MCDC News and Updates

Story Map

Women’s Role in the Missouri Workforce

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

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.

[Get a PDF version of this map ]

Map of the Month

Housing-Cost-Burdened Households Across Missouri

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

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

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.

Net jobs creation by state

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.

ACS Report

Nearly a Quarter of Veterans Live in Rural Areas

About five million (24.1%) U.S. veterans 18 years and older lived in areas designated as rural between 2011 and 2015, according to a new report (Veterans in Rural America: 2011–2015) from the U.S. Census Bureau’s American Community Survey (ACS). The report found that when considering demographic and economic characteristics, rural veterans were similar to urban veterans except for their median household income and employment rates.

Working veterans in urban and rural areas

Rural veterans had median household incomes more similar to those of rural nonveterans than urban veterans ($53,554 compared with $52,161 and $59,674, respectively). The poverty rate for all rural veterans was 6.9%. This rate increased by level of rurality, to a high of 8.6% for veterans in completely rural counties. Level of rurality is based on the percentage of the county population living in rural areas.

Working-age rural veterans (18-64 years old) had an employment rate of 66.0%, lower than rural nonveterans and urban veterans (67.7% and 70.7%, respectively). The employment rate of rural veterans decreased as the level of rurality increased. Employed rural veterans, however, were more likely to work full time and year-round than rural nonveterans (81.6% compared with 71.5%).

These findings use the ACS 5-year statistics released on December 8. Other highlights include:

Geography

Just under half of all rural veterans lived in the South (45.9%), followed by 26.4% in the Midwest, 14.1% in the West, and 13.7% in the Northeast.

Age

The median age of rural veterans was about 15 years higher than rural nonveterans and two years higher than urban veterans, and their age increased as the level of rurality increased. Rural veterans living in counties that were completely rural were the oldest, with a median age of 66.

Health Insurance

During the 2011-2015 period, 5.2% of all rural veterans and 15.4% of all rural nonveterans were not covered by any type of health insurance plan. Of the rural veterans who had health insurance during this period, 30.3% had private insurance only, 24.6% had public insurance only, and the remainder (45.1%) had a combination of private and public insurance.

New Census Estimates Compare School-Age Child Poverty to Prerecession Levels

According to U.S. Census Bureau estimates released this week, the poverty rate for school-age children increased in 928 U.S. counties between 2007 and 2013. Fifteen counties showed a decline in poverty rate over the same period, and there was no statistical change in 2,199 counties.

Percent change in poverty rate 2007-2013 for children ages 5-17, by county

The findings also show there were large concentrations in the South and West of the 972 counties with poverty rates statistically above the national average of 20.8% for school-age children. For example, in New Mexico and Mississippi, more than 80% of counties had poverty rates statistically greater than the national rate. Across the nation, 15% of school districts had poverty rates greater than 30% for school-age children.

Conversely, 902 counties had poverty rates for school-age children that were statistically lower than the national rate. In five states, 80% of counties had rates lower than the national rate: Connecticut, New Hampshire, North Dakota, Rhode Island, and Wyoming.

Poverty rate of children ages 5-17, by county, 2013

The statistics are from the Small Area Income and Poverty Estimates (SAIPE) program, which provides the only up-to-date, single-year income and poverty statistics for all counties and school districts — roughly 3,140 counties and nearly 14,000 school districts nationally. Data from the American Community Survey are an important input to these estimates.

The official poverty statistics for the nation were released in the fall of 2014, showing a decline in the poverty rate for children under age 18 from the previous year for the first time since 2000.

About the Small Area Income and Poverty Estimates

The Small Area Income and Poverty Estimates program provides statistics on the total number of people in poverty, the number of children younger than age 5 in poverty (for states only), the number of children ages 5–17 in families in poverty, the number younger than age 18 in poverty, and median household income. At the school district level, estimates are available for the total population, the number of children ages 5–17 and the number of children ages 5–17 in families in poverty. The estimates combine the latest data from the American Community Survey with aggregate data from federal tax records, the Supplemental Nutrition Assistance Program, decennial censuses, and the Population Estimates Program.

This release also includes 2013 Small Area Income and Poverty Estimates (SAIPE): An Overview, which presents income and poverty trends and explains the sources and approach.

Statistics from the SAIPE program are an input to the allocation formula for Title I of the Elementary and Secondary Education Act, which observes its 50th anniversary in April 2015. Title I distributes funding to school districts based on the number and percentage of low-income children. The U.S. Department of Education will use the 2013 estimates to allocate fiscal year 2015 funds for Title I and other Department of Education programs to states and school districts for use primarily in the 2015-2016 school year.

Census Report

Poverty Rate Declines, Number of Poor Unchanged

The nation’s poverty rate was 15.5% in 2013, down from 16.0% in 2012, according to the supplemental poverty measure released October 16 by the U.S. Census Bureau. The 2013 rate was higher than the official measure of 14.5%, but similarly declined from the corresponding rate in 2012.

Meanwhile, 48.7 million were below the poverty line in 2013 — not statistically different from the number in 2012. In 2013, 45.3 million were poor, using the official definition released in Sept. 2014 in Income and Poverty in the United States: 2013.

These findings are contained in the Census Bureau report The Supplemental Poverty Measure: 2013, released with support from the Bureau of Labor Statistics and describing research showing different ways of measuring poverty in the United States.

The supplemental poverty measure is an effort to take into account many of the government programs designed to assist low-income families and individuals that were not included in the current official poverty measure, released Sept. 16.

While the official poverty measure includes only pretax money income, the supplemental measure adds the value of in-kind benefits, such as the Supplemental Nutrition Assistance Program, school lunches, housing assistance, and refundable tax credits. Additionally, the supplemental poverty measure deducts necessary expenses for critical goods and services from income. Expenses that are deducted include taxes, child care and commuting expenses, out-of-pocket medical expenses, and child support paid to another household.

Estimates for States

The differences between the official and supplemental poverty measures varied considerably by state. The supplemental rates were higher than the official statewide poverty rates in the District of Columbia and 13 states: Alaska, California, Connecticut, Florida, Hawaii, Illinois, Maryland, Massachusetts, Nevada, New Hampshire, New Jersey, New York, and Virginia.

For another 26 states, supplemental rates were lower than the official statewide poverty rates. The states were Alabama, Arkansas, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Michigan, Mississippi, Missouri, Montana, Nebraska, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, West Virginia, Wisconsin, and Wyoming. Rates in the remaining 11 states were not statistically different using the two measures.

For more information about the supplemental poverty measure and how it differs from the official measure, see the U.S. Census Bureau’s blog post about this release.

New American Community Survey Data Released for 2013

The 2013 American Community Survey (ACS), released today in its one-year version, provides a multitude of statistics that measure the social, economic and housing conditions of U.S. states, counties, and communities. More than 40 topics are available with today’s release, such as educational attainment, housing, employment, commuting, language spoken at home, nativity, ancestry and selected monthly homeowner costs.

The ACS gives communities the current information they need to plan investments and services. Retailers, homebuilders, police departments, and town and city planners are among the many private- and public-sector decision makers who count on these annual results.

“The American Community Survey is our country’s only source of small area estimates for social and demographic characteristics,” Census Bureau Director John H. Thompson said. “As such, it is indispensable to our economic competitiveness and used by businesses, local governments and anyone in need of trusted, timely, detailed data.”

Also released today are two reports providing analysis on income and poverty for states and large metropolitan areas. The ACS three- and five-year data for 2013 will be released in October and December of this year, respectively.

Following are some highlights of the new ACS 2013 one-year release and related reports.

Income

  • For 2013, median household incomes were lower than the U.S. median ($52,250) in 28 states and higher in 19 states and D.C. (Three states did not have a statistically significant difference from the U.S. as a whole.)
  • In 2013, the states with the highest median household incomes were Maryland ($72,483) and Alaska ($72,237). Mississippi had the lowest ($37,963).
  • Median household income among the 25 most populous metro areas was highest in the Washington, D.C. ($90,149), San Francisco ($79,624), and Boston ($72,907) metro areas.

Income Inequality

Household Income: 2013 examined the Gini index for states and large metro areas. The Gini index is a summary measure of income inequality, ranging from 0 (complete equality) to 1 (complete inequality). Among the findings:

  • Five states and D.C. had Gini indexes higher than the U.S. index of .481; 36 states had lower Gini indexes than the U.S.
  • The Gini index of 15 states increased from 2012 to 2013. Alaska was the only state to have a decrease. All other states saw no significant change.
  • The highest Gini index was in the District of Columbia (0.532). Alaska’s (0.408) was among the lowest.

Poverty

  • Two states — New Hampshire and Wyoming — saw a decline in both the number and percentage of people in poverty. New Hampshire’s poverty rate declined from 10% in 2012 to 8.7% in 2013. Wyoming’s rate declined from 12.6% to 10.9%.
  • Three states saw increases in both the number and percentage of people in poverty between 2012 and 2013. New Jersey’s poverty rate increased from 10.8% in 2012 to 11.4% in 2013; New Mexico increased from 20.8% to 21.9%, and Washington increased from 13.5% to 14.1%.
  • In 2013, Mississippi had the highest poverty rate among states (24%), followed by New Mexico (21.9%). Both states also had the highest percentage of the population below 125% of the poverty level: 30.3% in Mississippi and 28.3% in New Mexico. About one in 10 people in both states had incomes less than 50% of the poverty level.
  • Among large metropolitan areas, one of the lowest proportions of people with incomes less than 50% of the poverty level in 2013 was 4.2% in the Washington, D.C., metro area, while one of the highest proportions was 8.4% in the Phoenix metro area.

Health Insurance

  • Between 2012 and 2013, 13 states and Puerto Rico saw a statistically significant increase in the percentage of civilians covered by health insurance. Two states (Maine and New Jersey) saw a decrease.
  • Among people whose incomes were below 138% of the poverty threshold, 25.6% were uninsured in 2013. (Under the Affordable Care Act, states have the option of expanding Medicaid eligibility to those with incomes at or below 138% of the poverty threshold.) Among people whose incomes were at or above 200% of the poverty threshold, 9.2% were uninsured in 2013.
  • Among the top 25 largest U.S. metropolitan areas, the uninsured rates were highest in Miami (24.8%), Houston (22.8%), and Dallas (21.5%) and lowest in Boston (4.2%), Pittsburgh (7.5%), Minneapolis (8.1%), and Baltimore (8.7%).
  • Among the top 25 large metropolitan areas, Tampa, Detroit, and Riverside, Calif., had public coverage rates of 33% or higher.

Computer and Internet Access

The 2013 American Community Survey included new questions to produce statistics on computer and Internet access. Mandated by the 2008 Broadband Data Improvement Act, the data will help the Federal Communications Commission measure broadband access nationwide. The data will also help identify communities eligible for available grants to expand access.

Some findings: 83.8% of the nation’s households have a computer (either desktop, laptop, tablet or smartphone). 74.4% have some form of Internet access at home. The Census Bureau is releasing a more detailed report on the new findings in early October.

Census Report

Gap Between Higher- and Lower-Wealth Households Widens

Median net worth increased between 2000 and 2011 for households in the top two quintiles of the net worth distribution — the wealthiest 40% of households — while declining for those in the lower three quintiles, according to statistics released recently by the U.S. Census Bureau. (Each quintile represents 20%, or one fifth, of all households.) The result: A widening wealth gap between those at the top and those in the middle and bottom of the net worth distribution.

where-is-the-wealth

According to the report, Distribution of Household Wealth in the U.S.: 2000 to 2011, median household net worth decreased by $5,124 for households in the lowest-net-worth quintile and increased by $61,379 (10.8%) for those in the highest quintile. Median net worth of households in the highest quintile was 39.8 times higher than the second lowest quintile in 2000, and it rose to 86.8 times higher in 2011.

The report also details a widening of the wealth gap for households sharing the same demographic characteristics, such as age, race and Hispanic origin, and educational attainment of the householder. For example, the median net worth for non-Hispanic whites in the highest quintile was 21.8 times higher than for those in the second-lowest quintile in 2000; in 2011, this had increased to 31.5 times higher. For blacks, the ratio increased from 139.9 to 328.1, and for Hispanics, the increase was from 158.4 to 220.9.

Between 2000 and 2011, the wealth gap has also widened between groups with different demographic characteristics. For example, the ratio of median net worth of non-Hispanic whites to that of blacks rose from 10.6 to 17.5 between 2000 and 2011, and the ratio of non-Hispanic whites to Hispanics also increased from 8.1 to 14.4.

“However, when looking at the highest quintile for these groups, we see that blacks experienced higher relative increases in median net worth than non-Hispanic whites and Hispanics,” Census Bureau economist Marina Vornovitsky said. For blacks in the highest quintile, median net worth increased by 62.8%, to $229,041; for Hispanics in the highest quintile, it increased by 17.9% to $250,462, and for non-Hispanic whites in the highest quintile, it rose by 11.9% to $754,244.

The Distribution of Household Net Worth and Debt in the U.S. detailed table packages were released for 2000, 2002, 2004, 2005, 2009, 2010 and 2011, the years for which data were collected.