The Location Pay Read, One Remote Role Priced Across Four Metros

This guide is for a job seeker deciding where to live, relocate, or simply register a home address for a remote role, and who needs to know what one role actually pays across cities. It carries a single role through posted ranges tallied across four metros and ends with a net, after-tax comparison you can rebuild on your own case. The point is to separate three things that most calculators quietly blend: the geographic pay differential, the cost of living, and the state tax bite.

Most pages on remote salary by location either explain the theory abstractly or hand you a black-box number. This one shows the arithmetic, including the wrong turns. You will see where the cost-of-living shortcut, the outlier posted range, and the ignored state tax each send you to a different, wrong answer.

Why one gross number cannot tell you where to live

A single posted salary is not a location decision, because the same role prices differently by metro, and gross is not what lands in your account. Three forces move the real number, and they do not point the same way.

The first is the geographic pay differential: the discount or premium employers apply to the same role by location. The second is the tax you pay on that gross, which varies by state. The third is cost of living, which is the one most people reach for and the one that most often misleads. The job of this guide is to keep those three apart and let each carry its own weight.

Start with the size of the differential. Named compensation research puts the base-salary discount at roughly 10 to 20 percent from a Tier 1 hub to a mid-tier metro. Worked illustrations agree: a software engineer at a $120,000 national baseline might see $144,000 in a top-tier market, a 20 percent premium, and $108,000 in a lower-cost market, a 10 percent discount. A $150,000 senior product manager anchor becomes $177,000 with an 18 percent New York differential and $138,000 with an 8 percent Phoenix differential. Geography alone can shift a range by 20 to 50 percent, which is why the same title should carry different min-mid-max figures across cities.

That single fact is the reason this guide exists. If a Texas offer at a lower gross nets more than a California offer at a higher gross, ranking on gross is simply wrong. And the tax swing is invisible in every posted range.

The example role: one remote backend engineer, four metros

I will carry one role the whole way: a senior backend engineer, remote-eligible, priced across Austin, Seattle, New York, and Denver. Pick your own role and level and follow along. The method does not change.

Suppose you gather four postings for the identical title and level, one per metro, and record the midpoint of each:

These midpoints are illustrative, chosen to walk the method. Yours will come from live postings. The important discipline is that each figure is a midpoint from a specific posting, tagged with metro and date, not a number you half-remember or a national average.

Note two things already. Seattle prices above New York here, which contradicts the reflex that New York is always the top of the market. That reflex comes from cost of living. New York has the highest cost of living but not the highest cost of labor, while Seattle commands a relatively high cost of labor even though its living cost sits below New York, San Francisco, and Los Angeles. Cost of living and cost of labor genuinely invert, and you cannot price a role on the wrong one.

The tier schedule you are pricing against

Employers group metros into two to five tiers and discount each tier against a hub baseline set to 100 percent, so your differentials should land near a known schedule or you have made an error. This is the frame to check your own arithmetic against.

Most companies that use formal location tiers keep it to two to five, and review the differentials at least annually as markets shift. Assignment is by market pay similarity, with the highest-cost location set to 100 percent. Hubs like San Francisco, New York, and Seattle form Tier 1; secondary markets like Boston, Los Angeles, Austin, and Washington DC form Tier 2 at 90 to 95 percent; emerging markets such as Charlotte, Miami, and Nashville fall into Tier 3 at 80 to 85 percent. Toast publishes a live version of this: Zone A is San Francisco, New York, and Seattle; Zone B is Boston, LA, Austin, Chicago, and DC; Zone C is Omaha, Atlanta, Charlotte, and much of remote.

Here is the discount schedule from Pave's research, which is your reference for a same-role move down the tiers.

The equity column is the one people miss. Base drops about 11 to 16 percent moving down a tier, but new-hire equity drops about 29 to 36 percent for the same move. Equity is priced off scarce hub labor markets, so a hub-to-mid-metro move can cut total comp far more than the base number implies. If your role carries meaningful equity, price it as a separate line, because the geo discount on it is roughly double the base discount.

How this goes wrong: seven ways to reach a wrong number

The failure modes below are where a location pay read quietly breaks. Each has a false positive that looks like a real answer, and a check that catches it. This is the most valuable part of the method, because every one of these produces a confident, wrong table.

Using cost of living as the differential

The false positive: you cut New York pay because rent is the highest in the country. But New York is not the highest cost of labor, so a living-cost cut underpays there and misreads Seattle. The check: for each differential, ask whether it is sourced to a local wage figure or a cost-of-living index. Only wage figures are valid.

Keeping an outlier range

A posting whose spread runs far above 60 percent most likely blends two levels or two zones, and it will drag your midpoint. Wide is not generous; wide is usually two things stacked. The check is arithmetic, covered in the next section.

Ignoring state tax

The false positive: ranking metros by gross. A higher gross in California can net less than a lower gross in Texas. The check: rank on net after federal and state income tax, not on the posted number.

Treating "no income tax" as "low tax"

The false positive: overstating Texas net because it has no income tax. The nine no-income-tax states recover revenue elsewhere. Texas and New Hampshire carry some of the highest effective property tax rates, running roughly 1.6 to 2.2 percent of home value. The check: add property and sales tax context before you call a no-income-tax metro the winner.

Rounding differentials to 10 percent tiers when precision matters

Sources disagree on rounding. ERI rounds to 10 percent tier increments; other methods keep exact city-level percentages. A metro near a tier boundary can be misclassified by rounding. The check: compute the exact percentage first, then decide whether to round.

Confusing a single posting with the market

One posting is not a metro rate. The check: triangulate against the BLS OEWS metro wage for your occupation code before you trust any single number.

Applying HQ-based geo to a remote worker

Many employers price on home zip code, not headquarters. Over half of organizations, about 55 percent, set geographic pay differences by city or metro area. The check: confirm whether the posting sets pay by employee location or by nearest office, because it changes which differential applies to you.

Wide is not generous. A posted range far above the professional norm is usually two levels stacked into one number.

The reliability screen: which ranges to keep

Compute the range spread for every posting and quarantine any that sits far outside the 40 to 60 percent professional norm, because that range is probably a level or geography blend rather than a real single-role spread. This is step two, and it protects everything downstream.

The formula is simple: range spread equals (maximum salary minus minimum salary) divided by minimum salary. Normal spreads are bounded by role class. It is common to use 30 to 40 percent for hourly or contract positions, 40 to 60 percent for entry-to-mid professional and managerial roles, and 60 to 70 percent for executive positions. Ranges under 20 percent are too tight to reward performance; ranges over 60 percent make it hard to justify pay differences for similar work.

There is no published formal "exclude if" rule for tallying postings across metros. That is not established publicly, so treat the spread as a benchmark, not a hard cutoff. The practical inference holds: a single-metro professional posting whose spread greatly exceeds the 40 to 60 percent norm most likely blends levels or geographies and should be treated as unreliable.

Run it on the example. Suppose the Denver posting reads $120,000 to $210,000. That spread is (210,000 minus 120,000) over 120,000, which is 75 percent, well above the professional norm. That posting is almost certainly two levels in one listing. Quarantine it, note the reason, and either find a cleaner Denver posting or use the BLS OEWS metro wage as your Denver anchor instead.

Building the read, step by step

Here is the full procedure, from raw postings to a ranked net-pay table. Work it in order; each step's output is the next step's input.

Working the example through to net

With the Denver outlier quarantined, take Seattle as the baseline at 100 percent and compute differentials on the surviving midpoints. Seattle at $190,000 is the anchor. New York at $185,000 is 97 percent of Seattle. Austin at $168,000 is 88 percent. Those percentages are close to the published schedule: New York as a fellow Tier 1 sits near the top, and Austin's 88 percent lands squarely in the Tier 2 band of 90 to 95 percent for base, a touch lower, which is worth a second look at the source posting.

Now the tax layer, which is where gross rankings fall apart. Washington and Texas levy no state income tax; New York's rate runs about 4 to 10.9 percent; California's top rate reaches 13.3 percent. On a $100,000 gross, Texas nets about $76,600 against California's $68,900. Two people earning identical $85,000 salaries can differ $4,000 to $7,000 a year in take-home purely on state. On a $90,000 salary, skipping a 5 percent state income tax keeps roughly $4,500 more per year.

Here is the state tax swing on identical gross, which you apply on top of the geo differential.

Apply this to the example. Seattle's $190,000 in no-income-tax Washington keeps its full state advantage; New York's $185,000 loses several percent to state tax; Austin's $168,000 in no-income-tax Texas closes part of the gap to the hubs on net even though its gross is lowest. The ranking on net can differ from the ranking on gross, which is the entire reason to run this read.

Then layer the caveat. Texas and Washington recover revenue through other taxes; Texas effective property tax runs roughly 1.6 to 2.2 percent of home value. If you rent, that burden lands differently than if you buy. Add a full-tax-burden note per metro so you are not fooled by the income-tax headline.

Metro | Gross (mid) | Differential vs baseline | State income tax | Est. net | Non-income tax note
Seattle | $190,000 | 100% (baseline) | none (WA) | $____ | check property/sales
New York | $185,000 | 97% | ~4-10.9% | $____ | -
Austin | $168,000 | 88% | none (TX) | $____ | property ~1.6-2.2% of home value
[your metro] | $______ | __% | __% | $____ | -

Where the labor market floor comes from

Scarcity, not city size, sets the floor under a role's pay, so a rare-skill role resists geographic discounting because supply is thin in every metro. Check your skill's scarcity before you assume any city will discount you.

In Refolk's index there are 349,664 US profiles with the title Software Engineer and 3,524 US profiles listing the skill Rust. That is about 99 generalist software engineers for every one Rust-skilled profile.

The scarce supply concentrates in Seattle, the San Francisco Bay Area, Austin, New York, and Boston. When supply is that thin, employers cannot discount much by geography, because there is no cheaper pool of the same skill in a lower-tier metro. A generalist role compresses across metros; a scarce-skill role holds its value. Knowing which one you are changes how much of the tier discount you should accept.

If you want to see where your own scarce skill actually clusters before you decide which metros to price, running the supply search directly is faster than guessing. Refolk writes and tailors your resume from your history, and it can also show you where the talent for your role sits.

Cost of labor versus cost of living, made visual

The two axes people conflate are cost of labor, what employers pay for your skill, and cost of living, what a metro costs you to live in. They move independently, and where they diverge is where a naive read goes wrong.

Seattle sits in the high-labor, lower-living quadrant relative to New York, which is exactly why it can out-price New York on net despite a lower cost of living. Price it on labor and it holds; price it on living and you underpay it. Use cost of living only as a sanity check on your net figure, never as the differential itself.

Keep it current, and what to verify before you trust the table

A location pay read is a snapshot, and markets shift, so review it at least annually and re-run the tax layer whenever you change home state. The mechanism to re-check is the same procedure; only the inputs age.

Public sources age at their own pace. BLS OEWS covers about 830 occupations across roughly 530 metropolitan and nonmetropolitan areas, but it is model-based on three years of data, so it is a blended recent rate rather than a live spot price. Treat it as a triangulation anchor, not a live market read. Posted ranges are live but noisy; that is why the spread screen matters. Tier schedules and tax rates change year to year, so date every input.

One last framing. Some workers value remote flexibility enough to trade pay for it: roughly 9 percent would accept a 20 percent pay cut to work remotely, and about 21 percent would accept a 10 percent cut. That is a legitimate preference, but it is a separate decision from the pricing read. Do the read first, in net dollars, then decide how much of the difference you are willing to give back for where you want to live. The table tells you the price of the choice; only you set its worth.