WageDex guide
Salary vs. Cost of Living
A practical walkthrough for comparing job offers across metros: how to adjust nominal pay for local prices, read a BEA Regional Price Parity, and avoid the most common relocation-math mistakes.
The short answer
A higher salary in an expensive city is not always more money. San Francisco is the priciest US metro at 116 on the BEA price index (100 = national average), so $100 of typical purchasing power is worth only about $86 there, versus Monroe at 84. Always adjust nominal wages for local prices before comparing offers.
- 116
- San Francisco price level
- 84
- Monroe price level
- $86
- Real value of $100 in San Francisco
WageDex shows metro-level wages; combine them with these BEA Regional Price Parities to compare real earning power, not just headline pay.
Why Nominal Salary Comparisons Mislead
When comparing job offers in different cities, the nominal salary figure, the number on the offer letter, is only the starting point. The purchasing power of that salary depends on three factors that vary enormously by location: housing costs, general cost of living, and state/local income taxes.
Consider two offers: $140,000 in Seattle and $95,000 in Columbus, Ohio. Seattle's cost of living is roughly 70% higher than Columbus. After applying that adjustment, the Seattle salary is equivalent to about $82,000 in Columbus purchasing power, substantially less than the $95,000 Columbus offer. Add the fact that Washington has no state income tax (Ohio has a 3.99% rate), and the gap widens further.
This kind of comparison used to require custom spreadsheets. WageDex's metro salary data lets you see what each occupation pays in each metro, the starting point for any location comparison.
The most expensive US metros
BEA Regional Price Parity, all items (100 = national average) - higher means your salary buys less
- San Francisco
San Francisco-Oakland-Fremont, CA
115.6 price index
- Miami
Miami-Fort Lauderdale-West Palm Beach, FL
114.2 price index
- Los Angeles
Los Angeles-Long Beach-Anaheim, CA
113.6 price index
- New York
New York-Newark-Jersey City, NY-NJ
112.6 price index
- Napa
Napa, CA
112.6 price index
- San Diego
San Diego-Chula Vista-Carlsbad, CA
111.9 price index
- Seattle
Seattle-Tacoma-Bellevue, WA
111.1 price index
- Urban Honolulu
Urban Honolulu, HI
111 price index
- Oxnard
Oxnard-Thousand Oaks-Ventura, CA
110.5 price index
- San Jose
San Jose-Sunnyvale-Santa Clara, CA
110.4 price index
Cost-of-Living Adjusted Salary, City Comparison
The table below shows how a $100,000 national-baseline salary translates to equivalent purchasing power across major metros, using BEA Regional Price Parity (RPP) index values. A salary in a city with index 150 (50% above national average) needs to be 50% higher just to match the national purchasing power baseline.
| Metro Area | Cost Index | $100K Equiv. Salary Needed | Tax Note |
|---|---|---|---|
| San Francisco, CA | 115.6 | $86,494 | 9.3% state income tax |
| New York City, NY | 112.6 | $88,842 | 6.85% state + 3.9% city tax |
| Seattle, WA | 111.1 | $89,981 | No state income tax |
| Washington, D.C. | 108.9 | $91,842 | 8.5% district income tax |
| Boston, MA | 108.3 | $92,363 | 5% flat state income tax |
| Chicago, IL | 103.6 | $96,529 | 4.95% flat state income tax |
| Phoenix, AZ | 103.3 | $96,790 | 2.5% flat state income tax |
| Dallas, TX | 103.1 | $97,002 | No state income tax |
| Atlanta, GA | 100.1 | $99,942 | 5.49% state income tax |
| Columbus, OH | 95.5 | $104,746 | 3.99% state income tax |
| Memphis, TN | 92.2 | $108,486 | No state income tax |
Cost index: national average = 100. "Equiv. salary" = salary needed in each city to match $100,000 national purchasing power. Approximate figures based on BLS RPP data and 2024 state tax rates. Does not include property tax or sales tax variation.
The Housing Factor: Why It Dominates
Housing is typically 30-50% of a worker's budget, and housing costs vary far more than any other expense category between cities. Groceries in San Francisco cost roughly 15% more than in Memphis. But housing in San Francisco costs 400-600% more. This asymmetry means housing almost single-handedly determines the real value of a relocation salary change.
The math becomes especially stark for homebuyers. The median home price in San Jose, CA is around $1.4 million. In Columbus, OH, it's around $240,000. A software developer buying a home in San Jose needs roughly 6x more income to carry the same mortgage debt-to-income ratio as a peer buying in Columbus.
When comparing cities, look at housing costs separately from general cost of living. If you plan to rent, focus on median monthly rent for your target unit type. If you plan to buy, compare median home prices and 30-year mortgage payments at current rates in each market.
State and Local Taxes: The Hidden Salary Differential
State income taxes can significantly affect take-home pay, especially at higher income levels. The difference between living in a no-income-tax state and a high-tax state can amount to $10,000-$30,000 per year for six-figure earners:
- No state income tax: Washington, Texas, Florida, Nevada, Tennessee, Wyoming, South Dakota, Alaska, New Hampshire (New Hampshire's former interest-and-dividends tax was fully repealed effective January 1, 2025).
- Low rate (under 3%): Arizona (flat 2.5%), Indiana (flat 2.95%), North Dakota (graduated, top rate 2.5%).
- High marginal rates (over 8%): California (up to 13.3%), Hawaii (up to 11%), New York (up to 10.9% + NYC 3.9%), New Jersey (up to 10.75%), Oregon (up to 9.9%).
At $150,000 of income, California's state income tax is roughly $13,000-$17,000 more than Texas (which has no state income tax). This difference equals a substantial pay cut that doesn't appear in the nominal salary comparison.
How to Compare Two Job Offers Across Cities
A practical step-by-step process for evaluating offers in different metros:
- Look up both occupations on WageDex. Check the metro-level wage data to understand what the market pays for your occupation in each city. Confirm your offer is reasonable relative to local percentiles.
- Find the cost-of-living index for each city. Use BLS RPP data or a reputable cost-of-living calculator. Note the housing sub-index separately.
- Calculate the purchasing-power-equivalent salary. Divide each salary by the city's cost index and multiply by 100. Compare the results.
- Calculate after-tax take-home pay. Apply federal and state income tax rates to each salary. For high earners in high-tax states, this step often changes the winner.
- Estimate monthly housing cost. Look up median rent or mortgage payment for your target unit type in each city. Confirm housing is affordable on after-tax take-home in both scenarios.
- Factor in career trajectory. Some markets (San Francisco tech, New York finance) offer higher long-term wage growth due to network density and employer concentration. A lower nominal salary in a high-trajectory market may beat a higher salary in a stagnant market over 5-10 years.
Geographic Arbitrage: The Remote Work Opportunity
Remote work created an opportunity that didn't exist at scale before 2020: earning wages benchmarked to a high-cost, high-wage market while living in a lower-cost area. This "geographic arbitrage" can dramatically increase real purchasing power:
- A remote software developer paid $180,000 at San Francisco rates while living in Austin, TX achieves purchasing power equivalent to roughly $250,000+ in San Francisco.
- No state income tax in Texas adds another $15,000-$25,000 in effective annual pay compared to living in California.
- Housing costs that are 50-60% lower mean dramatically accelerated wealth building through savings and equity.
The catch: many companies now adjust remote salaries based on where employees live, eliminating part of the arbitrage. Some pay full market regardless of location; others discount by local cost of living. Always ask about the remote pay policy before assuming you can arbitrage a high-cost employer's pay scale from a low-cost city.
Browse metro-level salary data and state wage comparisons on WageDex to build your own location comparison.
Frequently Asked Questions
How much of a salary difference does cost of living actually make?
The difference is often enormous. San Francisco typically costs 80-100% more than the national average for housing and general expenses. A $180,000 salary in San Francisco may have less purchasing power than a $100,000 salary in Columbus, Ohio. The specific impact depends heavily on housing, rent and mortgage costs vary far more than food or transportation. Use a cost-of-living index to estimate the equivalent salary in any target city.
What is a cost-of-living index?
A cost-of-living index quantifies how expensive one location is relative to another or to a national baseline (usually set at 100). An index of 150 means the location costs 50% more than the national average. The BEA Regional Price Parity (RPP) is the most statistically rigorous such index. When comparing job offers across cities, calculate the RPP-adjusted salary to compare purchasing power apples-to-apples.
Should housing or overall cost of living determine my salary comparison?
Housing is the most important single factor, but overall cost matters too. In many high-cost cities, transportation, dining, childcare, and services also cost more. A comprehensive cost-of-living comparison includes: housing (50-60% of the adjustment), transportation, food, healthcare, and taxes. That said, if you plan to buy a home, housing price differences are often even larger than rental cost differences, a home in San Jose costs 6-8x more than the same home in Memphis.
Does cost-of-living always favor lower-cost cities?
Not always. High-cost cities often offer career advantages that affect long-term earnings: denser labor markets (easier to switch jobs, negotiate raises), higher salary growth trajectories, and network effects from working alongside high performers. A few years in a top-tier market can accelerate career growth in ways that compound over decades. The calculus depends on career stage, industry, and personal priorities, it is not simply "low cost is always better."
How do I account for state income taxes in a salary comparison?
For high earners, state income taxes matter significantly. California's top marginal rate is 13.3%, New York's is 10.9% (plus NYC city tax of 3.9%). States with no income tax (Washington, Texas, Florida, Nevada, Tennessee, and others) effectively add 5-10% to take-home pay for workers earning $100K+. A $150,000 salary in Washington State nets substantially more than $150,000 in California after state income tax.
How does remote work change the cost-of-living equation?
Remote work allows workers to capture high-employer-market wages while living in lower-cost areas, the classic geographic arbitrage. A software developer paid at San Francisco rates while living in Phoenix or Raleigh achieves dramatically higher real purchasing power. However, many companies have moved to "location-based pay" - adjusting salaries based on where you live, not where the company is headquartered. Always clarify the pay policy before assuming remote work enables geographic arbitrage.
The Bureau of Labor Statistics OEWS survey, current as of May 2025, is the source: WageDex tracks 831 occupations across 582 U.S. states and metro areas, comprising 36,367 state-level wage records, according to the same federal survey.
Sources
- U.S. Bureau of Labor Statistics, OEWS, May 2025
- U.S. Bureau of Economic Analysis (BEA), Regional Price Parities 2023
- BLS, Consumer Price Index regional data
- State income tax data from Tax Foundation (2024)
This content is for informational purposes only. Cost-of-living indices and tax rates are approximate and subject to change. Individual circumstances vary significantly. Consult a financial professional for advice specific to your situation.
Understanding the Data
The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.
It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.
For readers who want to conduct their own research, we recommend going directly to the source whenever possible. the U.S. Bureau of Labor Statistics provides detailed documentation on the OEWS survey's collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.
How We Analyze Data Records
Our pipeline pulls the raw OEWS release, standardizes occupation and area names against a fixed taxonomy so the same job title matches across editions, and computes derived figures (percentile bands, metro-vs-national ratios, year-over-year change) that BLS publishes as separate files but most readers want to see side by side.
The metrics we track for every occupation include median and mean annual wage, employment counts, and percentile wage bands (10th through 90th percentile). These figures let you see not just what an occupation pays nationally, but how that compares across metro areas, states, and neighboring occupations, since a single national average can hide wide regional and role-level variation.