MCDC News and Updates

Category: Economics

Story Map

Missouri Unemployment Rates, 2020-2021

Posted on by glenn

This December, our partners at the Missouri Spatial Data Information Service (MSDIS) present a swipe map comparing unemployment rates in Missouri counties during the years 2020 and 2021. This is a follow-up to the previous MSDIS map comparing Missouri county unemployment  between 2000 to 2020.

The left side of the swipe map shows unemployment by county for 2020, and the right side shows the rates for 2021.

Missouri Census Data Center frequently works with MSDIS on mapping and data projects. MSDIS is a spatial data retrieval and archival system offering many mapping resources, primarily focused on the state of Missouri.

Story Map

Missouri Median Income vs. Gas Prices

Posted on by glenn

This month’s story map examines trends in Missouri median household income in comparison to gas prices. Data about Missouri income comes from the 2016-2020 American Community Survey via the Missouri Census Data Center, and energy costs data are based off the Consumer Price Index from the United States Bureau of Labor Statistics. County-level gas prices have been taken from the AAA Missouri Gas Prices site, which updates each day.

Missouri Census Data Center frequently works with MSDIS on mapping and data projects. MSDIS is a spatial data retrieval and archival system offering many mapping resources, primarily focused on the state of Missouri.

Equal Employment Opportunity (EEO) Tables for 2006-2010

Posted on by glenn

MCDC is pleased to announce the debut of the 2006-2010 Equal Employment Opportunity (EEO) Tables in our data archive.

The Census Bureau’s EEO tabulations have served as the primary external benchmark for comparing the race, ethnicity, and sex composition of an organization’s internal workforce, and the analogous external labor market, within a specified geography and job category. These are used by organizations to develop and update their affirmative action plans.

MCDC currently has two sets of Equal Employment Opportunity tabulations (aka EEO tabs) in its data collection. In the next few months, we will be adding the latest EEO tabs (2014-2018) to our collection as well.

As always, please contact the MCDC website manager with any questions or comments.

Data Updates (Spring 2021)

Posted on by glenn

We’ve updated many of our population-related applications and datasets over the past couple of months.

As always, please contact the MCDC website manager with any questions or comments.

Map of the Month

Missouri’s Uninsured Population, Before and After ACA

Posted on by glenn

In March 2015, the U.S. Census released the 2013 data collected by the Small Area Health Insurance Estimates Program (SAHIE). The SAHIE data is a valuable reference that provides annual estimates of health insurance coverage for every county in the United States. That year, MCDC published a map showing insurance coverage rates for Missouri counties. The 2013 SAHIE data was of particular interest, as that was the last round collected before the first enrollment period of the Affordable Care Act (ACA, or “Obamacare”).

More than five years have passed since the Affordable Care Act was enacted, and we now have an opportunity to compare rates of uninsured persons across Missouri between 2013 and 2018. These two maps both use SAHIE data and the same value scale. (Note that the 2013 map shown here differs slightly from the one we published in 2015. This is due to a different classification scheme, but the underlying data is the same.)

Uninsured in Missouri, before and after ACA

Taking a look first at the 2013 map, we can see that the percentage of uninsured working adults aged 18-64 in Missouri ranged from a low of 11.6% in St. Charles County to a high of 29,3% in Knox County. All counties in the state had an uninsured working population of 11.6% or greater.

The picture is quite different in 2018. Almost all Missouri counties now have uninsured rates of less than 20%, with many under 15%, especially in the central areas of the state. A few counties in the Kansas City and St. Louis areas have uninsured rates of less than 10%.

More significantly, the number and rates of Missouri’s most-uninsured counties have gone down substantially. In 2013, there were 20 Missouri counties where more than a quarter of the adult population were uninsured. By 2018, there were none.

Despite the differences in uninsured rates over the five-year period, one thing hasn’t changed much: The number of hospitals. In fact, between 2013 and 2018, the number of Missouri counties that lack a hospital increased from 41 to 46, according to the Missouri Hospital Profiles By County list, maintained by the Missouri Department of Health and Senior Services (DHSS).

However, only eight of those counties — Hickory, Knox, McDonald, Morgan, Ozark, Shannon, and Wright — had uninsured populations of 20% or more in 2018. That compares with 15 counties without hospitals that had uninsured populations of 25% or more in 2013. So, the overall picture for access to affordable health care has improved.

In addition, the DHSS list of hospitals does not include smaller facilities such as rural clinics, which can better serve a rural population with higher insured rates.

Story Map

Women’s Role in the Missouri Workforce

Posted on by glenn
Illustration by Ankita Ackroyd-Isales

Although Women’s History Month has come and gone, it is important to continue thinking about the various trends facing women at work. Here, we examine workforce participation. Women’s participation greatly increased throughout the second half of the twentieth century, but beginning in 2000, it began to stagnate and decrease.

This story map, designed by Abby Hunt of the Missouri Spatial Data Information Service (MSDIS), offers a county-level look at female participation in Missouri’s economy.

The Missouri Census Data Center frequently works with MSDIS on mapping and data projects. MSDIS is a spatial data retrieval and archival system offering many mapping resources, primarily focused on the state of Missouri.

Map of the Month

Missouri Educational Attainment and Income

Posted on by glenn

Educational attainment is an established, validated predictor of income. This map-of-the-month series looks at the distribution of both characteristics in Missouri’s counties. Derived from the U.S. Census Bureau, American Community Survey (ACS) 2012-2016 5-year data, Missouri households are mapped here by level of educational attainment and median household income, while a bivariate choropleth map displays the variable impact of earning less than a high school diploma on household income.

Education vs. Income in Missouri, 2012-2016

The bar chart, based on the 2016 ACS 1-year release, establishes the relative distribution of median household income by level of education. While the overall median household in Missouri realizes approximately $36,000 in income, the median household in Missouri headed by someone without a high school diploma or GED is closer to $20,000.  Completing high school results in a bump of roughly  $10,000, with the median household income of high school graduates a little more than $30,000. Completing some college or an associate’s (2-year degree) results in an incremental increase in household median income to the mid-$30,000 range, but it is completion of a bachelor’s degree or greater that accelerates median household income into the mid-$40,000 to mid-$50,000 range annually.

Educational attainment, however, is not the only driver of income. Access to workforce opportunities and proximity to infrastructure impacts potential income too. Review of the Median household income map reveals the influence of infrastructure investment and population density in driving up wages and income, as seen in the counties shaded in the darkest green.  It’s also interesting to visually note the geographically layered gradation of quantiles of the state with the I-70 highway corridor connecting Missouri’s relatively high income metropolitan areas, and the agricultural northern tier of counties falling into the mid-quantiles, while lower income households concentrate in the southern tier of counties (with exception of income concentrating in the Springfield metro area).

Not surprisingly, a close look at the concentrations of level of educational attainment (the blue-scale maps), correlate at the county level to the median household income map fairly predictably: Populations with higher concentrations of higher levels of education also have higher median household incomes.

The bivariate choropleth map, Median household income by percent of adults with less than high school diploma or GED, lets us see the outliers as well as validating the correlations we anticipated. For example, the truer the shade of blue a county is coded, the higher the percent of the adult population without a high school diploma/GED and the higher median household income indicating some combination of higher wage job and income opportunities relative to educational qualifications. We see these on the periphery of the other end of the spectrum, counties with higher median household incomes and the lowest rates of households with low educational attainment, suggesting “bedroom” communities. Further study to confirm this pattern might include looking at patterns of in-migration over time and commuting patterns.

 

Map of the Month

Housing-Cost-Burdened Households Across Missouri

Posted on by glenn

The U.S. Census Bureau, in partnership with the federal department of Housing and Urban Development (HUD), calculate a measure of the percent of household gross income committed to paying for basic housing costs. If more than 30% of household gross income is spent on housing costs, a household is considered housing-cost burdened. The definition of cost burden considers monthly rental fees and utilities for rental housing and mortgage payments, second mortgage payments, utilities, real estate taxes, association fees, and homeowner’s insurance for owner-occupied households.

The concept of measuring a housing-cost burden emerged as a policy indicator during the implementation of the United State Housing Act of 1937 and has been used as a tool to understand trends in housing affordability trends since. Initially, a household was considered cost burdened if spending greater than 20% of household income on housing costs. The policy definition of cost burden has evolved over time. The currently used 30% was adopted in the early 1980s by HUD and has been used as a tool to inform both mortgage-lending policy as well as policy regarding supports for low-income, subsidized housing. Households paying greater than 50% of their gross income for housing are considered severely housing-cost burdened. The paper “Who Can Afford to Live in a Home”, published by the U.S. Census Bureau in 2006, provides a policy history and discussions of methodology and interpretation that remain useful.

The U.S. Census Bureau publishes 1- and 5-year estimates of this indicator with counties with populations of 60,000+ receiving annual estimates and smaller-population counties an annual 5-year estimate. In order to compare all Missouri counties, these maps consider the most recent 5-year estimate from 2012-2016. To understand the impact of housing-cost burdened households on Missouri’s communities, we have created six maps that consider:

  • all households,
  • rental households,
  • owner-occupied households with a mortgage,
  • owner-occupied households without a mortgage,
  • households headed by those under age 65, and
  • households headed by those age 65 and older.

Cost-Burdened Housing in Missouri, 2012-2016

Approximately 30% of all Missouri households fall into the category of housing-cost burdened, spending 30% or more of gross income on housing costs. Nearly 50% of households that rent are housing-cost burdened, whereas a quarter of owner-occupied households making a mortgage payment are similarly cost burdened.

Approximately one in five households led by householders younger than 65 are cost burdened, and approximately 7% of senior householders fall into this category.

A careful consideration of these maps provides some surprises to the conventional wisdom that housing costs tend to be greater in higher-population-density areas. It’s important to keep in mind that the housing-cost burdened indicator is measuring the ratio of household income required for shelter to what is available for other household needs. Simply, whereas housing costs and values do tend to be higher in more population-dense areas, wages tend to be too. When considering the distribution by quintiles across Missouri counties, generally, southern Missouri households are more likely to be cost burdened compared to their rural northern Missouri neighbors. As a region, the Lake of the Ozarks/Truman Lake area is the densest area of cost-burdened owner-occupied housing as well as senior housing, at least partially accounted for by the region’s desirability as a retirement and/or second home destination. For seniors, the Branson area also has a high percent of both senior and renter households paying 30% or more of their gross household income on housing costs. The I-70 corridor, including Kansas City, Columbia, and the St. Louis metropolitan area tends to be most expensive for renters and households under 65.

Map of the Month

Educational Attainment in Missouri

Posted on by glenn

Levels of educational attainment play a key role in determining long-term outcomes for individuals, households, communities, and even regional economies. One’s level of education plays an important role in one’s risk for unemployment as well as bounding opportunities for earnings and income.

Educational Attainment in Missouri, 2016

The chart, Unemployment rate and earnings by educational attainment, 2016, from the U.S. Bureau of Labor Statistics captures inverse correlation between risk of unemployment and median earnings by highest level of education achieved. In short, the more education one has, the less likely one is to be unemployed as well as to earn higher median wages. Those with less than a high school diploma are approximately twice as likely or more to be unemployed as those with an associate’s degree or higher, whereas those with an associate’s degree earn a median income that is half as much or less than those with a professional or doctoral degree.

The three maps in this series provide a geographic representation of:

  • less than a high school diploma,
  • a high school diploma, some college with no degree, or an associate’s degree, and
  • a bachelor’s degree or greater

These patterns illustrate the strengths and challenges faced within regions of our state in regard to economic viability, job and employment growth, and workforce readiness.

Startups Created More Than Two Million Jobs in 2015

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In 2015, the nation’s 414,000 startup firms created 2.5 million new jobs, according to data from the Census Bureau’s Business Dynamics Statistics (BDS). This level of startup activity is well below the pre-recession average of 524,000 startup firms and 3.3 million new jobs per year for the period 2002–2006.

Other BDS highlights include:

  • Job creation in the U.S totaled 16.8 million and job destruction totaled 13.7 million, for a net job creation of 3.1 million in 2015.
  • Young firms (those less than six years old) accounted for 11% of employment and 27% of job creation.
  • Old firms (those more than 25 years old) comprised 62% of employment and 48% of job creation.
  • The job creation rate for young firms, excluding startups, was 20% in 2015. This rate is above the Great Recession low of 15% in 2009, and it has recovered to its average level of 20% during the period 2002–2006.
  • The net job creation rate for establishments* in metro areas was 2.7%. For establishments in nonmetro areas, the rate was lower at 1.2%.
  • States with the highest net job creation rates in 2015 — 3.4% and above — are in the South Atlantic, Pacific and Mountain divisions.

The Business Dynamics Statistics are based on Business Register data, which covers all employers in the U.S. private nonfarm economy. This year’s release is limited to 13 tables; this temporary reduction in the number of tables will allow the completion of work to modernize the methodology that generates the Business Dynamics Statistics. The next release, planned for 2018, will provide an expanded set of tables that incorporate long-planned enhancements, including switching from the Standard Industrial Classification system to the North American Industry Classification System.

*A firm is a business organization consisting of one or more establishments under common ownership or control. An establishment is a single physical location where business is conducted or where services or industrial operations are performed. The firm and establishment are the same for single-establishment firms. Startup firms are new firms of age zero. See the BDS concepts and methodology page for definitions of job creation and net job creation rate.