Variations in Inflation across U.S. Metro Areas

December 01, 2022

KEY TAKEAWAYS

  • Some goods and services aren’t easily transportable, and many services are closely tied to a location. As a result, both local prices and inflation rates can vary across U.S. metro areas.
  • Regional differences in housing inflation were a key contributor to variations in inflation across metro areas. When housing was removed, metro area inflation rates began to converge.
  • The economic, demographic and cultural composition of households, as well as local labor market conditions, can help explain differences in regional inflation not fully captured by housing.

Inflation in the United States has risen sharply over the last year. As of October 2022, the consumer price index (CPI) had risen 7.7% annually.CPI data to calculate inflation are from the Bureau of Labor Statistics. In other words, consumers would need $107.70 to buy what cost $100 just a year ago. Research has highlighted several factors driving this high inflation: tight labor markets, a sharp rise in energy prices, supply chain disruptions and higher inflation expectations, among others.For more, see the October 2022 International Monetary Fund working paper “Understanding U.S. Inflation during the COVID Era” by Laurence M. Ball, Daniel Leigh and Prachi Mishra.

It may seem reasonable for one to think that this inflation rate would apply to the entire United States. After all, a $100 bill that is accepted in California will also be accepted in Missouri. Its value does not change when crossing state lines. Yet, inflation rates vary across U.S. metro areas, currently ranging from 12.1% to 6%.

Why is this? We know goods that are easily tradable—transportable at low cost—are most likely to have similar prices in different locations. A video game is going to cost roughly the same before taxes in both locations. If the video game was cheaper in St. Louis, a person in Los Angeles could easily buy it online and ship it to his or her house for a lower cost. This would cause stores in Los Angeles to drop prices to a similar level to compete or risk not being able to sell video games at all.

However, not all goods are easily transportable (e.g., perishable goods, such as fish, or goods that are expensive to transport, like concrete), and these prices can vary widely across locations.

Moreover, many services are also closely tied to a location. For example, if people want to attend a baseball game, they may face different ticket prices in different cities because it is unlikely fans would travel a far distance to see a cheaper game. Preferences for a certain team also play into the equation, given a Cardinals fan will be less inclined to travel to see a Cubs game regardless of whether it’s cheaper. The performance of the team can affect the prices further; a winning team may command a higher price, and losing teams may have to lower prices to attract fans.

Price Level vs. Inflation

For the reasons mentioned above, the prices of services and certain goods can vary across locations. Thus, the price level, or cost of living, in Los Angeles is higher than in St. Louis. However, price levels should not be confused with inflation. Inflation captures the rate of change in prices over a period of time, not the level of prices.

To compare price levels for metro areas, the Bureau of Economic Analysis (BEA) constructs a regional price parity (RPP) measure annually for prices in each area, whose national average is 100.See the BEA for RPP data for states and metro areas. So, if a metro area has an RPP of 110, it means $110 in that city would purchase the same quantity of goods and services as $100 in the average U.S. metro area.

To compare inflation rates for metro areas, one can use the CPI for the price of a basket of goods in some specific location at some point in time. Constructed by the Bureau of Labor Statistics (BLS), these price indexes can’t be used to compare price levels for metro areas because all CPIs for metro areas are normalized to have a value of 100 in 1982. Even if Los Angeles had a higher cost of living in 1982 than did St. Louis, both indexes are set to 100 in 1982, so a person can see how fast local prices rise or fall in a specific area regardless of what is going on elsewhere.

We can use RPP and the CPI to illustrate the difference between the current price level and inflation. The 2020 RPP, which is the most up to date, was 111.9 for Los Angeles and 95.7 for St. Louis, indicating that Los Angeles prices were 16.9% higher than St. Louis prices. From October 2021 to October 2022, however, St. Louis experienced a 7.0% inflation rate, while Los Angeles had a 7.5% inflation rate. In other words, living in Los Angeles is more expensive, but prices are rising in both cities at nearly the same rate.

Housing Costs Are a Key Factor

Housing accounts for a large portion of consumer spending, and thus the CPI. Changes in the cost of housing can be a major contributor to inflation in metro areas. It is important to note that this does not measure the purchase prices of homes, but rather the rental cost of housing. For homeowners, it is the amount they forgo by not renting out their spaces. The actual price of a house is not included because it is considered an investment and not consumption.See the May 2022 Brookings article “How Does the Consumer Price Index Account for the Cost of Housing?” by David Wessel and Sophia Campbell.

Unlike for many other goods and services consumed across the U.S., regional differences in housing inflation are likely to persist over time. This is because housing costs essentially capture the value of a region’s amenities and migration patterns, which tend to persist for decades. Shifts in household preferences for moving to a given region (e.g., retirees moving to the Sunbelt) would increase the demand for housing and push up prices faster than in other areas.

The figure below shows overall inflation rates (measured from October 2021 to October 2022) for the 21 metro areas in our sample. The rates range from 12.1% in Phoenix to 6.0% in San Francisco, a difference of 6.1 percentage points. Housing significantly contributes to the differences in metro area inflation rates. If we exclude housing costs from the CPI, inflation rates are less variable by metro area, ranging from 10.6% in Chicago to 7.2% in New York, a spread of only 3.4 percentage points. Still, variation remains, as we explore in more detail.

Inflation vs. Inflation Less Housing by Metro Area

A bar chart plots inflation as measured by the consumer price index from October 2021 to October 2022 for 21 U.S. metropolitan statistical areas against inflation less housing consumption over the same period for the same cities. 

SOURCES: Haver Analytics and BLS.

NOTES: Data are gathered from 21 metropolitan statistical areas (MSAs) in the United States from October 2021 to October 2022.

Different Regions, Different Consumption Baskets

Characteristics such as climate, as well as the economic, demographic and cultural composition of households in an area, explain some of the remaining differences in regional inflation. For example, a St. Louis household spends a greater share of its budget on heating than does a Los Angeles household because St. Louis typically has colder winters. A rise in heating prices will adversely affect the budget of the St. Louis household more than that of the Los Angeles household. Additionally, power sources vary across the nation, so regions utilizing coal or natural gas would be susceptible to price changes of these commodities, while regions relying on hydroelectric or solar sources for power may experience price changes due to other factors, such as drought.

This dynamic also occurs for goods that are culturally preferred, or relatively more abundant, in a region. For example, in metro areas where the average household consumes more beef, a surge in beef prices would raise inflation more than it would in regions that consume more fish.

Differences in Labor Market Conditions

Lastly, differences in inflationary pressures may also stem from differences in local labor market conditions. The most popular understanding of this relationship is called the Phillips curve. The theory suggests that when the labor market is tight, employers bid up wages to attract the workers they need and then raise prices to accommodate the higher labor costs.

The first scatter plot below shows this negative relationship between the unemployment rate and inflation for each of the 21 metro areas in our sample. Regions where the unemployment rate is historically low—when the unemployment rate was lower in October 2022 than in December 2019—tended to have higher rates of inflation in October 2022; the relationship is shown by the red regression line in the figure.

Inflation vs. Unemployment Rate

A scatter plot plots the difference in the unemployment rate between December 2019 and October 2022 for 21 U.S. metropolitan statistical areas against those cities’ October 2022 inflation rates. A downward sloping regression line between the points shows the negative relationship between the unemployment rate and inflation. 

SOURCES: Haver Analytics and BLS.

NOTES: The horizontal axis in each figure reports the difference in the unemployment rate between December 2019 and October 2022. This adjustment is made to account for structural differences across regions (such as in demographics or unemployment benefits) that lead regions to have different natural rates of unemployment. Data are gathered from 21 MSAs in the United States. Some plotted points overlap.

As other research has found, however, the variation in housing inflation tends to drive the Phillips curve relation.See Jonathon Hazell, Juan Herreño, Emi Nakamura and Jón Steinsson’s article, “The Slope of the Phillips Curve: Evidence from U.S. States,” which was published in the August 2022 issue of The Quarterly Journal of Economics. If housing is excluded from the CPI, as shown in the second scatter plot below, the Phillips curve becomes flatter; that is, the relation between changes in unemployment and inflation weakens.

Inflation Less Housing vs. Unemployment Rate

A scatter plot plots the difference in the unemployment rate between December 2019 and October 2022 for 21 U.S. metropolitan statistical areas against those cities’ October 2022 inflation rates less housing consumption. A flatter regression line between the points shows the weaker relationship between the unemployment rate and inflation. 

SOURCES: Haver Analytics and BLS.

NOTES: The horizontal axis in each figure reports the difference in the unemployment rate between December 2019 and October 2022. This adjustment is made to account for structural differences across regions (such as in demographics or unemployment benefits) that lead regions to have different natural rates of unemployment. Data are gathered from 21 MSAs in the United States. Some plotted points overlap.

This suggests that, at least on the regional level, the Phillips curve channel is not higher wages driving higher business costs but rather higher rents. However, it is likely that this correlation is not causality; both low unemployment and strong rent growth tend to be associated with economically vibrant regions, where people can easily find jobs and demand for housing is strong.

Notes

  1. CPI data to calculate inflation are from the Bureau of Labor Statistics.
  2. For more, see the October 2022 International Monetary Fund working paper “Understanding U.S. Inflation during the COVID Era” by Laurence M. Ball, Daniel Leigh and Prachi Mishra.
  3. See the BEA for RPP data for states and metro areas.
  4. See the May 2022 Brookings article “How Does the Consumer Price Index Account for the Cost of Housing?” by David Wessel and Sophia Campbell.
  5. See Jonathon Hazell, Juan Herreño, Emi Nakamura and Jón Steinsson’s article, “The Slope of the Phillips Curve: Evidence from U.S. States,” which was published in the August 2022 issue of The Quarterly Journal of Economics.
About the Authors
Charles S. Gascon
Charles S. Gascon

Charles Gascon is a senior economist at the Federal Reserve Bank of St. Louis. His focus is studying economic conditions in the Eighth District. He joined the St. Louis Fed in 2006. Read more about the author and his research.

Charles S. Gascon
Charles S. Gascon

Charles Gascon is a senior economist at the Federal Reserve Bank of St. Louis. His focus is studying economic conditions in the Eighth District. He joined the St. Louis Fed in 2006. Read more about the author and his research.

Jack Fuller

Jack Fuller is a research associate at the Federal Reserve Bank of St. Louis.

Jack Fuller

Jack Fuller is a research associate at the Federal Reserve Bank of St. Louis.

Views expressed in Regional Economist are not necessarily those of the St. Louis Fed or Federal Reserve System.


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