Methodology

Best Counties to Live ranks counties with a neutral, category-based score that users can rebalance around their own priorities. The public beta currently uses imported public datasets for its first partial scores while additional official county datasets are being added.

Beta data disclaimer

Current scores are partially generated from Census ACS 5-year county data, BLS unemployment data, BEA county economic data, Zillow county home value data, FBI reported crime data, and SEDA education data where available, plus beta property tax estimates. They should not be used as final rankings until remaining county-level datasets are fully imported, normalized, reviewed, and documented.

Default overall score

The default target formula blends six broad categories. During the beta, placeholder categories are excluded from the current overall score until real data is imported. Users can still disable a category or adjust the weights on rankings and map pages; active, available categories are rebalanced to total 100%.

Economy: 25%
Affordability: 25%
Schools: 20%
Safety: 15%
Taxes: 10%
Peace & Quiet: 5%

Peace & Quiet score

Peace & Quiet is designed to capture lower-friction living signals without using demographic or protected-class proxies. It currently uses public built-environment proxies, including population density, HUD-assisted housing density when configured, and high-risk retail or POI density when configured. Lower density generally improves the score. Missing HUD or POI source files are not treated as zero; the score is marked as a limited beta estimate until those feeds are added.

Low Crime: 30%
Low Density: 20%
Low Traffic: 15%
Low Vacancy/Blight: 15%
Low High-Risk Retail Density: 10%
Low HUD-Assisted Housing Density: 10%

Excluded variables

The scoring model intentionally does not use religion, race, ethnicity, national origin, disability, family status, age, sex, or other protected-class variables. It also does not include mosques, churches, synagogues, temples, or any religion-specific places in the score. Future data imports should preserve this constraint.

Current data coverage

ACS is currently used for median household income, poverty rate, median housing value, mean commute time, vacancy rate, and owner-occupied housing rate. BLS Local Area Unemployment Statistics are included in the Economy score when county unemployment records are available. BEA Regional GDP and Personal Income county data are used for real GDP growth and personal income growth where available. Zillow ZHVI county data is used for current home value estimates when available, with ACS median home value used as the fallback. Safety uses FBI UCR reported crime data where available, agency-level aggregation when direct county rows are incomplete, and modeled estimates from related public indicators when reported crime data is not reliable enough to use directly.

Economy currently combines BLS unemployment, ACS income, ACS poverty, BEA real GDP growth, and BEA personal income growth. Safety scores use reported crime data where available. When direct county data is incomplete or unreliable, we use agency-level aggregation or a modeled estimate from related public indicators. Missing crime is never treated as zero. Direct county-level FBI rows are preferred. When county-level rows are unavailable, city/agency records can be aggregated by county as a fallback using summed reported crimes over summed covered reporting population; the fallback does not average city rates. Modeled Safety scores are capped to avoid false precision or false-perfect results. Affordability currently combines home-price-to-income ratio, home value level, owner-occupied rate, vacancy/housing stability, and recent Zillow home-value growth pressure. It is still a beta estimate and should be treated as directional rather than final. Placeholder categories show as coming soon and do not affect the current overall score.

Crime inputs describe reported crime, not actual crime. Missing, blank, suppressed, absent, or incomplete reporting is not treated as zero crime. FBI UCR participation, agency coverage, and reporting completeness can vary by state, county, agency, and year, so the Safety score is a beta signal rather than a final or precise measure.

Schools uses public education achievement data from Stanford Education Data Archive county-level estimates as the first national baseline. Higher county achievement percentiles improve the Schools score. The score is a county-level estimate that will be refined over time as additional school and district sources are reviewed. Missing school data is not treated as poor school quality.

Taxes currently uses estimated property tax burden at the county level. Effective property tax is estimated from median real estate taxes paid divided by a typical home value, using Zillow ZHVI when available and ACS median home value as a fallback. Lower effective rates and lower estimated annual property tax burden improve the score. State and local tax burden uses WalletHub 2026 state tax burden data as the first practical state-level support input. The Taxes score is a beta estimate and will be refined over time.

Peace & Quiet now uses national county population density from generated population estimates and Census county land area. HUD and OSM/POI proxy fields are present in the generated data model and will be populated by later imports; until then, counties with only density available are marked limited. The score avoids race, ethnicity, religion, and protected-class variables.

What comes next

The import pipeline is being built around official county-level sources, starting with Census ACS 5-year county data. As each source lands, the methodology should identify the input, transformation, normalization range, and scoring direction before it affects public rankings.