Taxes are Racist

The IRS on Monday said that Black taxpayers are significantly more likely to face an IRS audit, confirming recent findings. IRS Commissioner Daniel Werfel said the agency is weighing changes to address the disparity.

A study released in January by economists at Stanford University, the University of Michigan, the U.S. Department of the Treasury and the University of Chicago found the IRS audits Black taxpayers about three to five times more than other Americans. Researchers based their assessment on microdata from roughly 148 million tax returns and 780,000 audits.

Those findings prompted questions from lawmakers during Werfel’s nomination process.

“While there is a need for further research, our initial findings support the conclusion that Black taxpayers may be audited at higher rates than would be expected given their share of the population,” Werfel wrote in a May 15 letter to the Senate Finance Committee.

Werfel said the IRS has dedicated “significant resources” to address the disparity, including a closer look at the agency’s automated processes and data used for exam selection.

Specifically, he vowed to examine algorithms for audits of filers claiming the earned income tax credit, or EITC, a tax break to low- to moderate-income workers. The EITC is more closely scrutinized because it’s refundable, meaning it still provides a refund even when the credit value exceeds taxes owed. Werfel stressed the IRS does not and will not consider race as part of the audit selection process, but the original research suggests the EITC has contributed to the disparity.

Senate Finance Committee Chair Ron Wyden, D-Ore., said the findings are a “shameful consequence” of racial discrimination that often shows up in government and private organization algorithms. “This bias is completely unacceptable regardless of where it occurs, and we have an obligation to stamp it out,” he said in a statement on Monday.

Wyden said the previous decade of IRS budget cuts made it “virtually impossible to enforce our tax laws fairly,” resulting in an “overreliance on these flawed algorithms.”