According to Stanford RegLab, Black taxpayers receive IRS audit notices at least 2.9 times more frequently than non-Black taxpayers and possibly as much as 4.7 times more often.
The new study included research by Daniel E. Ho, the William Benjamin Scott and Luna M. Scott Professor of Law at Stanford Law School, faculty director of the Stanford RegLab, a senior fellow at the Stanford Institute for Economic Policy Research, Hadi Elzayn, a researcher at the Stanford RegLab, Evelyn Smith, Ph.D. candidate at the University of Michigan, and Arun Ramesh, a pre-doctoral fellow at the University of Chicago; Jacob Goldin, a professor of tax law at the University of Chicago; and economists in the U.S. Department of Treasury’s Office of Tax Analysis.
The researchers concluded that the disparity “is unlikely to be intentional on the part of IRS staff.”
The team’s research showed that a set of internal IRS algorithms causes racial differences in audit selection. Goldin compared them to the recipe for Coca-Cola: “It’s completely secret.”
To better understand this audit selection bias, the research team modeled the racial impact that various alternative audit selection policies might have.
The result showed how the IRS could change its secret algorithm to make it less unfair to people of different races.
“The IRS should drill down to understand and modify its existing audit selection methods to mitigate the disparity we’ve documented,” Ho said.
“And we’ve shown they can do that without sacrificing tax revenue.”
Although there have been long-standing questions about whether the IRS uses its audit powers somewhat, Ho said it was challenging to study because tax returns are private.
The IRS’s approach to audit decisions was confidential.
That changed when, on his first day in office, President Joe Biden signed Executive Order 13985. This order requires all federal agencies to examine how their programs affect racial and ethnic equity.
To apply that order to the IRS tax return audit program, economists at the Treasury Department worked with the Stanford RegLab team to analyze more than 148 million tax returns and about 780,000 tax returns for 2014. The RegLab team used anonymous data to do the analysis.
Even with all that information, the research team found that tax returns do not ask for a person’s race or ethnicity.
So, the team adapted and improved on a state-of-the-art approach that uses first names, last names, and geography (U.S. Census block groups) to predict the probability that a person identifies as Black.
And they confirmed their racial identification results using a North Carolina sample of voter registration records. In that state, until recently, when people registered to vote, they had to check a box for race and ethnicity.
After finding that Black taxpayers were 2.9 to 4.7 times more likely to be audited than non-Black taxpayers, the team looked at why this might be the case.
They suspected that the problem lay with an IRS algorithm’s use of the Dependent Database, which flags a potential problem and generates an audit letter to the taxpayer.
That instinct proved correct in that most racial differences were found in so-called “correspondence” audits. These audits are done by mail rather than in person.
The team also found that the IRS audits people more often who claim the Earned Income Tax Credit (EITC). The EITC helps low- and moderate-income people.
But claiming the EITC only explains a small percentage of the observed racial disparity.
The largest source of disparity occurs among EITC claimants. Indeed, Black taxpayers accounted for 21% of EITC claims but were the focus of 43% of EITC audits.
The racial disparity in audit rates persists regardless of whether EITC claimants are male or female, married or unmarried, raising children, or childless.
But it is most extreme for single male taxpayers claiming dependents (7.73% for Black claimants; 3.46% for non-Black claimants) and for single male taxpayers who did not claim dependents (5.66% for Black; 2% for non-Black).
Perhaps the most striking statistic is this: A single Black man with dependents who claims the EITC is nearly 20 times as likely to be audited as a non-Black jointly filing (married) taxpayer claiming the EITC.
Although the team does not know precisely what algorithm the IRS uses to choose audits, they thought of several possible reasons for high audit rates.
First, they tried an “Oracle” approach. They used a dataset called the National Research Project (NRP).
Because each tax return in this dataset was subjected to a line-by-line audit, the amount of underreported tax liability is known.
So the researchers looked at what would happen if the IRS selected taxpayers based on the known amount of underreported tax in the NRP dataset.
The result: The racial difference in audit selection flips.
The IRS would audit more non-Black taxpayers than Black taxpayers to catch the most underreported income tax.
The team also used the NRP dataset to train a model to predict the likelihood that a taxpayer has underreported income and the magnitude of a taxpayer’s underreporting for the entire 2014 dataset.
They found that an approach focused just on the likelihood that there’s underreporting of at least $100 would result in auditing more Black taxpayers (as was observed).
By contrast, focusing on the magnitude of underreporting (the amount of money unpaid by a taxpayer) would yield a result much closer to the oracle: More non-Black taxpayers would be audited than Black.
“The choice to focus on whether there is underreporting, as opposed to the magnitude of underreporting, is connected to broader structural sources of economic inequality and racial justice,” Smith said.
Because far more Black taxpayers have lower income, they have less opportunity to underreport substantial amounts of income, the researchers concluded.
By contrast, Smith said, “focusing audits on the amount of underreported income will disproportionately end up focusing on higher income individuals who are less likely to be Black taxpayers.”
Finally, the team wondered if the racial disparity in audits springs from IRS and congressional concerns about refundable tax credits, including the EITC and several others.
When someone claims one of these social security tax credits, they receive a refund even if they did not pay any taxes.
And some in government think it’s more important to avoid paying money to someone who claims it inappropriately than to collect all the tax dollars due from someone engaged in some other form of tax evasion.
To test the hypothesis that this approach would have a disparate impact on Black taxpayers, the team examined what would happen if the IRS focused audits specifically on the underreporting due to over-claiming of refundable tax credits (the EITC as well as two others) rather than total underreporting.
Their findings: This policy would result in Black taxpayers being audited at rates like what the team observed in the 2014 data.
Seventy percent of IRS audits happen through the mail, and 50% involve EITC claimants.
The team found that correspondence audits of EITC claimants are easy to trigger compared to labor-intensive field audits, cost very little, and require minimal effort by IRS personnel.
Unfortunately, the burden of correspondence audits on EITC claimants is more likely to fall on lower-income individuals, whose tax returns are less complex and less likely to lead to litigation, according to a recent study by the same research team.
In their new work, the team found that additional aspects of the IRS audit selection process have a racially disparate impact in the United States.
For example, even among correspondence audits of EITC claimants, the IRS devotes fewer resources to auditing EITC returns with business income.
The team concluded suggested that it’s because it would be more expensive to audit EITC returns with business income (about $385 per audit compared to $29 per audit for EITC claimants with no business income), Elzayn said.
And the team found this cost-saving measure has a disparate impact on Black taxpayers, who make up only 10% of EITC claimants reporting business income but 20% of EITC claimants who don’t report business income.
Yet even if IRS resource limits explain some of the racial disparities the team observed, they don’t explain all of them.
“Even holding fixed how many audits are devoted to EITC claimants who report business income, we still observe racial disparities,” Elzayn said.
The study’s authors have not made any formal recommendations for making the IRS audit selection algorithm more just.
Instead, they have written about the possible effects of alternative policies. This allows the IRS to reduce the racial impact of its system of choosing auditors.
These include predicting and focusing on the magnitude of taxpayers’ underreported income rather than just the likelihood of it; using IRS resources to audit more complex returns rather than focusing only on the simpler ones that are cheaper to audit; and viewing dollars as equal whether they are to be paid in refundable credits or received in taxes.
Before Biden signed the Racial Justice Executive Order that engendered this research project, the IRS needed more impetus and the ability to do that.
Now that they know the equity implications of how they select audits, Ho hopes they will tweak their confidential audit selection algorithm.
“Racial disparities in income are well known, and what the IRS chooses to focus on has big implications for whether audits complement, or undercut, a progressive tax system,” Ho said.