Guide

What Metro-Level Data Tells You

The verdict

Affordability is the widest-swinging dimension in PlainCompare's field: Monroe, LA scores 100 on cost while San Francisco-Oakland-Fremont, CA scores 0, a 100-point gap on the same 0-100 scale.

100
Monroe, LA cost score (highest)
0
San Francisco-Oakland-Fremont, CA cost score (lowest)
100pt
spread across the field
387
metros scored

Most affordable metros by cost score

Highest cost-affordability scores across PlainCompare's 387-metro field

  1. 1
    Monroe, LA 100 cost score
    100% of the leader · rank #1 of 8
  2. 2
    Eagle Pass, TX 100 cost score
    100% of the leader · rank #2 of 8
  3. 3
    Dothan, AL 99 cost score
    99% of the leader · rank #3 of 8
  4. 4
    Texarkana, TX-AR 99 cost score
    99% of the leader · rank #4 of 8
  5. 5
    Enid, OK * 99 cost score
    99% of the leader · rank #5 of 8
  6. 6
    Hammond, LA 99 cost score
    99% of the leader · rank #6 of 8
  7. 7
    98% of the leader · rank #7 of 8
  8. 8
    98% of the leader · rank #8 of 8

Source Bureau of Economic Analysis Regional Price Parities, via PlainCompare life_scores · 2026-08-29

Understanding what each data dimension reveals, and where the numbers have limits.

Key Takeaway

Metro areas are defined by commuting patterns, not political boundaries, they capture the real economic geography. Cost of living (especially housing) is the most variable dimension, with housing costs differing 4x+ between cheap and expensive metros. Each data source measures something different: wages don't account for cost of living, crime rates don't account for reporting differences, and health data reflects communities, not individuals.

Affordability: Cost of Living vs. Income

Raw salary comparisons are meaningless without cost of living context. A $80,000 salary in Topeka, Kansas (RPP ~87) buys significantly more than $100,000 in Boston (RPP ~115). PlainCompare shows both wages and Regional Price Parities so you can calculate real purchasing power.

The formula: Real income = Nominal income ÷ (RPP / 100). An $80,000 salary at RPP 87 equals $91,954 in national-average purchasing power. A $100,000 salary at RPP 115 equals $86,957. The Topeka worker is financially better off despite a lower nominal salary.

Browse metro rankings by affordability to see which areas offer the best value.

Safety: Violent and Property Crime

PlainCompare shows FBI crime data broken into violent crime (direct threat to personal safety) and property crime (theft, burglary, financial loss without direct physical threat). These measure very different risks:

  • A metro with low violent crime but high property crime is generally safe to walk around but has a car theft or package theft problem.
  • A metro with high violent crime but low property crime may have concentrated violence in specific neighborhoods while most areas are safe.

Metro-level crime averages can mask neighborhood variation. Use PlainCompare for initial screening, then research specific neighborhoods within your target metros.

Jobs, Education, Health, and Environment

Jobs: BLS data shows employment levels and wages by occupation. Check whether your specific field is well-represented and well-paid in the metro, aggregate income numbers aren't useful if your industry is absent.

Education: NCES and Census data show school infrastructure and adult educational attainment. High bachelor's degree rates (40%+) correlate with stronger school systems, more professional services, and higher property values.

Health: CDC community health indicators reveal population-level health behaviors and outcomes. These affect your healthcare environment, insurance costs, provider availability, and the health culture of your community.

Environment: EPA air-quality data and FEMA disaster-risk indicators provide the environmental context in PlainCompare. Air quality affects long-term health, while disaster risk is a separate planning consideration. For climate normals, consult NOAA directly; they are not a Life Score input. Check metro pages for the available breakdown.

Frequently Asked Questions

What is a Regional Price Parity (RPP)?

An RPP is the BEA's measure of how much goods and services cost in a metro relative to the national average (100). An RPP of 110 means prices are 10% above national average. An RPP of 90 means 10% below. RPPs cover all consumer goods and services, with separate measures for housing, which varies most dramatically.

Why is housing the biggest price differentiator?

Housing RPPs range from 60 (40% below average) to over 200 (double the average). No other expense category varies this much. A median home in San Jose costs 4x what it costs in Memphis. This is why housing affordability is typically the dominant factor in cost-of-living comparisons.

What crime data does PlainCompare show?

FBI UCR data covering violent crime (murder, assault, robbery, sexual assault) and property crime (burglary, theft, vehicle theft) rates per 100,000 residents. Rates are more meaningful than counts because they normalize for population size. Some metros don't report to the FBI program, PlainCompare notes where data is unavailable.

How should I interpret healthcare-access data for a metro?

HRSA Health Professional Shortage Area (HPSA) designations show where a metro is short on primary care, dental, or mental health providers relative to its population. A high shortage score means longer waits and fewer options for care, it is a measure of provider availability, not the health status of residents.

What does the composite score mean?

PlainCompare's composite score combines multiple data dimensions into a single livability index. It weights affordability, safety, health, education, and environment into a normalized 0-100 scale. The score provides a quick comparison but should not replace dimension-by-dimension analysis, a high composite score can mask weakness in one area you care about deeply.

Can I trust FBI crime data?

FBI UCR data is the best available national crime dataset, but it has limitations. Not all agencies report in every year. Reporting practices differ between jurisdictions, some agencies are more aggressive about recording crimes than others. Comparing year-over-year trends within a single metro is more reliable than comparing absolute rates between different metros.

Sources

  • Bureau of Economic Analysis, FBI UCR, BLS OEWS, Census ACS, NCES, HRSA HPSA, EPA AQS

This content is for informational purposes only. Data represents statistical averages for metropolitan areas and may not reflect conditions in specific neighborhoods.

What to do with this

Affordability swings the most of any dimension, so start there when you screen.

  • Monroe, LA tops the cost-score field at 100, but check its other six dimensions before assuming affordability alone makes it the right fit. Browse affordability rankings
  • Pair a cost score with the matching wages score to see real purchasing power, not just sticker price. Compare framework
  • Percentile scores show relative position, not the underlying crime rate, rent dollar amount, or wage figure - open the metro page for the actual numbers.

Cost scores are recomputed from life_scores (vintage 2026-08-29); 387 metros scored fleet-wide.

A worked example

Use a real metro page to read the current affordability and wage percentiles together. That makes the method repeatable without turning an illustrative salary into a claim about your own income, taxes, housing, or commute.

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.

"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 rebuild after validated source extracts change. 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.

Every figure on PlainCompare is loaded directly from BEA, HUD, FBI UCR, BLS OEWS, NCES, DOL, EPA, and the Census Bureau, no number is typed in by an editor. This guide's figures are drawn directly from the same federal sources used across PlainCompare. See our editorial standards & corrections policy, the methodology behind these numbers, or report a data error. Data current as of 2026.