Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program? / Sergey Chernenko, Nathan Kaplan, Asani Sarkar, David S. Scharfstein.

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Chernenko, Sergey

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TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w31172.Publication details: Cambridge, Mass. National Bureau of Economic Research 2023.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: 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% 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.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w31172 (Browse shelf(Opens below))	Not For Loan

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April 2023.

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% 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.