Skip to main content

The FRED® Blog

Population and income disparity in the St. Louis MSA

Comparing St. Louis City and MSA population growth

FRED lives at the St. Louis Fed, which is in St. Louis City, which is adjacent to St. Louis County, which are all part of the St. Louis metropolitan statistical area (MSA).* Population and income vary widely across the region, so let’s see what FRED’s Census data can show us.

The graph above shows population for St. Louis City in red (left axis) and the entire St. Louis MSA in blue (right axis).

The city’s population is less than half of what it was 50 years ago: down from 622,236 in 1970 to 302,838 in 2018. The most drastic population declines were in the early 1970s and right after the Great Recession. Despite some steadiness in the 2000s, the city’s population has consistently fallen.

The MSA’s population also declines in the early 1970s, but it stabilizes in the next decade and then steadily increases at a rate of about 0.5% per year. The Great Recession chipped away at MSA population, but soon it stabilized. Its recent growth is way below the previous trend, but the MSA’s overall population has grown by about 10% over the past 50 years.

Comparing St. Louis MSA and U.S. population growth

Overall growth of the St. Louis MSA is actually dwarfed by national population growth and growth in other regions. U.S. population grew by 60.7% from 1970 to 2018. St. Louis is now the 20th largest MSA, a far cry from its standing in 1970, when it was 10th largest.

Comparing St. Louis City and County median income

The graph above shows St. Louis median income relative to U.S. median income for 1998-2018. St. Louis County’s relative median household income is in blue (left axis), and St. Louis City’s relative median household income is in red (right axis).

St. Louis County income is consistently above the U.S. median—initially by a large margin, almost 30% in 1998. St. Louis City income is consistently below the U.S. median—always in the range of 28% to 37%. This income disparity isn’t surprising for St. Louis area residents, who are aware of the wealthy county neighborhoods west of the city (e.g., Clayton, Frontenac, Ladue, Town and Country) and the poor neighborhoods in the city itself (e.g., Hyde Park, Fairground, North Riverfront).

How these graphs were created: First graph: Search for St. Louis resident population and select the city series. From the “Edit Graph” panel, use “Add a Line” to search for and select St. Louis MSA population. Second graph: Search for “Estimate of Median Household Income” and select the St. Louis county series. From the “Edit Graph” panel, use “Add a Line” to search for and select the St. Louis city series. With the “Format” tab, select and in each line add “Median Household Income in the United States.” Using the box for changing the formula, use “a/b” and click enter. For both: Use the “Format” tab to select the right axis for one series and adjust color and line thickness to your liking.

*The St. Louis MSA includes, beyond St. Louis City and County, the Missouri counties of Crawford, Franklin, Jefferson, Lincoln, St, Charles, and Warren and the Illinois counties of Bond, Calhoun, Clinton, Jersey, Macoupin, Madison, Monroe, and St. Clair.

Suggested by Alexander Monge-Naranjo.

View on FRED, series used in this post: MEHOINUSA646N, MHIMO29189A052NCEN, MHIMO29510A052NCEN, MOSSPOP, STLPOP

Pie charts for Pi Day

FRED offers a variety of keen ways to display data

March 14, aka 3/14, is Pi Day because the Greek letter pi represents 3.14 etc.

This post offers pie charts because the FRED Blog is not above using puns.

Now, these delectable pie charts cover a variety of topics from recent blog posts. Observe the appealing ways FRED can help you display data, and then click the headings to review the posts themselves.

Percentage of homeownership rate by racial and ethnic group in the U.S.

The price of a BLT sandwich

CO2 emissions from fuel by sector

How these graphs were created: It’s a simple recipe: To convert any FRED graph to a pie chart, go to the “Edit Graph” panel, open the “Format” tab, and select graph type “Pie.”

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: ANHPIHORUSQ156N, AORHORUSQ156N, APU0000702111, APU0000704111, APU0000712211, APU0000712311, BOAAAHORUSQ156N, EMISSCO2TOTVCCTOUSA, EMISSCO2TOTVECTOUSA, EMISSCO2TOTVICTOUSA, EMISSCO2TOTVRCTOUSA, EMISSCO2TOTVTCTOUSA, HOLHORUSQ156N, NHWAHORUSQ156N

Calculating the value of women’s unpaid work

U.S. women's unpaid labor basically equals the state GDP of New York

Yesterday was International Women’s Day, so FRED is taking the opportunity to examine one economic contribution from women that’s often ignored: The value of women’s domestic labor that goes unpaid.

For this calculation, we use Oxfam’s methodology: We calculate the total amount of hours that women spend doing unpaid household work and then use the minimum wage to put a dollar value on that work: 

  1. Take the number of women above age 16 and multiply by 26.7 hours, which is, according to the Bureau of Labor Statistics, the average number of hours per week women spend on unpaid household work.
  2. Multiply this weekly value by 52, the number of weeks in a year.
  3. Multiply the result by the federal minimum wage.
  4. Divide this annual dollar amount by the consumer price index to adjust for inflation. (Note we use annual data here, aggregated at the end of each year, to make the graph easier to read.)

OK. Nice graph. But how big a number is this? To put it in context, let’s compare the value of women’s unpaid labor with all the economic activity recorded in the state of New York.


Customize | Download data

For 2018 (the most recent data available), the dollar value of women’s unpaid work in the U.S. was equal to 86% of all the economic activity recorded in the state of New York. In other years—say, the late 1990s and late 2000s—the value of women’s unpaid work even surpassed New York state GDP. And keep in mind this value is at the low end of the possible range because we use the federal minimum wage and not, for example, higher state minimum wages let alone market wages that correspond to the specific work being done.

How these graphs were created: For the first graph: Search for and select the population of women (series ID LNU00000002). From the “Edit Graph” panel, use “Edit Line”/”Customize data” to search for and add the series for the federal minimum wage (series ID FEDMINNFRWG) and CPI (series ID CPIAUCSL). Adjust frequency to annual. Apply formula ((a*26.7*52*b)/c)*100. From the “Format” tab, choose graph type “Area” and change the color to International Women’s Day purple. For the second graph: Start with the first graph. From the “Edit Graph” panel, adjust the units for CPI to 100 in 2012. Then use the “Add Line” tab to search for and select New York state GDP (series ID NYRGSP). Apply formula a*1000. Finally, adjust the sample period to a time when both series are available.

Suggested by Diego Mendez-Carbajo.

View on FRED, series used in this post: CPIAUCSL, FEDMINNFRWG, LNU00000002


Subscribe to the FRED newsletter


Follow us

Back to Top