Geographic inequality has widened over the past four decades. The gap in incomes between richer places and poorer places has grown. Strikingly, geographic income inequality continued to climb in recent years even though many measures of overall income and wage inequality have narrowed somewhat as wage growth has been strongest for lower-wage workers.

Rising geographic inequality suggests that economic opportunities are becoming less even across the country. Increasingly unequal economic opportunity risks reducing households' ability to move to desired locations, concentrating economic and social challenges in certain places, or contributing to political polarization.

In this first blog post for the Department of Commerce’s Regional Economic Research Initiative, we document this increase in geographic inequality and draw out implications for further research and for government programs. Many of the programs in the Biden-Harris Administration’s Investing in America agenda target specific places, in part to reduce geographic inequality. The measures of inequality presented in this post will serve as one yardstick of success.

Local incomes have become more unequal over time

Geographic income inequality has risen more than 40% between 1980 and 2021. We measure geographic inequality as the variation in average income across all places in America -- metropolitan areas, micropolitan areas, and counties outside of metropolitan and micropolitan areas. This measure includes market income -- wages and other earnings as well as interest, dividends, and other capital income -- but not transfers. It increased from 0.22 to 0.31 over the past four decades.

Another way to measure this growth in per capita income inequality is to compare average incomes in a place near the top of the income distribution with one near the bottom. In 2021, per-capita average income was $69,000 in the place at the 90^th percentile of the income distribution (metropolitan New York) and $32,000 in the place at the 10^th percentile (Saginaw, MI, and Ashland, OH), for a ratio of 2.2. In 1980, this same 90^th/10^th percentile ratio was 1.7.

Other measures confirm the rise in geographic inequality. Using the same math, the spread in per-capita local Gross Domestic Product (GDP) also increased since 2001, the earliest year local GDP data are available. In fact, GDP is even more unequal across places than income is, as shown by the GDP-inequality line in the chart consistently above the income-inequality line.

Cost of living differences and transfers reduce geographic inequality

However, standards of living and wellbeing are probably less unequal than these income and GDP numbers suggest, for two reasons.

First is that high-income places are more expensive. For instance, incomes in 2021 in metro New York were more than double those in Saginaw, MI, as noted above – but local prices were also 26% higher in metro New York than in Saginaw, according to the Bureau of Economic Analysis’s regional price parities. That means that the gap between richer and poorer places is narrower when adjusted for the local cost of living.

Across all places, the inequality measure for 2021 falls from 0.31 in the baseline measure, as noted above, to 0.25 adjusted for cost of living. Also, the 90^th/10^th percentile ratio is 1.8 with the cost-of-living adjustment, compared with 2.2 as noted above. Still, this cost-of-living adjustment doesn’t change the trend: adjusted or not, geographic inequality grew in the US since 2008, when local cost of living data became available.

Second is that geographic inequality is lower when including transfer income, such as Social Security, Medicaid, and Medicare. The level of geographic inequality is lower for market income plus transfers (0.23 in 2021) than for market income alone (0.31 in 2021). That is because transfers tend to be higher in places where market income is lower, so transfers partially smooth out geographic differences. Furthermore, inequality in market income plus transfers has grown minimally since 2000 and actually dipped in 2020 and 2021, when transfers swelled during the pandemic.

Finally, geographic inequality might have declined in 2022 relative to 2021. Wage data through the fourth quarter of 2022 exhibit less geographic inequality than in 2021 and 2020. Full-year income data for 2022 will be available in November 2023.

The richest places are pulling away

Geographic inequality increased more because the richest places got richer than because poorer places fell further behind. Inflation-adjusted average per capita income in the median place increased 70% from 1980 to 2021. If all places had similar income gains over this period, then income inequality would have stayed relatively constant.

But incomes grew a bit more slowly in lower-income places, and much more rapidly in higher-income places. Toward the bottom of the distribution, income grew 55-57% in the places at the 25^th percentile, 10^th percentile, and near the very bottom, at the 1^st percentile. Growth was modestly higher at the 75^th percentile, much higher at the 90^th percentile, and dramatically higher – 172% -- near the very top, at the 99^th percentile.

Incomes are highest in the largest metros

What are these richest places? Among all metropolitan areas, the highest cost-of-living-adjusted incomes in 2021 were in Midland, TX, an oil-production center; San Francisco and San Jose, CA; Fairfield County, CT; and Naples, FL. The highest-income micropolitan areas were vacation and recreation communities, mostly in the Mountain West, like Jackson, WY; Heber, UT; and Hailey, ID.

On average, larger metropolitan areas have higher incomes than smaller places, even after adjusting for the cost of living, which also is higher in larger metros. This gap is large: incomes are 24% higher in large metropolitan areas than in smaller metropolitan areas, 39% higher than in micropolitan areas, and 51% higher than in counties outside of metropolitan and micropolitan areas. Many of the lowest-income communities are in rural America.

As noted above, transfer income somewhat offsets the geographic inequality of market income. Transfer income, again adjusted for the local cost of living, is highest in counties outside of metropolitan and micropolitan areas. Even with transfers, large metropolitan areas have the highest per capita income, but the gap is smaller than for market income alone.

One implication of larger places having higher incomes and income inequality rising is that American economic activity has become increasingly concentrated in a small number of places. The share of national income, not including transfers, earned in the largest 10 local economies rose from 31.6% in 1980 to 33.5% in 2021. The share of income in the largest 50 local economies rose from 58.7% to 64.5% over the same period. Economic activity has become more concentrated even though some large metros have gained population slowly or even lost population in recent years.

What it means, and what comes next

Geographic inequality has increased over recent decades, and economic activity has become more concentrated in the largest local economies. A few places have pulled far ahead, and many – especially smaller towns and rural areas – have fallen farther behind. Across the country, millions of people live in communities with few or dwindling economic opportunities. For some people, moving to places with more jobs and higher incomes is the answer, but for many moving is too costly or infeasible.

The Biden-Harris Administration is investing in numerous place-based programs. Some are designed to boost infrastructure, like high-speed internet, in underserved places. Others, like Tech Hubs, are designed to spread economic opportunity and innovation to places with assets and capacity outside the dominant economic centers.

Research and analysis are critical to the success of these programs. Our office at the Department of Commerce launched the Regional Economic Research Initiative to link place-based program data with local economic data to improve the design, implementation, and evaluation of these programs. As part of this initiative, we plan to publish a series of blogposts – this being the first – on regional economic trends and place-based efforts. Future blogposts in this series will look at places that have transformed over in recent decades, the effect of the pandemic on the location of economic activity, and more.

We are eager to hear your feedback, insights, and suggestions for future blogposts at [email protected].

Methodology notes

All measures of inequality in this blogpost are the standard deviation of the natural logarithm of local per-capita income or GDP, weighted by population of the geographic areas. We consider four measures:

1. Income. Our baseline income measure is nominal local per-capita market income, which includes wages and other earnings as well as interest, dividends, and other capital income. It is equal to personal income minus transfers.
2. GDP: nominal local per-capita Gross Domestic Product.
3. Adjusted income: nominal local per-capita market income, adjusted by regional price parities.
4. Income plus transfers: nominal local per-capita market income plus transfers. It is equal to personal income.

Local cost of living is the regional price parity all-items index (RPP) for metros; micropolitan areas and non-CBSA counties are assigned the RPP for the non-metro portion of their state. All income, GDP, and RPP measures come from the Bureau of Economic Analysis. The inflation adjustment used to compare real income growth at different percentiles is based on the CPI-R-US series from the Bureau of Labor Statistics.

Wage data through the fourth quarter of 2022 are from the Bureau of Labor Statistics’ Quarter Census of Employment and Wages. These wage data are a key input to BEA’s income measures. BEA is scheduled to publish the data needed to calculate full geographic inequality measures for 2022 in November 2023.

Metropolitan and micropolitan areas follow the 2020 OMB definition. All 384 metropolitan areas, 543 micropolitan areas, and 1272 counties outside metropolitan and micropolitan areas were included in the analysis. Specific places mentioned in this post are intended to provide context for readers to help them better understand the research and statistics presented.