The United States ranks 20th out of 167 nations on prosperity. While this is a relatively high ranking, the American Dream Prosperity Index reveals that prosperity varies considerably across the 50 states and D.C., with Massachusetts exhibiting the highest level of prosperity and Mississippi the least. Similarly, the Index reveals that the level of prosperity within each of the 17 selected states also varies considerably, between different counties and parishes.

Local variation

Generally speaking, as illustrated by the chart, those states that exhibit the highest levels of prosperity have more top performing counties. In Nebraska (11th), for example, nearly two-thirds of its counties are in the 1st quintile (i.e., rank in the top 296 out of all 1,481 counties in the Index), and the remainder are in the 2nd quintile. Iowa (12th) has a very similar distribution, although the pattern for New York (13th) is quite different, with three-quarters of counties in the 2nd decile and 16% in the 1st quintile.

It is perhaps not a surprise, therefore, that those states that exhibit the weakest levels of prosperity also tend to have more weaker performing counties. In Louisiana (49th), for example, only one of its counties is in the 3rd quintile, 6 counties are in the 4th quintile, with the remaining 57 in the 5th quintile. While the pattern is somewhat similar in Mississippi (51st), we find that in New Mexico (47th) nearly one in five counties are in the 3rd decile and Los Alamos County is in the 1st decile. The performance of Los Alamos seems out of context with that of the other counties in the state, but nearly 65 percent of the jobs in the county are with the federal government, on nuclear research. 35 This highlights the importance of using other local information to bring greater understanding and insight to the data within the Index.

This broader spread of prosperity is illustrated more strongly by a number of other states in the Index, that act as microcosms of the U.S. as a whole, in terms of prosperity levels within them. Across California (25th), for example, there is much greater variation in the performance of its counties. Six counties reside in the 1st quintile and seven counties are in the 5th quintile, and the remaining 45 counties are fairly evenly spread across the 2nd, 3rd and 4th quintiles. As an illustration of the close proximity of prosperity variation, Santa Clara, one of the nine counties in the Bay Area, is the second most prosperous county in the state and ranks in the top quintile in the county Index, whereas neighboring Merced County, ranks 43rd in the county rankings in California and lies within the 4th quintile overall. Other states that exhibit such wide prosperity levels within them are Florida (31st), Montana (35th), Georgia (36th), and Texas (38th). Also, in Kentucky (43rd), there are six counties in the 2nd quintile and over a quarter in the middle quintile. Most of the weaker counties in Kentucky are in the Appalachian region in the South Eastern corner.

We also see a wide variation in performance of the 1,481 counties and parishes across the different aspects of prosperity. As illustrated by the chart, the spread of performance of each county and parish across the 10 pillars of prosperity relative to the overall U.S. average varies considerably.

Urban and rural differences

In addition to assessing the performance of counties within and across states, the Index also enables exploration of the performance of different types of counties, utilizing other datasets – urban and rural for example, using the U.S. Census Bureau’s classification. 36 This analysis reveals that, on the whole as evidenced by the chart, urban counties perform more strongly than rural counties, although this is not universally the case. In 2022, a third of rural counties had higher levels of prosperity than the average urban county. Furthermore, the more rural a county, the less prosperous
it tends to be, although again there are exceptions. Filmore County, Minnesota, for example, is ‘deeply rural’ with a population of around 21,000 but it ranks within the top 50 counties across the 17 states due to low crime and strong social capital, with one in two people in the county report doing favors for their neighbors, compared to less than one in three for Minnesota as a whole. Or consider urban Nassau County, New York, with a population density of over 4,500 people per square mile, which is roughly as prosperous as rural Mineral County, Colorado, which has fewer than one person per square mile.

Furthermore, the exact nature of prosperity composition varies across the two area types. Urban counties generally exhibit a stronger economic performance (especially infrastructure) and social wellbeing such as education and health, whereas rural counties have lower crime rates and stronger social networks.

Demographic variation within urban and rural areas

Reasons for disparities in prosperity at the local level are not entirely explained by location, although geographical features (e.g., mountains) can present physical challenges to greater prosperity (e.g., fast reliable Internet). To help ensure the most effective solutions are developed, these disparities need to be properly understood, for example, by understanding the experiences of different groups in society. Consider education, where we see considerable differences in outcomes across the main ethnic groups. For example, while 94% of the White American labor force and 94% of the Black American labor force have at least a high school diploma, this falls to 79% for the Hispanic or Latino labor force. 37 When considering those that continue on in education these disparities become more apparent. Prior to the pandemic, 43% of the White American labor force had attained at least a bachelor’s degree, compared to 34% of the Black American labor force and 24% of Hispanic or Latino labor force. We see similar disparities in health. Death rates from diabetes stands at 21.1 deaths per 100.000 population for White Americans, and contrasts with 46.8 for Black Americans and 30.9 for Hispanic Americans.38 Policies that seek to improve outcomes for the most disadvantaged Americans should be mindful of these differences and their underlying causes. Understanding how these national patterns are experienced at a local level is therefore important. Consider the variation in the death rate from diabetes for Black Americans, from 26.9 deaths per 100,000 population in Connecticut to 64.4 in West Virginia.

By utilizing population estimates from the Center for Disease Control and Prevention by ethnic group, and combining it with the score across different aspects of prosperity, in each of the 1,481 counties across the 17 selected states, a fairly basic assessment of how prosperity and its characteristics vary depending on the ethnic diversity of urban and rural counties can be produced.

For example, we can look at the experience of White and Black Americans in urban and rural counties.

As illustrated by the chart, Black Americans in urban areas and White Americans in urban and rural areas, experienced far similar levels of prosperity than Black Americans living in rural areas. In other words, Black Americans in rural areas are far more likely to live in counties that experience lower levels of prosperity.

We see this pattern across many different aspects of prosperity, although it is not universally the case. For example, Black and White Americans living in rural areas experience higher levels of safety and security than Black and White Americans living in urban areas. Moreover, Black Americans living in urban areas experience better infrastructure than the other three groups analyzed.

Summary

Place matters, but so does the demography of each place. Developing a clear understanding of the prosperity of each state and county and the challenges they face, particularly in relation to ethnicity and racial equity, and the opportunities that are presented is crucial to developing the most effective pathways to progress.

The Index enables the strengths and weaknesses of each state and county to be clearly identified, but to elicit greater insight and understanding about the challenges faced by particular groups within communities, more granular data is needed on their experience across different aspects of prosperity. Carrying out this data exploratory work is significantly hindered, however, by the lack of available datasets on these different groups in society being captured and reported on a consistent basis across the different dimensions of prosperity.