Calculating regional price disparities at the county level using publicly available data.

Estimating County-Level Regional Price Parities from Public Data: A New Approach

March 27, 2024

ASowah@doc.gov

Wed, 03/27/2024 – 14:12

The concept of price differences between different places is a well-known economic principle. It is easy for consumers to recognize that the cost of living in New York City is significantly higher than in rural Texas. To quantify these differences, the Bureau of Economic Analysis (BEA) publishes regional price parities (RPPs). These RPPs use a weighted average of goods and services across different locations to allow for place-to-place price comparisons. They 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 a more granular level, such as the county level, can be useful for decision-making in areas such as policy, planning, and growth. To further these goals, a new working paper from the U.S. Office of Economic Analysis (OUSEA) documents the construction of experimental county-level RPPs using publicly available data. Additionally, an experimental data set with these county-level estimates is now available. While this data set is not an official government statistical product, it provides valuable insights into how price-related economic experiences may differ at the county level. This blog will highlight some of the top-level findings from the experimental data set, while the working paper provides a more detailed methodology.

Expensive Counties Tend to be in Metropolitan Areas

Similar to BEA’s official RPP data, these experimental RPPs are designed to average out to 100. RPPs above or below 100 indicate that a county is more or less expensive than the national average. When ranking all counties from most expensive to least, 8 out of the top 10 most expensive counties are located in a metropolitan area, as shown in Table 1. While it is expected that cities would be more expensive than their suburban or rural counterparts, the prices in these counties are significantly higher, with New York, NY (Manhattan) leading at 32.6% above the national average. Interestingly, these 10 counties tend to be clustered in the same metropolitan areas, with seven of them located in the New York, San Francisco, or Washington, DC metropolitan areas. When expanding to the top 20 most expensive counties, 13 of them are in these same three metropolitan areas.

Using Experimental RPPs to Show Price Differentials within Metropolitan Areas

Metropolitan areas, as defined by the U.S. Office of Budget and Management, are urbanized areas with at least 50,000 people, along with a high degree of social and economic integration and commuting ties. However, some metropolitan areas can be quite large, leading to significant price differences between counties within the same area. This gap between the most expensive and least expensive county within a metro can be substantial and highlights the importance of looking at price differentials at a more granular level. The experimental RPPs allow for a better understanding of these differences within metropolitan areas.

In Conclusion

The new experimental county-level RPPs and data set provide valuable insights into the price differences between different places. The data shows that expensive counties tend to be clustered in metropolitan areas, with significant price differentials within these areas. This information can be useful for policymakers, planners, and individuals making decisions about where to live and work. While this data set is not an official government product, it offers a new approach to understanding price differences and their impact on economic experiences at the county level.  

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