word lights up: the page says too close to call and shows you the figure anyway.

A share rather than a fixed amount, because the uncertainty scales with the household: a $300 gap means something different on $50,000 than on $400,000. A share of gross salary rather than of leftover money, because leftover is at or below zero for a great many real households and a percentage of zero is not a threshold at all. And the salary you have now rather than the one on offer, so the bar does not move every time you try a different number in the box you came here to experiment with.

Share links

A link carries every input and the version of the data it was made with. When the underlying federal figures are refreshed, links already shared keep computing against the data they were created with. Whoever opens your link sees the numbers you saw, not different ones. Nothing is stored on a server — there is no database, and no account.

What this gets wrong

Every model is wrong somewhere. These are the places this one is wrong that we know about.

Some local income taxes still use state averages. New York City, Yonkers, Philadelphia, Detroit, Columbus and Cincinnati carry their own published rates, and you are asked whether you live inside the city, because a metro is much larger than the city at its centre. Cleveland, Pittsburgh, Louisville, Kansas City, St. Louis, Baltimore and Portland do not yet, and sit on their state’s average — which understates all of them.
Social Security is capped once per household, not per worker. For a couple who each earn well, this understates what they pay. It is federal, so it mostly cancels out of the comparison.
Alabama, Missouri and Oregon let you deduct federal tax from state taxable income. Not modelled — it is circular and needs solving iteratively.
Head-of-household filers use each state’s single schedule, because most states publish only single and joint. This is conservative: it never invents a better result than reality.
Income-based phase-outs of state deductions, exemptions and credits are not modelled. They mainly affect high earners.
Only wage income. No investment income, no self-employment, no rental income, no equity compensation.
Moving itself is free here. This is a steady-state annual comparison — movers, closing costs and deposits are not counted.
Home and renters insurance are not included at all. No per-state dataset is loaded yet, so ownership is understated everywhere — and badly in Florida and Louisiana, where premiums are a multiple of the national average.
The top income band is open-ended. The Census publishes rent burden for “$100,000 or more” as a single group, so the rent curve is anchored at $150,000 and extrapolated above it. Expect it to be roughest for very high earners.
Bedrooms are inferred, not asked. Two adults are assumed to share a room and children to pair up. If you rent more space than that, or less, the rent field is yours to change.
Averages are not you. Every figure is a local median. Your rent, your car, your grocery bill will differ. That is why almost every field is editable.

The figures themselves, and where each comes from, are on the data page.

Think something here is wrong?

This list is not finished, and it is not meant to be — every item on it got there because someone noticed. If a number looks off for a place you know, or an assumption on this page does not match how your household actually works, that is worth telling me about even if you are not certain. A model is only corrected by the people it gets wrong.

Two ways to reach me: Email me or open an issue. Every figure is a local median, and the people who live somewhere spot a wrong one first.

This is not financial, tax or legal advice. It is an estimate built from public data to help you think, not a substitute for someone who knows your situation.