Lack of disaggregated data clouds economic recovery for Black communities
Black communities have been disproportionately impacted by the coronavirus, but a lack of data is making it difficult for policymakers to target relief efforts.
Advocates argue that data broken down by race and ethnicity would lead to better policy from Washington, D.C., as the Biden administration continues to work through its $1.9 trillion package. Failure to do so may leave Black communities, already suffering steeper unemployment, farther behind in the economic recovery.
“Without the disaggregated data, it doesn’t allow us to tell the narratives to tell the nation the breadth and depth of what was caused by the pandemic,” said PolicyLink CEO Michael McAfee.
PolicyLink is an Oakland-based nonprofit that has advocated for more detailed data through the economic recovery. Disappointed with the lack of official data, PolicyLink has constructed its own dataset, the National Equity Atlas, to measure racial gaps and economic inclusion across the country.
Still, McAfee worries that policymakers in the nation’s capital are turning a blind eye to Black communities by not collecting more robust data as it rolled out its two relief packages last year.
For example, small business relief from the Paycheck Protection Program (PPP) asked applicants to fill out race and ethnicity fields. But because the form made those questions optional, 75% of loans included no demographic data.
The lack of data makes it nearly impossible to gauge the effectiveness of the program in getting to Black businesses that were particularly hard-hit by the pandemic. Private sector data from the JPMorgan Chase Institute shows that Black-owned businesses saw steeper cash balance losses in the depths of the crisis, compared to the average small business.
A similar problem exists in assessing the efficacy of stimulus checks.
After the first round of $1,200 Economic Impact Payments, the Treasury Department released a state-by-state breakdown of its disbursement but no data on who received — or didn’t receive — the checks.
A survey from the Federal Reserve Bank of Philadelphia illustrates the need for targeted support, with 30% of Black respondents worrying that the second relief package passed in December would not help their economic situation for long (compared with 23% of overall respondents).
Is more data always better?
Some government agencies have made efforts to disaggregate data. For example, the Bureau of Labor Statistics teamed up with several other agencies to collect a “rapid response” Household Pulse Survey through the pandemic.
Among the survey topics: the use of stimulus payments broken down by race and ethnicity, which showed that Black households were most likely to have reported needing the stimulus checks to cover expenses.
Shena Ashley, who leads the Racial Equity Analytics Lab at the Urban Institute, said better data will be important in the economic recovery especially as households turn to repairing and building their credit.
But Ashley points out that collecting more data comes with risks. Algorithms in credit scoring, for example, could lead lenders to further discriminate against Black borrowers.
“Which circumstances should we be collecting that kind of data? If there were a more robust conversation about that in the public space, it would be very helpful to people like us who use this,” Ashley said.
The need for more disaggregated data has come alongside calls for more data ethics and consideration to data privacy, especially as the Biden administration places a greater emphasis on better data collection.
Hours after his inauguration, President Joe Biden signed an executive order establishing an equitable data working group tasked with better disaggregating Federal datasets by race, ethnicity, and other demographic variables.
“A first step to promoting equity in government action is to gather the data necessary to inform that effort,” the administration said.
Brian Cheung is a reporter covering the Fed, economics, and banking for Yahoo Finance. You can follow him on Twitter @bcheungz.
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