The Good, the Bad, and the Ugly: Truths about Equity in the U.S. Paycheck Protection Program
By: Nyc Opportunity
Tags: Small Business, Poverty, Government, Equity, NYC

Small businesses that were in wealthy and majority-white neighborhoods with better employment outcomes and fewer COVID cases were more likely to receive a PPP loan (see Figure 3).³ The top five zip codes that benefited heavily from the PPP are in Midtown Manhattan, the city’s central business district that includes parts of affluent neighborhoods such as Chelsea (zip code 10001), Murray Hill (zip codes 10016 and 10017), Hell’s Kitchen/Midtown (10018) and East Midtown (10022) (Figure 3). A total of 19,345 businesses in these areas received $4.02 billion. The leading sector in these zip codes was PST services with 6,717 loans worth $1.7 billion or about 41% of the area’s total PPP funds ($4.2 billion). That is to be expected — Midtown Manhattan is a business center. But businesses in other high-income neighborhoods such as Hudson Square/Little Italy/SoHo/TriBeCa (10013) and Gramercy (10003 and 10010) also received hefty PPP money, totaling almost $1.3 billion, despite having a much lighter concentration of businesses.

By contrast, small businesses in communities of color that were hit hard by the coronavirus pandemic did not get much PPP loan relief. In Corona (zip code 11368), a densely populated neighborhood in north central Queens and home to a large immigrant population, only 837 businesses received federal PPP loans, totaling $55 million. Similarly, zip code 10453 (Morris Heights/Mt Hope/University Heights), a group of lower-income majority-Hispanic neighborhoods in the Bronx, received only $18.7 million, with a combined 516 loans. In these two zip codes, the borrowers tend to be micro-businesses, which explains the small size of the loans,⁴ but not the number of loans granted. Figure 4 highlights how the program failed to reach the firms in the neediest minority communities hammered by COVID-19. Only about 31% of PPP loans flowed to zip codes with populations where non-whites are a majority of the population.

Figure 4: Community Shares of PPP Loans

What explains the immense disparities in PPP lending across NYC neighborhoods and industry sectors? There could be multiple reasons. First, firms in lower-income, minority neighborhoods are often too small to have good payroll records and less likely to have strong relationships with mainstream financial institutions due to a decades-long history of financial exclusion, all of which put those firms at a disadvantage when applying for PPP loans.⁵ Second, given the fee schedule that is set forth under the PPP rules, participating lenders had an incentive to prioritize loans for bigger businesses or businesses with larger payrolls. Third, there are no fair lending provisions in the PPP regulatory directives that prohibit participating financial institutions from exercising gating or a preference system in processing applications. Restricting applications to existing customers or prioritizing some applications over others inevitably introduces fair lending issues that disproportionally hurt minority-owned businesses.

Our analysis of the loan-level data⁶ suggests that non-mainstream financial institutions, in particular smaller lenders, served the city’s communities of color and/or woman-owned businesses better than the large commercial banks (see Figure 5). JPMorgan Chase & Co is the top lender in the city by loan count (35,448 PPP loans), but they were less likely to serve firms in communities of color. Cross River Bank, a small community bank with only one branch in New Jersey, ranked 2nd by originating 14,775 PPP loans for the city’s small businesses and about 43% of their borrowers were firms in communities of color. Kabbage, Inc, an online small business lender, ranked 3rd in providing loans, to a total of 12,566 small firms, almost a half of which were in communities of color. Celtic Bank Corporation, the lender partnering with fintech companies Square and OnDeck, handed out 7,810 loans, roughly 40% of which went to businesses in the hardest-hit sectors and neighborhoods of color.

Fig 5: Lenders by the Percentage of PPP Loans to Women and Communities of Color

Looking at the city as a whole, businesses eligible for PPP were clearly underserved as a group. According to a report published by the NYC Comptroller’s Office, only 12% of eligible businesses in the city received PPP loans. States such as the Dakotas, Nebraska, and Iowa had up to 20% penetration of PPP loans for eligible businesses. What explains this geographic variation in PPP penetration? An analysis by Federal Reserve Bank of New York suggests that areas with higher shares of community banks had higher shares of PPP loans. Our city is still predominantly served by large commercial banks such as JPMorgan Chase & Co, Citigroup Inc., TD Bank, NA, and Bank of America Corp. These four large commercial banks churned out 42% of area total PPP Loans.

The Ugly: Gaming the PPP System

While many of the city’s smallest and minority-owned businesses were left empty-handed, multiple industries took advantage of the system. Staffing agencies (NAICS codes 561311 and 561312) are just one example of the diversion of PPP funds from where they were needed the most. In the city, 463 firms in the employment placement industry sector received a total of $194.8 million, with 42 getting more than $1 million each. ProPublica reported that many temp companies were able to double dip, getting paid twice for the same worker, once by their clients and then again by taxpayers. Many staffing agencies in the city with secured PPP loans also appear to have included external workers in their loan application (Figure 7); public records on their company size are often smaller than what they report on their application. It may not be illegal for temp agencies to claim external employees for purposes of registering for PPP loans, but it violates the basic intent of the loans, diverting millions of dollars of hard-earned taxpayers’ money intended to prevent layoffs in the hard-hit sectors

Fig 6. PPP Loan Amounts Received and Number of Jobs Reported by Staffing Agencies, NYC

The Road to Equitable Recovery for Small Businesses and their Workers Looks Fraught Without Reconsidering How Small Business Relief Funds Are Deployed

Instead of providing efficient and fair employee retention assistance directly through employers as has been done in the Netherlands, Australia, and many other countries, the U.S. government relied on commercial banks and other types of private lenders as intermediaries for delivery of assistance to employers and their employees. As illustrated above, it dramatically failed to reach the neediest businesses in the hardest-hit sectors and neighborhoods of color, leaving them and their workers vulnerable.

As we publish this blog, Congress has passed a $900 billion Coronavirus Relief Bill, which includes $284 billion in aid for small businesses. This new bill makes a few changes to the Paycheck Protection Program, including limiting loans to firms with fewer than 300 employees that can show more than a 25% revenue loss in any 2020 quarter compared with the same quarter in 2019. The bill also creates a simplified loan forgiveness application process for loans under $150,000 and specifies that business expenses paid with forgiven PPP loans are tax-deductible. However, the bill does not address the biggest problems with the first round of PPP, including use of financial intermediaries to deploy the funds, the perverse financial incentives embedded in the program, and the lack of regulatory measures to ensure fair lending practices in processing loan applications. Whether they are small or big, banks ultimate interest is not in ensuring equity in public-resource allocation decisions, but rather in maintaining their own bottom lines. The community banks are better equipped to serve local businesses and more focused on lending. But there are still risks that when the floodgate is opened, they will be most inclined to serve pre-existing customers who have built credit with them over time. Once again, well-connected businesses will be first in line to get loans while underbanked (or unbanked) micro-businesses are left at the bottom of the pile. Without fundamental changes in regulatory measures, better targeting of assistance towards the hardest-hit sectors, and possibly a direct delivery of PPP assistance to the neediest firms (perhaps using the Unemployment Insurance system, as in the Netherland’s model), it will be difficult, if not impossible, to achieve equitable economic recovery for small businesses and their workforces.

¹ The U.S. SBA’s detailed loan-level microdata file does not include information on applicants whose application was denied. The universe includes only the approved PPP loans.

² Nonemployers businesses such as independent contractors and sole proprietorships are not included in the counts of establishments from the Census Bureau’s County Business Patterns.

³Zip codes where whites make up more than 50% of the population are classified as majority-white neighborhoods. Minority neighborhoods are those zip codes in which the percentage of residents of a racial or ethnic minority is higher than that minority’s percentage in the city-as a whole.

⁴The PPP loan amount is calculated by multiplying the average monthly payroll of a business by 2.5

⁵ Financial exclusion at the household level in the same communities is documented at: https://www1.nyc.gov/assets/dca/downloads/pdf/partners/Research-UnAndUnderbankedNewYorkers.pdf

⁶On December 1, 2020, the Small Business Administration (SBA) released loan-level microdata files from the Paycheck Protection Program that disclose lender, geography, and borrower- and loan-level information including precise loan amount. For the present blog, the loan-level data used is limited to the five boroughs of New York City. The two key indicators- i.e., the number and the amount of loans — are aggregated at the Zip code level.