This blog post serves as the last of in a series of three posts that explore a dataset from the US Bureau of Labor Statistics (BLS) that includes unemployment rate data. The previous posts have looked at overall trends by educational attainment level and trends by race/ethnicity and gender separately. What we have seen is that increasing educational attainment improves unemployment rates for all adults in the data, especially persons of color, and that increased credentials also help close gaps between race/ethnicity groups within educational attainment levels. When reviewing trends by gender alone, there are small differences between male and female adults (25 years of age and older) in the data, even when stratifying the data by educational attainment. The monthly BLS data also showed that higher levels of educational attainment serve somewhat as a “recession-proofing” mechanism, as the effects of recessions are less profound for those with a bachelor’s degree or higher than for adults included in the other categories of educational attainment.
While the previous posts showed data broken out by specific demographic variables, this post analyzes how increased levels of educational attainment may differentially affect the unemployment rates across and within groups by combining race/ethnicity and gender variables. The visualizations below use data published from the US Census Bureau’s Current Population Survey (CPS). While the previous analysis showed data spanning almost 30 years, the unemployment data disaggregated by demographic variables and educational attainment levels has only been reported since 2015. These data are reported as annual averages by the BLS, so the following analysis will include six years of trend data. Because the data presented are unemployment rates, the better-performing groups have lower unemployment rates.
The first visualization below shows the six-year (2015-2020) average unemployment rate for the following combination of variables (moving left-to-right across the rows): Race/Ethnicity + Educational Attainment + Gender. Within each row, the color of the “lollipop” is based on which gender (women or men) had the worse (i.e, higher) unemployment rate within that Race/Ethnicity + Educational Attainment combination. For example, in the top row, women who were Black or African American with Less Than a High School Diploma had a slightly higher average unemployment rate (13.67%) than Black or African American men with Less Than a High School Diploma (13.61%). If you move down to the last row in the Black or African American group, you see that men in this race/ethnicity group with a Bachelor’s Degree or Higher had an average unemployment rate (4.39%) that was worse than Black or African American women at the same level of educational attainment (4.01%).
By way of observation…
As we have shown across three blog posts, higher levels of educational attainment promote better unemployment outcomes for all adults 25 and older, regardless of race/ethnicity, gender, or the combination of both. This was especially true during the 2020 pandemic, as higher levels of educational attainment served as a “recession-proofing” mechanism, where the rise in unemployment from 2019 to 2020 was lower for those with a bachelor’s degree or higher than the corresponding groups with an associate’s degree or less.
As higher education seeks to better understand and prepare to combat the continuing fallout of Covid-19, the unemployment rate data speaks to a growing concern for higher education leaders: the dramatic difference between the lowest two levels of educational attainment — Less Than High School Diploma and High School Graduate, No College. With some K-12 educational leaders observing double-digit increases in the high school drop-out rate over the past two years, the trickle-up effects of lower high school completion rates will squeeze a higher education pipeline that has already been damaged by the 2020 pandemic, where two-year colleges have seen dramatic decreases in student enrollment. For the health of colleges and universities moving forward, these trends at various stages within the enrollment pipeline should be of great concern. This is a topic that may be explored further in this blog as the data from K-12 schools becomes more readily available at scale in the months to come.