Authors: Sergey Chernenko, Nathan Kaplan, Asani Sarkar, and David Scharfstein
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Staff Reports
Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?
Number 1060
May 2023
May 2023
JEL classification: G01, G21, G23, G28
We use the 2020 Small Business Credit Survey to study the sources of racial disparities in use of the Paycheck Protection Program (PPP). Black-owned firms are 8.9 percentage points less likely than observably similar white-owned firms to receive PPP loans. About 55 percent of this take-up disparity is attributable to a disparity in application propensity, while the remainder is attributable to a disparity in approval rates. The finding in prior research that Black-owned PPP recipients are less likely than white-owned recipients to borrow from banks and more likely to borrow from fintech lenders is driven entirely by application behavior. Conditional on applying for a PPP loan, Black-owned firms are 9.9 percentage points less likely than white-owned firms to apply to banks and 7.8 percentage points more likely to apply to fintechs. However, they face similar average approval disparities at banks (7.4 percentage points) and fintechs (8.4 percentage points). Sorting by Black-owned firms away from banks and towards fintechs is significantly stronger in more racially biased counties, and the bank approval disparity is also larger in more racially biased counties. We conclude that insofar as automation by fintechs reduces racial disparities in PPP take-up, it does so by mitigating disparities in loan application rates, not loan approval rates.
AUTHOR DISCLOSURE STATEMENT(S)
Sergey Chernenko
I declare that I have no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
Nathan Kaplan
I declare that I have no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
Asani Sarkar
I declare that I have no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
David Scharfstein
I was on the board of M&T Bank Corporation, which participated in the Paycheck Protection Program. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
I declare that I have no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
Nathan Kaplan
I declare that I have no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
Asani Sarkar
I declare that I have no relevant or material financial interests that relate to the research described in this paper. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
David Scharfstein
I was on the board of M&T Bank Corporation, which participated in the Paycheck Protection Program. Prior to circulation, this paper was reviewed in accordance with the Federal Reserve Bank of New York review policy.
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