The Good, the Bad, and the Ugly: Truths about Equity in the U.S. Paycheck Protection Program
This is the fourth post in the COVID Data Analysis series by NYC Opportunity’s Poverty Research Team. This post explores the U.S. Small Business Administration’s Paycheck Protection Program loan-level data to assess whether the funds have been distributed equitably in New York City.
In March of 2020, Congress created the Paycheck Protection Program (PPP) as part of the Coronavirus Aid, Relief, and Economic Security (CARES) Act, to provide loans to small businesses and self-employed individuals. With a $669 billion budget, PPP’s main objective was to preserve jobs during the initial lockdown in order to ensure small business continuity. The program, with the loan application process operated by private financial intermediaries, offered potentially forgivable loans to firms with fewer than 500 employees. The maximum loan amount was $10 million or 2.5 times the average monthly payroll costs, whichever was less. NYC Opportunity’s analysis of the U.S. Small Business Administration’s Paycheck Protection Program loan-level data¹ finds that in New York City, the funds disproportionally flowed to less affected industry sectors and to white and affluent neighborhoods. Firms in the hardest-hit sectors and in minority neighborhoods did relatively worse.
Industry Composition of Small Businesses with Fewer than 500 Employees in the City
From mom-and-pop corner stores to medical practices to tech start-ups, small businesses play a vital role in the city’s economy. Among the more than 240,000 businesses in New York City as of 2018, 99 percent were firms with fewer than 500 employees who were potentially eligible for PPP loan relief.² These small businesses employed more than half of New York City’s private sector workforce. With 34,046 firms, the retail trade sector including establishments ranging from grocery stores to gas stations and car dealerships accounted for nearly 15% of all small businesses in the city (See Figure 1). Close behind was the professional, scientific and technical (PST) services sector with approximately 12.1%. This sector includes accounting and law firms, scientific research and development, and management and consulting companies. Firms in the accommodation and food services sectors accounted for 10.7% of all small businesses in the city. Four industry sectors hit hard by the pandemic in terms of revenue and job losses — Accommodation and Food Services, Other Services, Entertainment, and Retail — together accounted for about 40% of all small businesses in the City.
The Good: The City’s Small Businesses Were Granted a Total of 155,123 Loans that Supported Approximately 1.4 Million Jobs
By August 8, 2020, there were 155,123 small businesses in New York City receiving potentially forgivable loans through the Federal Paycheck Protection Program (see Table 1 below). With the help of this $17.9 billion liquidity injection, the city’s small businesses temporarily maintained about 1.4 million workers on payroll. However, the evidence to date suggests that the impact on the eligible firms’ employment rates has been rather modest, with estimates ranging from an increase of 2 to 4.5 percentage points. This might be because the bulk of the funding went to businesses that would have kept their workers on payroll even without the loans, including businesses whose operations could be carried out remotely.
The Bad: Massive Inequity in Distribution of PPP Loans Across the City’s Business Sectors and Neighborhoods
In the city, the PPP loans disproportionally flowed to the industries that were relatively less adversely affected by the pandemic in terms of business revenue losses and declines in employment. Back in April 2020, a month when the city’s economy lost an unprecedented 887,000 private sector jobs, PST industries saw the smallest decline in their employment (about 5%) and no significant revenue changes, whereas the accommodation and food services sector lost nearly 70% of its payroll jobs due to the sharp drop in discretionary consumption induced by the pandemic. Nevertheless, the sector that received the most loans was PST, which received $2.8 billion, or about 15.9% of the total PPP dollars in New York City (see Panel A and B of Figure 2). Within the PST industry, the businesses that snapped up the most loans included:
- Law offices
- Management consulting services
- Marketing consulting services
In contrast, the accommodation and food service industry sector, which was deeply wounded by business shutdown and social distancing measures, drew only $1.7 billion, a little less than 10% of the total pool of money distributed in the city. Retail, another hard-hit sector that accounts for 15% of the city’s small firms with less than 500 employees, received 6.6% of the pie (about $1.2 billion). Similarly, other services such as hair salons, funeral homes, and dry cleaners also claimed 6.6% of PPP aid distributed within New York City. The apparent imbalance between the loan amounts and the industry’s employment decline is striking, yet it is only the tip of the iceberg.
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.
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.
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
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.
THE NYC OPPORTUNITY COVID DATA ANALYSIS SERIES
This series will continue to explore the U.S. Census Bureau’s Household Pulse data. In the current environment of persistently high unemployment, widespread income loss, and the absence of comprehensive stimulus benefits, it is important to monitor timely, detailed data. The Pulse data is one important tool that can help us to assess COVID-19’s impact as the pandemic evolves.
Previous blog posts in this series have examined the pandemic’s economic impact and recovery trends, and housing crisis. For more information on the Pulse data, including future releases, and NYC Opportunity’s use of the data see the NYC Opportunity website.
This publication of the COVID Data Analysis was written by Jihyun Shin (jshin@opportunity.nyc.gov) of the NYC Opportunity’s Poverty Research team.
The poverty Research Team at NYC Opportunity is responsible for the development of the NYCgov Poverty Measure. The alternative NYC Poverty measure, in comparison to the official U.S. measure of Poverty.
The work has received nationwide attention and contributed to the development of the Federal Supplemental Poverty Measure.
