Guide

How to Compare Cities with Data

By the numbers

The seven dimensions, by the numbers

7
dimensions of daily life
6
federal source agencies
387
US metros scored
51
states scored
Cost of Living20%Wages20%Rent15%Safety15%Schools10%Childcare10%Environment10%
How the composite Life Score is weighted, cost of living and wages carry the most, each from its own federal dataset.

A structured approach to evaluating where to live using objective federal data.

Key Takeaway

Compare cities across six dimensions: affordability (cost vs. income), safety, jobs and wages, education, health, and environment. No single city wins on all dimensions, the goal is finding the best match for YOUR priorities. PlainCompare combines data from 7 federal sources to enable objective, multi-dimensional comparison.

The Six Comparison Dimensions

PlainCompare evaluates metros across six key areas, each drawing from a different federal data source:

  1. Affordability: BEA Regional Price Parities measure how much goods and services cost relative to the national average. Combined with BLS wage data, this shows your real purchasing power, not just what you earn, but what you can buy with it.
  2. Safety: FBI Uniform Crime Reporting data shows violent and property crime rates per 100,000 residents. Compare both types, a city can be safe from violent crime but have high property crime, or vice versa.
  3. Jobs & Wages: BLS data shows employment levels and median wages for major occupations. Compare your specific occupation's wages across metros, not just overall median income.
  4. Education: NCES data covers school counts, student-teacher ratios, and enrollment. Combined with Census data on educational attainment, this paints a picture of the education landscape.
  5. Healthcare access: HRSA Health Professional Shortage Area (HPSA) designations show where a metro is short on primary care, dental, or mental health providers relative to population.
  6. Environment: EPA air quality data shows how many unhealthy air days a metro sees per year and water-system safety compliance under the Safe Drinking Water Act.

Browse all metros or use the comparison tool to evaluate specific cities side by side.

Step 1: Define Your Priorities

Before comparing cities, rank what matters most to you. Common priority sets:

  • Young professional: Jobs → affordability → culture → safety
  • Family with kids: Safety → education → affordability → health
  • Retiree: Health → affordability → climate → safety
  • Remote worker: Affordability → climate → safety → environment

Your priorities determine which dimensions carry more weight in your decision. A city that's excellent on safety but poor on affordability might be perfect for a high earner but impractical for a median-income household.

Step 2: Filter by Non-Negotiables

Start by eliminating cities that fail your must-have criteria. Use PlainCompare's rankings to filter:

  • If affordability is critical, eliminate metros with price parities above 110% (10%+ more expensive than national average).
  • If safety is non-negotiable, eliminate metros in the top quartile for violent crime.
  • If your career requires a specific industry, eliminate metros without a strong job market in that field.

Step 3: Compare Your Shortlist

With 3-5 metros remaining, do a deep comparison:

  1. Use the side-by-side comparison to see all dimensions at once.
  2. Check composite scores that weight multiple factors into a single livability index.
  3. Look at state-level context on state pages - state taxes, regulations, and policies affect daily life beyond metro-level data.
  4. Cross-reference with county-level data for more granularity within a metro.

What Data Can't Tell You

Federal data is excellent for objective, quantifiable comparison. But some important factors aren't captured:

  • Culture and community feel: No dataset measures walkability, restaurant quality, arts scene, or neighborhood character. Visit in person.
  • Social connections: Proximity to family and friends matters enormously for happiness. Data can't capture this.
  • Future trajectory: Data reflects the past. A city investing heavily in infrastructure and attracting employers may be much better in 5 years than current data shows.
  • Micro-geography: A metro area contains diverse neighborhoods. Data for the metro average may not reflect the specific suburb you'd live in.

Frequently Asked Questions

What data sources does PlainCompare use?

PlainCompare draws from multiple federal databases: BEA Regional Price Parities (cost of living), FBI UCR (crime rates), BLS OEWS (wages), Census ACS (demographics, housing), NCES (education), HRSA HPSA designations (healthcare access), and EPA (air quality). This multi-source approach gives a more complete picture than any single dataset.

What is a metropolitan statistical area (MSA)?

An MSA is a geographic region defined by the Census Bureau around a core urban area of 50,000+ population plus surrounding counties with strong commuting ties. MSAs capture the full economic area, not just the city itself. "Dallas-Fort Worth-Arlington" includes all the counties where people live and commute as part of that metro economy.

Why compare metros instead of cities?

City limits are arbitrary political boundaries that don't reflect where people actually live, work, and commute. A person might live in a suburb, work downtown, and shop in a neighboring town, all within the same metro area. Metro-level data captures the entire labor market, housing market, and community.

Which factors matter most for quality of life?

Research consistently shows that cost of living relative to income (affordability) has the strongest impact on financial quality of life. Safety, healthcare access, and education quality matter most for families. Climate and cultural amenities matter more for lifestyle preferences. There is no universal "best" city, it depends entirely on your priorities.

Can I compare more than two cities?

Yes. PlainCompare supports side-by-side comparison of multiple metros. This is particularly useful for narrowing down a shortlist, compare your top 3-4 candidates across all dimensions to see where each excels and falls short.

How current is the data?

Each data source has its own update cycle. BLS wages are updated annually. FBI crime data lags by 1-2 years. Census ACS is a rolling 5-year average. Cost of living (BEA RPP) is annual. PlainCompare uses the most recent available data from each source.

Sources

  • Bureau of Economic Analysis, Regional Price Parities
  • FBI, Uniform Crime Reporting (UCR)
  • Bureau of Labor Statistics, OEWS
  • Census Bureau, American Community Survey
  • NCES, Common Core of Data
  • CDC, PLACES (Population Level Analysis)
  • EPA, Air Quality System

This content is for informational purposes only. City selection is a personal decision involving many factors beyond data.

A worked example

Take the same $100,000 salary to two different metros. In one with a cost-of-living index of 95, below the national average of 100, that salary stretches further than in a metro at 115, a gap of roughly $20,000 in real purchasing power before you weigh rent, schools, safety or commute. Affordability is just one of the seven dimensions, but it is the one that reshapes every other trade-off, which is why a side-by-side comparison beats any single headline number.

The trade-off, across 387 metros

That $100k example isn't a one-off, it's the pattern. Each dot is a US metro, placed by how affordable it is (rightward) against how high its wages run (upward). The cloud drifts down-right: cheaper places usually pay less. The rare gold metros beat the trade-off on both.

↑ higher wages less affordable ← · → more affordable

Where to dig deeper

The methodology page documents exactly which federal series we draw from, how we weight regional differences, and the reference period for each metric. The research section publishes original analyses derived from the same underlying database, useful when you want to see year-over-year shifts or peer-jurisdiction comparisons that the per-page detail views don't surface.

ThresholdFederal definitionPractical meaning
Below 7%AffordableComfortable margin for unexpected expenses
7-30%Moderate burdenManageable but constrains discretionary spending
Above 30%BurdenedHUD definition, qualifies for federal subsidy programs
Above 50%Severely burdenedTrade-offs with food, healthcare, savings
"The strongest decisions come from triangulating multiple data sources against your specific situation, not from chasing the latest headline number."

Frequently asked questions

Where does this data come from?

All figures on this page derive from official federal data, primarily the U.S. Bureau of Labor Statistics, U.S. Census Bureau, U.S. Department of Health and Human Services, and U.S. Department of Labor. We cite the underlying agency and series in the methodology section. No proprietary aggregators are used.

How often are figures updated?

Each series follows its own publication cadence. We refresh our database within 30 days of each upstream release. Specific update timestamps appear in the page footer where available; the methodology page documents the cadence per data series.

Can I use this data for my own analysis?

Yes. The underlying federal data is public domain. Our presentation, calculations, and editorial commentary are licensed for individual reference. For commercial republication or large-scale data extraction, contact us at the email listed on the contact page.

What if the figures here disagree with another source?

Different sources use different methodologies, definitions, geographic boundaries, and reference periods, disagreement is normal and informative. Our methodology page documents exactly which series and reference period we use for each metric, so you can reproduce or audit the figures against the upstream agency directly.

Source: Federal data aggregation: BEA + BLS + FBI UCR + NCES + HRSA HPSA + EPA AQI PlainCompare quality-of-life framework · 2024 See methodology page for full provenance: BEA Regional Price Parities (annual), BLS OEWS (annual), FBI UCR (1-2yr lag), NCES (annual), HRSA HPSA designations (periodic), EPA AirNow (quarterly).