In 2019, the average non-white male worker in Ohio made $12,000 less than the average white male worker in the state. The average white female worker made $19,000 less and the average non-white female worker made $23,000 less than the average white male worker in the state.
This is all according to American Community Survey data from the United States Census Bureau. Considering the number of workers in each category, the gap in earnings between white male workers and the other three categories came out to $560 million in 2019.
This gap has persisted over the past five years. While the earnings gap fell to $470 million in 2011, it ballooned 21% from 2011 to 2015 on the backs of higher earnings for white male workers. Since then, the earnings gap has persisted in the $560 million to $570 million range every year.
The total gap is largely driven by the earnings gap between white male workers and white female workers. This is because of both the large difference in earnings between white male workers and white female workers and the fact that for every non-white worker in Ohio there are more than three white female workers.
This is despite the fact that white women became a smaller portion over the workforce and grew their earnings more than any other category over the past decade. While Ohio’s non-white male workforce grew by 23% from 2010 to 2019 and its workforce of white males and non-white females grew by 11% each, only 5% more white women were working in Ohio in 2019 than in 2010. At the same time, they were earning 11% more after adjusting for inflation in 2019 than in 2010, higher than the 8% increase for white male workers and the 5% increase for non-white males and females.
Despite the earnings growth white female workers experienced in the past decade, the gap between white male earnings and white female earnings continued to grow due to the high baseline earnings white male workers enjoyed in 2010. The 4% ten-year increase in the white male/white female earnings gap pales in comparison to the 14% ten-year increase in the gap between non-white female and white male earnings and the 25% increase in the gap between non-white male earnings and white male earnings.
Secondary data collection for this analysis was conducted by Masashi Hamano. Analysis conducted by Rob Moore.