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Data Methodology

PlainCompare combines seven official U.S. government data sources into a single side-by-side comparison tool. Here is how each dimension is sourced and processed.

Data Sources by Dimension

Cost of Living

Source: Bureau of Economic Analysis (BEA) Regional Price Parities (RPP). RPPs measure price differences across U.S. metropolitan areas and states relative to the national average (100 = national average). An RPP of 115 means prices are 15% above the national norm.

Rent

Source: HUD Fair Market Rents (FMR). Published annually by the U.S. Department of Housing and Urban Development, FMRs cover studio through 4-bedroom units for metropolitan and non-metropolitan areas across all 50 states.

Crime

Source: FBI Uniform Crime Report (UCR). Violent and property safety statistics per 100,000 population, drawn from FBI Crime in the United States annual reports. Rates are computed using FBI-reported population figures.

Wages

Source: Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS). Annual occupational salary data covering hundreds of job categories at the metropolitan area level.

Schools

Source: National Center for Education Statistics (NCES). Public school enrollment, student-teacher ratios, and charter school counts at the metropolitan or county level.

Childcare

Source: U.S. Department of Labor childcare cost estimates. State and metropolitan-level median weekly childcare costs for infant and toddler care.

Environment

Source: U.S. Environmental Protection Agency (EPA) ECHO. Facility counts from the Toxics Release Inventory (TRI), Safe Drinking Water Act compliance records, and Superfund National Priorities List sites.

Processing Pipeline

  1. Each dataset is downloaded from its official government source and validated.
  2. Records are normalized to metropolitan statistical area (MSA) or state level as appropriate.
  3. All seven databases are loaded into a structured SQLite database keyed by geography identifier.
  4. Comparison pages query all seven databases in real time and display results side by side with winner highlights.

Data Vintage

Each dimension reflects the most recent data release from its source agency at time of database build. BEA RPP data typically lags by 1–2 years; FBI Uniform Reporting program data by 1 year; HUD FMR data is released annually for the upcoming fiscal year.

Editorial Workflow

Content on PlainCompare is compiled by our editorial team. Raw data from BEA, HUD, FBI Uniform Reporting program, BLS OEWS, NCES, DOL, EPA, Census ACS, and CDC PLACES is ingested programmatically by our ETL pipeline; narrative framing, metro guide text, rankings commentary, and methodology writeups are drafted by our editorial team and then reviewed line-by-line by the PlainCompare Editorial team at Kiznis Studio before publication. We follow rigorous editorial standards: source data is loaded directly from official agencies, never invented or interpolated. No page on PlainCompare is published without human review. We do not accept payment for coverage, placement, or rankings — composite scores and rankings are computed directly from the source agencies' data.

How the Source Agencies Collect Data

Each of PlainCompare's seven data dimensions comes from a different federal agency with its own data collection methodology. BEA Regional Price Parities are estimated from the Consumer Expenditure Survey and price data from the Bureau of Labor Statistics. HUD Fair Market Rents are computed from Census ACS rent data and updated with local housing market surveys. FBI Uniform Reporting program crime data is voluntarily reported by law enforcement agencies. BLS wage data comes from mandatory employer surveys. NCES school data is collected through annual mandatory surveys of school districts. DOL childcare costs come from state market rate surveys. EPA environmental data comes from mandatory facility reporting under federal environmental laws.

Data Accuracy Commitment

PlainCompare presents government data from each source without modification. Comparison pages display values exactly as published by each agency. We do not normalize across sources or adjust for differences in data vintage. Where data is unavailable for a particular geography from any source, we display it as unavailable rather than estimating. If you find any data that appears incorrect, please contact us at hello@plaincompare.com.

Limitations

Frequently Asked Questions

Which federal datasets does PlainCompare combine?

PlainCompare combines nine official U.S. government sources: BEA Regional Price Parities (cost of living), HUD Fair Market Rents (rent), FBI Uniform Reporting program (crime), BLS OEWS (wages), NCES (schools), DOL childcare survey (childcare costs), EPA ECHO/TRI (environment), Census ACS (demographics and housing), and CDC PLACES (community health indicators). Data is harmonized to metropolitan statistical area (MSA) and state level.

How often is PlainCompare data updated?

Each federal source operates on its own publication cycle — BEA RPP is annual, HUD FMR is annual, FBI Uniform Reporting program is annual with 10–18 month lag, BLS OEWS is annual, NCES is annual, DOL childcare is irregular, EPA is refreshed quarterly from ECHO, Census ACS is a rolling 5-year average updated annually, and CDC PLACES is annual. We monitor all sources and refresh within 30 days of each new release.

How are composite scores and rankings calculated?

Each metro receives a 0–100 percentile score on every dimension based on its rank within the full dataset. For "higher is better" dimensions (wages, schools) higher raw values earn higher percentiles; for "lower is better" dimensions (cost, crime, rent, childcare, environmental hazards) the rank is inverted. The composite score is a weighted combination across seven dimensions. Rankings are computed directly from the data — no editorial ranking or payment for placement.

What are the main limitations of metro comparisons?

Federal data is published at the MSA level, so conditions within a metro (urban cores vs. suburbs) can differ significantly. Publication lag of 12–24 months means rapidly changing markets may not be fully reflected. FBI Uniform Reporting program depends on voluntary agency reporting, so some jurisdictions under-report. Composite scores are inherently reductive — use them for initial screening and then examine individual dimensions that matter most to your decision.