New Tool Reveals Potential GDP Gains from Closing Racial and Gender Gaps

June 24, 2021

Widespread racial, ethnic and gender economic disparities exist in the United States. These gaps represent lost potential—fewer innovations, less-diverse ideas, untapped talent and unrealized growth. Though these disparities most keenly affect minority communities and women, they also have an economic cost for everyone.

What exactly is that cost, and how much could the economy improve if the gaps didn’t exist?

Those are the exact questions that colleagues from across the Federal Reserve System and I set out to answer.We make up part of the Federal Reserve Racial Equity Learning Community, a group made up of community development staff formed to understand and address structural barriers that limit the full potential of communities of color. Views presented here are our own. The result was the creation of a data simulation tool offered for free to the public via Fed Communities, a website that highlights the Federal Reserve’s work in underserved communities.

Using the tool, one can visualize the estimated economic gain—measured by annual gross domestic product (GDP)—for each state and Washington, D.C.; this is the potential benefit stemming from closing racial, ethnic and gender gaps in the labor market.We defined closing gaps as raising the level of average hourly earnings, average hours worked, educational attainment and employment-to-population ratios to at least the level of the most historically advantaged group (non-Hispanic white men). When closing gender gaps alone, the comparison group is same-race men; when closing racial/ethnic gaps alone, the comparison group is non-Hispanic whites. In our approach, education is included in GDP calculations through adjustments to average hourly earnings. See the detailed methods section. Below is the image of part of the results available for Illinois.

Envision a US economy that works for everyone

A Thought Exercise—Closing Gaps

To formulate our estimates, we leveraged 15 years of data for adults ages 25-64 from the U.S. Census Bureau’s American Community Survey (2005-19). Our methodology is adapted from a similar analysis conducted on a national level by the Federal Reserve Bank of San Francisco.

We looked at actual levels of earnings, hours worked, educational attainment and employment-to-population ratios for different racial and ethnic groups, as well as for men and women.Hispanics may be of any race, while the categories of white, Black, Asian, American Indian, Alaska Native and all other races refer to non-Hispanic racial groups. Because of data limitations, we were able to look at only binary gender. The employment-to-population ratio is calculated as the state’s civilian labor force currently employed divided by its total working-age population. Using these variables, we estimated the labor component of aggregate GDP in the economy.This is not a general equilibrium model and is not intended to holistically describe state economies; simulated GDP in our calculation will differ from other GDP measures. See the detailed methods section. Then, we simulated what GDP could have been if gaps were closed. The difference between the two is our main outcome variable: simulated gains to GDP.

We found staggering racial, ethnic and gender disparities along these measures of labor market outcomes and opportunities. Thus, all states and Washington, D.C., economically benefited from closing the gaps in our simulation. The Federal Reserve Bank of St. Louis serves Arkansas and parts of Illinois, Indiana, Kentucky, Mississippi, Missouri and Tennessee; together, this area is called the Eighth Federal Reserve District. In these states’ economies, the estimated gains amounted to $282 billion per year. An increase in simulated GDP means the state as a whole would benefit; closing gaps is not a zero-sum game but instead results in added value to a state’s economy.

The Gaps and Gains for the Eighth District

In the table below, I present the potential gain that could have been realized by closing racial, ethnic and gender gaps in the Eighth District states. States vary widely in terms of economic output, population and racial distribution, which will all affect estimates of gained GDP. As a result, comparing states is strongly discouraged. Instead, it’s recommended that one look at an individual state’s existing gaps and the potential gain to closing those gaps.

Closing Racial, Ethnic and Gender Gaps in the Labor Market
 

Simulated Annualized Gain in GDP (in Billions)

 
State Closing Racial, Ethnic and Gender Gaps Closing Racial and Ethnic Gaps Closing Gender Gaps Simulated Baseline GDP (in Billions)
Arkansas $15 $4 $10 $43
Illinois $120 $38 $69 $280
Indiana $37 $6 $30 $120
Kentucky $19 $2 $16 $69
Mississippi $22 $8 $10 $41
Missouri $32 $5 $24 $110
Tennessee $37 $7 $27 $110
SOURCE: Federal Reserve simulation.
NOTE: The table shows estimates of how much each state in the Eighth Federal Reserve District could have gained annually from 2005 to 2019 if gaps in various labor market measures—average hourly earnings, average hours worked, educational attainment and employment-to-population ratio—were closed. Gains from closing gaps in the second and third columns will not sum to the first column. The baseline GDP in our calculation simulates the labor market component of GDP and will differ from other GDP measures.

Some examples of gaps are given in the next few paragraphs. Eliminating racial, ethnic and gender gaps in earnings was the largest contributor to the GDP gains across states. Large disparities exist in this labor market measure. The following are average hourly earnings from 2005 to 2019:

  • In Illinois, non-Hispanic white men earned $34 per hour, whereas non-Hispanic Black women averaged $23 per hour.
  • In Missouri, white men earned $27, while white women and Hispanic men earned $21.
  • In Arkansas, white men averaged $25, while Asian women earned $21, and Black men earned $19.

Educational attainment is another area with yawning gaps. In Indiana, 28% of white men had a bachelor’s degree or higher, whereas 23% of Black women and 19% of Hispanic women did. In Tennessee, 30% of white men had a bachelor’s degree versus 20% of Black men and just 12% of Hispanic men.

In Kentucky, the employment-to-population ratio for white men was 71%, whereas for American Indian and Alaska Native women it was 50%. These groups also had differences in the average number of hours worked per week, with white men working 44 hours and American Indian and Alaska Native women working 39 hours. In Mississippi, white men had an employment-to-population ratio of 76%, while Hispanic women had a ratio of 54%. Hispanic women also worked fewer hours per week, averaging 37 hours compared with the 45 hours among white men.

Clearly, gaps exist across various measures of economic well-being for a wide variety of groups. Curious about a different comparison or state? The data simulation tool presents labor market outcomes and educational attainment for gender, ethnic and racial groups.

An Equitable Economy

What if the economy worked for everyone? My colleagues and I explored the potential effect of closing racial, ethnic and gender gaps along various labor market measures and found the estimated economic gains were considerable. The gaps are a result of a legacy of discrimination, erected barriers, societal pressures and systemic constraints resulting in unequal opportunities. Solutions do exist, however, and their scope is varied—from self-education to systemic change. The data tool provides a clear view of the vast potential we all stand to gain by creating a more inclusive and equitable economy.

Notes and References

  1. We make up part of the Federal Reserve Racial Equity Learning Community, a group made up of community development staff formed to understand and address structural barriers that limit the full potential of communities of color. Views presented here are our own.
  2. We defined closing gaps as raising the level of average hourly earnings, average hours worked, educational attainment and employment-to-population ratios to at least the level of the most historically advantaged group (non-Hispanic white men). When closing gender gaps alone, the comparison group is same-race men; when closing racial/ethnic gaps alone, the comparison group is non-Hispanic whites. In our approach, education is included in GDP calculations through adjustments to average hourly earnings. See the detailed methods section.
  3. Hispanics may be of any race, while the categories of white, Black, Asian, American Indian, Alaska Native and all other races refer to non-Hispanic racial groups. Because of data limitations, we were able to look at only binary gender. The employment-to-population ratio is calculated as the state’s civilian labor force currently employed divided by its total working-age population.
  4. This is not a general equilibrium model and is not intended to holistically describe state economies; simulated GDP in our calculation will differ from other GDP measures. See the detailed methods section.

Additional Resources

About the Author
Ana Hernández Kent
Ana Hernandez Kent

Ana Hernández Kent is the senior researcher for the Institute for Economic Equity at the Federal Reserve Bank of St. Louis. Her research interests include economic disparities and opportunity, class and racial biases, and the relationship between psychological factors and the household balance sheet. Read more about Ana’s research.

Ana Hernández Kent
Ana Hernandez Kent

Ana Hernández Kent is the senior researcher for the Institute for Economic Equity at the Federal Reserve Bank of St. Louis. Her research interests include economic disparities and opportunity, class and racial biases, and the relationship between psychological factors and the household balance sheet. Read more about Ana’s research.

This blog offers relevant commentary, analysis, research and data from our economists and other St. Louis Fed experts. Views expressed are not necessarily those of the St. Louis Fed or Federal Reserve System.


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