About PlainCost

Our Mission

We believe that understanding how far your money goes in different parts of the country should be straightforward and data-driven. PlainCost exists because the Bureau of Economic Analysis publishes detailed Regional Price Parities that measure price differences across every U.S. metro area and state — but that data is locked behind API endpoints, academic publications, and government report formats that most people will never access. We built PlainCost to make this information usable for everyone.

Our philosophy is to present cost of living data without lifestyle assumptions or hidden adjustments. Many cost-of-living tools use proprietary methodologies that blend subjective quality-of-life scores with economic data. PlainCost takes a different approach: we use the BEA's own price index — the only federally produced measure of geographic price differences — and present it transparently, broken down by spending category so you can see exactly where prices differ.

Why we built this: millions of Americans relocate each year, negotiate remote salaries, or simply wonder whether their income stretches further somewhere else. These are consequential financial decisions, and they deserve to be informed by rigorous government data rather than anecdotal impressions or proprietary scores. PlainCost is that resource — free, transparent, and built on the same data that federal economists use to study regional price variation.

Our Data Sources

All data on PlainCost comes from the U.S. Bureau of Economic Analysis (BEA), a statistical agency within the Department of Commerce. We do not use proprietary indexes, crowdsourced prices, or third-party estimates. Our specific data sources are:

• BEA Regional Price Parities (RPP) — Metropolitan Statistical Areas (MSA) — Price indexes for 384 metropolitan statistical areas, retrieved via the BEA Data API (apps.bea.gov/api, dataset: Regional, table: MARPP). RPPs are expressed relative to the national average (100 = national average). An RPP of 110 means prices are 10% above average; 90 means 10% below. The BEA breaks RPPs into subcategories: All Items, Goods, Services (excluding rents), and Rents.
• BEA Regional Price Parities (RPP) — States — Price indexes for all 50 states, the District of Columbia, and U.S. territories, retrieved via the BEA Data API (dataset: Regional, table: SARPP). These use the same methodology and subcategories as the metro-level RPPs, providing a complementary geographic view at the state level.

Both datasets include historical data from 2008 through the most recent publication year, enabling longitudinal analysis of how regional prices have shifted over time.

How We Process the Data

Our methodology transforms raw BEA API responses into the metro profiles, state comparisons, and salary calculators you see on PlainCost. The pipeline involves several stages:

Data acquisition: We fetch RPP data directly from the BEA Data API for both MSA-level and state-level geographies. API calls retrieve all available years and all four price categories (All Items, Goods, Services, Rents) in a single request per geography level. Responses arrive as structured JSON with FIPS codes, geography names, year, and index values.

Parsing and normalization: API responses are parsed and loaded into a structured SQLite database. Metropolitan area names are standardized (the BEA uses Census Bureau MSA definitions, which sometimes include multiple city names). FIPS codes are mapped to clean geography names. Multi-year time series are constructed for each metro and state to support trend analysis.

Salary equivalent calculation: Our relocation salary calculator uses RPP indexes to compute purchasing-power-equivalent salaries between metros. The formula is transparent: if you earn $X in City A (RPP = A) and move to City B (RPP = B), the equivalent salary is $X × (B / A). This provides a reasonable estimate based on regional price levels, though individual spending patterns will vary.

Indexing and caching: Pre-computed comparison tables, ranking pages, and metro profiles are built during data processing to ensure fast page loads. All calculations use the BEA's published RPP values without adjustment, rounding, or normalization beyond what the BEA itself applies.

Data Currency

Regional Price Parities have a publication lag because they require extensive economic survey data to produce. Here is how the timeline works:

• BEA RPP publication: The BEA releases updated Regional Price Parities annually, typically 18 to 24 months after the reference year. For example, 2023 RPPs are typically published in late 2024 or early 2025. The BEA also revises prior years when new source data becomes available.
• Historical coverage: PlainCost includes RPP data from 2008 through the most recent BEA publication year. This 15+ year time series lets you track how regional prices have evolved over time.
• Our update schedule: We refresh the database when the BEA publishes new annual RPP data. Between annual updates, the data remains static and reflects the most recent BEA release.

RPPs are annual averages and do not capture seasonal price fluctuations, short-term inflation spikes, or rapid changes in local housing markets. For the most current price information in a specific metro area, supplement PlainCost data with local real estate listings, utility rates, and cost surveys.

Editorial Independence

PlainCost is published by the Kiznis Studio editorial team. We compile, verify, and contextualize public data from the Bureau of Economic Analysis, HUD, Census, BLS, and related housing and demographic agencies. Methodology is documented above; corrections are published within 48 hours of any factual flag. The official source release (linked on every page) is always the authoritative reference for any specific number.

We do not accept payment, sponsorship, or promoted placement from landlords, cities, governments, or any covered entity. Our only revenue source is contextual display advertising served by Google AdSense — advertisers do not influence which entities we cover or how we present data, and they do not receive preferential placement.

Limitations and Disclaimers

Understanding what RPP data can and cannot tell you is important for making good decisions. Key limitations include:

• Price levels, not cost of living: RPPs measure differences in price levels across regions. "Cost of living" also includes income, taxes, commute costs, and quality-of-life factors that RPPs do not capture. A metro with high prices but also high wages may be more affordable in practice than a low-price metro with low wages.
• Metro-level granularity: RPPs are calculated at the Metropolitan Statistical Area level, which can encompass large geographic areas with significant internal variation. Prices in a downtown core may differ substantially from suburbs within the same MSA.
• Annual averages: RPPs represent annual average price differences. They do not capture seasonal variation, month-to-month changes, or the impact of sudden economic events like natural disasters or rapid population growth.
• Category limitations: The four RPP categories (All Items, Goods, Services, Rents) are broad aggregates. Individual spending patterns — such as someone who spends heavily on healthcare or childcare — may experience price differences that diverge significantly from the category averages.
• Salary estimates are approximations: Our salary calculator provides a useful starting point, but actual compensation depends on industry, role, employer, and local labor market conditions that RPP data does not capture.

Contact

We welcome questions about our data sources, methodology, salary calculator, or the cost-of-living information presented on PlainCost. If you notice an error in a metro or state profile, have feedback on how we present the data, or want to understand how a specific calculation works, we want to hear from you. We are also happy to assist journalists, economists, HR professionals, and relocation consultants who use regional price data in their work.

Email us at hello@plaincost.com.