U.S. flag

An official website of the United States government

Dot gov

Official websites use .gov
A .gov website belongs to an official government organization in the United States.


Secure .gov websites use HTTPS
A lock () or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


  1. Home
  2. News
  3. Blog

Was this page helpful?

Estimating County-Level Regional Price Parities from Public Data

The idea that prices differ by place is a well-known economic concept. Most consumers could easily identify that a day in New York City would cost more than an identical day in rural Texas. To quantify these price differences, the Bureau of Economic Analysis (BEA) publishes regional price parities (RPPs). By using a weighted average of goods and services across places in a given year, RPPs allow place-to-place price comparisons and are available for all 50 states, the District of Columbia and 384 metropolitan areas. For example, RPPs show that goods and services in the most expensive state, California, cost nearly 30% more than in the least expensive state in 2022.

The ability to see these price differences at finer levels of geography may be useful for people making decisions about policy, planning, and growth. To further these goals, a new OUSEA working paper documents the construction of experimental county-level RPPs based on publicly available data. In addition, a new experimental data set with these county-level estimates are also now available. This novel data set is not a government statistical product nor is it meant to be interpreted as one. Instead, the data and methodology are meant to harness existing public data to explore how price-related economic experiences may differ at the county-level. The working paper details the full methodology; this blog describes top-level findings from the experimental data set.

Expensive counties tend to be in metropolitan areas

Like BEA’s official RPP data, these experimental RPPs are meant to average to 100. RPPs above or below 100 are more or less expensive than the national average.

Ranking all counties from most expensive to least, 8 of the top 10 most expensive counties are in a metropolitan area as seen in Table 1. While cities are typically more expensive than their suburban or rural counterparts, prices in these counties are substantially high with New York, NY (Manhattan) leading at 32.6% above the national average. Yet of these 10 counties, they tend to be in the same metropolitan areas. Seven of the ten are in the New York, San Francisco or Washington, DC metropolitan areas. When extending to the top 20 most expensive counties, 13 counties are in these same three metropolitan areas.

Using the experimental RPPs to show price differentials within metros

Defined by the U.S. Office of Budget and Management, metropolitan areas are urbanized areas with at least 50,000 people along with a high degree of social and economic integration and commuting ties. Understandably some metropolitan areas can be quite large, which can lead to substantial price differences between counties in the same metropolitan area. This gap between a metro’s most expensive and least expensive county can be understood as a price differential; in other words, how much more expensive is the most expensive county compared to the least expensive.

As seen in Table 2, the largest price differentials within metropolitan areas are notable. For example, among counties in the Washington, D.C. metro area, Arlington County, VA, is 37% more expensive than Madison County, VA. Most metropolitan areas have smaller price gaps than this; 86% of metro areas have a price differential of less than 10% between their most and least expensive counties. However, there are 54 metros with a price differential of 10% or more.

Top non-metropolitan area price differentials

Price differentials also exist in states’ non-metropolitan counties. Table 3 compares the most and least expensive non-metropolitan counties within a state. Numerous factors can drive a state’s non-metro county price variation; one county may have luxury resorts while another, hundreds of miles away, could be agriculture-heavy. What is clear is that these price differentials highlight non-metro residents within the same state may face substantially different price experiences.

Some counties with notable resort towns appear among the top 5 largest differentials, as seen in Table 3. Monroe County, FL, includes Key West, and Summit County, CO, has multiple ski towns. Leelanau, MI, is located on the shore of Lake Michigan and has a variety of summer home rentals and wineries. Of all the states, Massachusetts has the smallest non-metro price differential at 3.7%. Dukes County, MA, and Nantucket, MA, are the only two Massachusetts counties not in a metropolitan area, are geographically close, and are both popular vacation spots.


What it means and what’s next

The experimental estimates suggest there is substantial county-level price variation both within metropolitan areas and across non-metro counties. This illustrates that residents within the same metropolitan area may face considerably different prices and thus may have different purchasing power. Similarly, residents of non-metros counties face varying price differentials. For example, one non-metro county may have high housing costs due to being a resort town, another may have low housing costs, but expensive goods given its remote location.

This experimental dataset can have a variety of research applications to further understanding of how economic conditions vary across metro/non-metro counties and within metropolitan areas. From calculating county-level cost-of-living adjusted wages to grouping counties by similar price profiles, this dataset may be able to aid research on important and challenging questions.