How’s Your County Doing? A New Fed Tool Compares Socioeconomic Trends

March 20, 2019

Second to generational poverty, the issue having the greatest negative impact on people with low income is housing affordability, according to the Federal Reserve Bank of St. Louis Community Development Outlook Survey. Utilizing the Economic Resilience and Inclusion Navigator (ERIN), a new data tool developed by the St. Louis Fed, we are able to dive deeper into socioeconomic issues, such as housing affordability, to determine whether the data confirm or contradict what we are hearing from community and economic development practitioners.

The St. Louis Fed’s Community Development team, in collaboration with the Center for Learning Innovation and the Federal Reserve Economic Data (FRED) departments at the St. Louis Fed, developed ERIN to provide insight into trends taking place at the county level for every county in the U.S. We believe this trend analysis and the ability to compare across geographies will allow counties to more effectively gauge how they are doing over time and how their performance compares to that of their peers. ERIN includes 17 socioeconomic indicators, compiled by the St. Louis Fed’s team in consultation with both internal and external stakeholders. The indicators were chosen based on the following guiding principles:

  • data availability;
  • outcome-oriented indicators (e.g., travel time to work), as opposed to input-oriented indicators (e.g., access to public transportation);
  • relevance to community development practitioners; and
  • actionability—a practical tool to inform policies and programs.

The indicators have been organized into three broad domains—economy, household and community. The economy domain refers to indicators related to the health and resilience of an economy. The household domain refers to indicators related to opportunity at the individual or household level. Finally, the community domain refers to indicators related to community health and civic life.

Part of the St. Louis Fed’s district is southern Illinois. There are portions of the region where housing affordability varies substantially from one county to another. For instance, in Jackson County (which includes Carbondale), nearly four out of 10 households in 2016 were housing cost-burdened, defined as spending 30 percent or more of their income on housing. Utilizing ERIN, it is clear to see that the housing affordability trend in the county has been relatively flat for the last seven years. (See Figure 1.)

Figure 1

Housing Affordability in Jackson County, Ill., versus U.S.

Housing Affordability in Jackson County, Ill., versus U.S.

SOURCE: Census Bureau

Now that we know how Jackson County is doing with respect to housing affordability, we want to see how it compares to a peer county. By population size and geographic proximity, one county that can be considered a peer is Williamson County, Ill. Williamson borders Jackson to the east; its population is 67,640, whereas Jackson’s population is 59,032. While nearly four in 10 households in Jackson are housing cost-burdened, just over two in 10 households in Williamson are housing cost-burdened. Recognizing the difference in housing cost-burdened households between the two counties, see Figure 2 to see a side-by-side comparison of how each county performs on a number of indicators.

Figure 2

Jackson County versus Williamson County, Ill.

Jackson County, Ill.
Pop: 59,032
Median HH Age: 30.8
Williamson County, Ill.
Pop: 67,640
Median HH Age: 40.9
Data Indicator Name Value Value
Educational Attainment—
2-yr. degree or higher
44.7% 32.8%
Homeownership Rate 56.8% 74.2%
Disconnected Youth 2.8% 9.1%
Subprime Consumer
Credit Population
31.4% 28.3%
Single-Parent
Household Rate
36.4% 33.9%
Income Inequality 30.6 13
Housing Affordability 38.7% 23.7%
Combined Violent and
Property Crime (per capita)
445.5 452.4
Average Commuting Time
to Work
18.9 min 21.4 min
Poverty Rate 28.3% 14.9%
Racial Segregation 38.5% 28.7%
Building Permits
(per capita)
2.9 13
Unemployment Rate 6.2% 7.4%
Net New-Business
Formations
-3.6% -3.7%
New Patents (per capita) N/A N/A

SOURCES: Census Bureau, FBI, Federal Reserve Bank of New York/Equifax, Bureau of Labor Statistics

Some indicators, such as poverty rate or homeownership rate, might be what one would generally expect. For instance, the higher the poverty rate and lower the homeownership rate, the more likely it would be for families to be housing cost-burdened. Other indicators, such as educational attainment or unemployment rate, might seem counterintuitive. In this case, the county with the higher percentage of housing cost-burdened residents also has higher levels of educational attainment and a lower unemployment rate. For those looking to dive further into the data and look at how strongly these data correlate with each other or with other data sets, we allow all the raw data in ERIN to be downloaded for further analysis.

Another feature offered through ERIN is the ability to pull reports by state and by indicator—based on a given year or based on the change from a defined period of time. For instance, when analyzing the percentage of people in 2016 in Arkansas with a credit score below 660, or those considered subprime, one finds that the county with the lowest percentage of subprime residents is Baxter County, in north central Arkansas, with just under 21 percent. Conversely, the county with the highest percentage of subprime residents is Crittenden County, in northeastern Arkansas in the Memphis metropolitan statistical area (MSA), where nearly 45 percent of the residents have a credit score below 660. (See Figure 3.)

Figure 3

Subprime Consumer Credit Population, Arkansas Counties, 2016

Value County
20.8% Baxter County, AR
23.4% Newton County, AR
23.4% Polk County, AR
23.7% Marion County, AR
24.5% Fulton County, AR
24.6% Carroll County, AR
25.1% Benton County, AR
25.2% Cleburne County, AR
25.9% Izard County, AR
25.9% Searcy County, AR
37.4% Desha County, AR
37.9% Miller County, AR
38.2% Monroe County, AR
39% Mississippi County, AR
39.3% Chicot County, AR
40.9% Jefferson County, AR
41% Lee County, AR
43% St. Francis County, AR
43.3% Phillips County, AR
44.6% Crittenden County, AR

SOURCE: Federal Reserve Bank of New York/Equifax

Regarding analysis based on the change during a defined period of time, for example, we look at the change in homeownership rates in Missouri between 2012 and 2016. With a 6.3 percent increase, Caldwell County, in northwest Missouri, had the highest positive change in homeownership rate during this time period. Conversely, in the central Missouri county of Morgan, homeownership rates decreased the most in the state—10.5 percent—during the same period of time. (See Figure 4.)

Figure 4

Homeownership Rate, Missouri Counties, 2012-2016

County Change%
Caldwell County, MO 20.8%
Sullivan County, MO 6.3%
Washington County, MO 5.7%
Randolph County, MO 5.0%
Texas County, MO 4.6%
Reynolds County, MO 4.0%
Douglas County, MO 3.9%
McDonald County, MO 3.6%
Ripley County, MO 3.4%
Wayne County, MO 3.4%
Phelps County, MO -8.0%
Crawford County, MO -8.2%
Dallas County, MO -8.5%
Mississippi County, MO -8.7%
Barton County, MO -8.7%
Pulaski County, MO -9.4%
Maries County, MO -9.6%
DeKalb County, MO -9.7%
Taney County, MO -9.9%
Morgan County, MO -10.5%

SOURCE: Census Bureau

In addition to offering insights into housing affordability, ERIN can be useful in other ways:

  • If you are a financial institution or a nonprofit organization working in financial security, you might be interested in learning about the population in your county that has a subprime credit score.
  • If you work for an economic development agency, you may be interested in the trends in net new-business formations.
  • If you work for an organization focused on youth, you may want to learn the percentage of disconnected youth in your county and how it compares to that of peer counties.
  • If you are a researcher and would like to learn more about the correlation between indicators in ERIN, you can download the raw data to conduct further analysis.

Whether you represent a financial institution, a foundation, a university, a nonprofit service provider or a government agency, or you are an engaged citizen, ERIN can help you analyze trends taking place in your county and compare them to those of other counties.

Mike Eggleston is a community development advisor focusing on finance at the Federal Reserve Bank of St. Louis.

About the Author
Michael Eggleston
Michael Eggleston

Michael C. Eggleston is a manager of the St. Louis Fed’s Community Partnerships and Investment team. Read more about Mike’s work.

Michael Eggleston
Michael Eggleston

Michael C. Eggleston is a manager of the St. Louis Fed’s Community Partnerships and Investment team. Read more about Mike’s work.

Related Topics

Bridges is a regular review of regional community and economic development issues. Views expressed are not necessarily those of the St. Louis Fed or Federal Reserve System.


Email Us

Media questions

All other community development questions

Back to Top