Federal Reserve Banks, Small Business Credit Survey: 2021 Report on Nonemployer Firms (2021)
Summary
Small Business Credit Survey 2021 Report on Nonemployer Firms from the Federal Reserve Banks, based on the 2020 survey of businesses with no employees other than their owners. The report team was Emily Wavering Corcoran, Lucas Misera and Ann Marie Wiersch of the Federal Reserve Bank of Cleveland. Its sections cover owner and firm characteristics, revenue and financial condition, pandemic-related emergency funding, PPP applications and outcomes, PPP nonapplicants, debt and financing. The key statistics table reports that 23.9% of nonemployer firms applied for financing, 59.3% had outstanding debt, 59.9% received at least some of the financing they sought and 32.0% were in poor condition.
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“Federal Reserve Banks, Small Business Credit Survey: 2021 Report on Nonemployer Firms (2021).”
Original at web.archive.org. Archived at Pandemic Darlings, https://pandemicdarlings.com/source-documents/federal-reserve-banks-small-business-credit-survey-2021-report-on-none-8f6d366633/
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SMALL
BUSINESS
CREDIT
SURVEY
2021 REPORT ON
NONEMPLOYER FIRMS
F E DE R A L R E SE RV E BA N K S
Atlanta • Boston • Chicago • Cleveland • Dallas • Kansas City • Minneapolis
New York • Philadelphia • Richmond • St. Louis • San Francisco
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 1
TABLE OF CONTENTS
I ACKNOWLEDGMENTS 11 LOOKING AHEAD
11 Performance Expectations, Next 12 Months
II EXECUTIVE SUMMARY
12 Expected Pandemic-Related Challenges,
Next 12 Months
1 DEMOGRAPHICS
1 Nonemployer Trends 13 DEBT & FINANCING
2 Firm Owner Characteristics 13 Debt Outstanding
3 Firm Characteristics 14 Financial Services Providers
15 Financing Demand and Outcomes,
4 PERFORMANCE & CHALLENGES
Prior 12 Months
4 Revenue Change and Financial Condition
16 Financing Needs and Outcomes
5 Financial Challenges and Reliance on
17 Loan, Line of Credit, and Cash Advance
Personal Funds
Sources
6 EMERGENCY FUNDING 18 Loan, Line of Credit, and Cash Advance
Application Outcomes
6 Pandemic-Related Emergency
Funding Needs
19 METHODOLOGY
7 PPP Nonapplicants
8 Applications and Outcomes
9 PPP Applications and Outcomes
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS i
ACKNOWLEDGMENTS
The Small Business Credit Survey is made possible through collaboration with business and civic organizations in communities across the
United States. The Federal Reserve Banks thank the national, regional, and community partners who share valuable insights about small
business financing needs and collaborate with us to promote and distribute the survey.1 We also thank the National Opinion Research
Center (NORC) at the University of Chicago for assistance with weighting the survey data to be statistically representative of the nation’s
small business population.2
Special thanks to colleagues within the Federal Reserve System, especially the Community Affairs Officers,3 and to representatives
from the US Small Business Administration; America’s SBDC, the nationwide network of Small Business Development Centers; the US
Department of the Treasury; the Consumer Financial Protection Bureau; the Opportunity Finance Network; Accion; and The Aspen Institute
for their ongoing support for the Small Business Credit Survey.
The 2020 Small Business Credit Survey and this report are the result of the collaborative effort, input, and analysis of the following teams:
REPORT TEAM4 OUTREACH TEAM
Emily Wavering Corcoran, Federal Reserve Bank of Cleveland Leilani Barnett, Federal Reserve Bank of San Francisco
Lucas Misera, Federal Reserve Bank of Cleveland Brian Clarke, Federal Reserve Bank of Boston
Ann Marie Wiersch, Federal Reserve Bank of Cleveland Joselyn Cousins, Federal Reserve Bank of San Francisco
Naomi Cytron, Federal Reserve Bank of San Francisco
SURVEY TEAM Peter Dolkart, Federal Reserve Bank of Richmond
Jessica Battisto, Federal Reserve Bank of New York Emily Engel, Federal Reserve Bank of Chicago
Mels de Zeeuw, Federal Reserve Bank of Atlanta Ian Galloway, Federal Reserve Bank of San Francisco
Rebecca Landau, Federal Reserve Bank of New York Dell Gines, Federal Reserve Bank of Kansas City
Lucas Misera, Federal Reserve Bank of Cleveland Desiree Hatcher, Federal Reserve Bank of Chicago
Ann Marie Wiersch, Federal Reserve Bank of Cleveland Melody Head, Federal Reserve Bank of San Francisco
Mary Hirt, Federal Reserve Bank of Atlanta
SURVEY ADVISORS Treye Johnson, Federal Reserve Bank of Cleveland
Claire Kramer Mills, Federal Reserve Bank of New York Jason Keller, Federal Reserve Bank of Chicago
Mark Schweitzer, Federal Reserve Bank of Cleveland Garvester Kelley, Federal Reserve Bank of Chicago
Steven Kuehl, Federal Reserve Bank of Chicago
PARTNER COMMUNICATIONS LEADS Michou Kokodoko, Federal Reserve Bank of Minneapolis
Grace Guynn, Federal Reserve Bank of Atlanta Lisa Locke, Federal Reserve Bank of St. Louis
Mary Hirt, Federal Reserve Bank of Atlanta Craig Nolte, Federal Reserve Bank of San Francisco
Drew Pack, Federal Reserve Bank of Cleveland
PARTNER OUTREACH LEADS Emily Ryder Perlmeter, Federal Reserve Bank of Dallas
Brian Clarke, Federal Reserve Bank of Boston Alvaro Sánchez, Federal Reserve Bank of Philadelphia
Janelle Williams, Federal Reserve Bank of Atlanta Javier Silva, Federal Reserve Bank of New York
Marva Williams, Federal Reserve Bank of Chicago
We thank all of the above for their contributions.
Emily Wavering Corcoran, Small Business Credit Survey Program Manager, Federal Reserve Bank of Cleveland
The views expressed in the following pages are those of the report team and do not necessarily represent the views of the Federal Reserve System.
1 For a full list of community partners, please visit www.fedsmallbusiness.org.
2 For complete information about the survey methodology, please see Methodology.
3 Joseph Firschein, Board of Governors of the Federal Reserve System; Karen Leone de Nie, Federal Reserve Bank of Atlanta; Prabal Chakrabarti, Federal
Reserve Bank of Boston; Daniel Sullivan, Federal Reserve Bank of Chicago; Emily Garr Pacetti, Federal Reserve Bank of Cleveland; Roy Lopez, Federal Reserve
Bank of Dallas; Teesha Miller, Federal Reserve Bank of Kansas City; Alene Tchourumoff, Federal Reserve Bank of Minneapolis; Tony Davis, Federal Reserve
Bank of New York; Theresa Singleton, Federal Reserve Bank of Philadelphia; Christy Cleare, Federal Reserve Bank of Richmond; Daniel Davis, Federal Reserve
Bank of St. Louis; and Laura Choi, Federal Reserve Bank of San Francisco.
4 The Report and Survey Teams appreciate the thoughtful comments, managerial support, and guidance from the following colleagues: Lisa Nelson from the
Federal Reserve Bank of Cleveland; Brent Meyer, Veronika Penciakova, Nick Parker, and Kevin Foster from the Federal Reserve Bank of Atlanta; and Barbara
Lipman and Marysol Weindorf from the Board of Governors of the Federal Reserve System. Valuable assistance with this publication was provided by Heather
Ann from the Federal Reserve Bank of Cleveland.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS i
EXECUTIVE SUMMARY
The COVID-19 pandemic affected small This publication examines findings for In some instances, this report references
businesses across the United States, with nonemployer firms and highlights the “larger” and “smaller” nonemployer firms
few escaping financial and operational differences in experiences between and employer firms. Smaller nonemployer
challenges as a result of declines in nonemployer and employer businesses. firms are those with $100,000 or less in
economic activity and actions taken to On average, nonemployer firms reported annual revenues; larger nonemployers are
reduce the spread of the virus. Among the larger declines in performance in the 12 those with more than $100,000 in annual
most impacted firms were the smallest months preceding the survey than employer revenues. Smaller employer firms are those
businesses—nonemployer firms—which firms, and nonemployers also more often with $1 million or less in annual revenues;
are businesses with no employees other struggled to access the funding necessary larger employers are those with more than
than the owner(s). Given nonemployers to keep their businesses afloat. This $1 million in annual revenues.
make up 81% of all small businesses in the report also underscores the importance
United States, understanding the impact of revenue size: Nonemployer firms with
Nonemployer firms widely reported
of the pandemic on those businesses and $100,000 or less in annual revenues faced
declining revenues between 2019 and
their ability to access emergency funding is more challenges and worse outcomes than
2020 and often turned to personal funds in
important in assessing the overall well- larger-revenue nonemployers, which often
response to financial challenges.
being of the small business sector. reported conditions similar to those of
smaller-revenue employer businesses. n Seventy-six percent of nonemployers
This publication focuses on the experiences
reported a decline in revenues in the 12
of nonemployer firms in the months leading
months prior to the survey. Just 13%
up to the pandemic and the first six months SURVEY FINDINGS reported revenue growth.
of the crisis. The report supplements the
findings from the 2020 Small Business The SBCS provides data on small business n Among all nonemployers, 32%
Credit Survey (SBCS) described in the Small performance, financing needs and characterized their financial condition as
Business Credit Survey 2021 Report on decisions, and borrowing outcomes. The “poor” at the time of the survey. Thirty-
Employer Firms, which explored outcomes 2020 SBCS, which was fielded in September six percent of smaller nonemployer
for businesses with 1–499 paid employees and October 2020, yielded 4,531 responses firms were in poor financial condition;
other than the owner(s). Nonemployer from nonemployer firms (hereafter this figure falls to 23% for larger
firms are distinct from employer firms in “nonemployers,” or “nonemployer firms”) in nonemployer firms.
more than just the employment size of the all 50 states and the District of Columbia.
business. Nonemployers are concentrated This report also includes findings from a n Eighty-one percent of nonemployer
in different industries and are more likely sample of 9,693 small employer firms— firms experienced some type of financial
to be owned by women and people of color. that is, firms with 1-499 full- or part-time challenge in the 12 months prior to the
While some nonemployers are gig workers employees (hereafter “employers,” or survey. Compared to employer firms,
supplementing their income, a majority “employer firms”). nonemployers more often turned to
of the respondents in the SBCS sample personal funds and reported some
reported that their firm was the primary impact to household finances as a result
source of income for their household, of those challenges.
and a quarter of them planned to become
employer firms within the next year.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS ii
EXECUTIVE SUMMARY
(Continued)
Nonemployer firms accessed COVID- As the availability of emergency funding ABOUT THE SURVEY
related small business assistance at increased, demand for traditional financing
lower rates than employer firms, though fell among nonemployers between 2019 The SBCS is an annual survey of firms with
many nonemployer firm owners received and 2020. Nonemployer firms that did fewer than 500 employees. Respondents
enhanced unemployment benefits. apply for financing were less likely than are asked to report information about their
employer firms to receive the full amount business performance, financing needs
n While 91% of employer firms completed they sought. and choices, and borrowing experiences.
an application for emergency assistance Responses to the SBCS provide insights on
funding, just 66% of nonemployers n Twenty-four percent of nonemployers the dynamics behind lending trends and
completed an application. However, 30% applied for financing in the 12 months shed light on various segments of the small
of nonemployer firm owners reported prior to the survey, a decline from 29% in business population.
collecting unemployment insurance the 2019 survey period.
benefits.
n More than one in three nonemployer
n Smaller nonemployer firms were less firms received none of the financing
likely than larger nonemployer firms for which they applied. Among smaller
to apply for and receive emergency nonemployer firms, 42% received none
assistance funding. While 62% of smaller of the financing they sought. The same
nonemployers sought and received was true for 35% of larger nonemployer
assistance, 78% of larger nonemployers applicant firms.
did so.
n Compared to employer firms that
n The Paycheck Protection Program (PPP), applied for financing, nonemployers
which was the most popular emergency firms that applied were less likely to
funding program for employer firms, seek financing at small banks (30% vs.
was far less commonly used by 43% of employers) and more likely to
nonemployers. Thirty-five percent of turn to online lenders (25% vs. 20% of
nonemployers applied for a PPP loan, employers).
as compared to 82% of employers.
Nonemployers that did apply for a n Across the most common sources of
PPP loan were less successful than loans, lines of credit, and cash advances,
employers at obtaining the funding they nonemployer applicant firms were more
sought. likely to be at least partially approved at
small banks (56%) than at online lenders
(50%) or large banks (41%).
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS iii
DEMOGRAPHICS
Nonemployer Trends
81% of small businesses are nonemployer firms—firms with no employees other
than the business owner(s).
NUMBER OF SMALL BUSINESSES, 1998–2018 1,2
Nonemployer firms
Small employer firms
35
30
Number of firms (millions)
25
20
15
10
5
0
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018
NUMBER OF NONEMPLOYER FIRMS 3
2018
26,485,532
2013 23,005,620
2008 21,351,320
2003 18,649,114
1998 15,708,727
1 Data for small employer firms is sourced from US Census Bureau’s Statistics of US Businesses.
Data for nonemployer firms is sourced from US Census Bureau’s Nonemployer Statistics.
2 Small employer firms are businesses with 1–499 employees.
3 Sourced from US Census Bureau, Nonemployer Statistics.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 1
DEMOGRAPHICS
Firm Owner Characteristics
Nonemployer firms are more likely than employer firms to be owned by people
of color and women.
RACE/ETHNICITY OF OWNER(S) 1,2 GENDER OF OWNER(S) 2
(% of nonemployer and employer firms) (% of nonemployer and employer firms)
6%
10% 21%
14% 2%
7%
Nonemployer Employer Nonemployer 42% Employer
firms firms firms firms
11%
(N=4,531) (N=9,693) (N=4,531) (N=9,693)
68% 58%
82% 79%
Asian Black Hispanic White Women-owned Men-owned or equally owned
DESCRIPTION OF PRIMARY OWNER’S WORK
FOR THE BUSINESS 3 (% of nonemployer firms) N=4,011
Business is owner's
59% of nonemployer firms
only job 67% account for all or most of their
primary owner’s household income
Owner has multiple jobs;
this is the main job 17%
45% of nonemployer firms work
Owner has multiple jobs; as independent contractors for
this is not main job 14%
other businesses or agencies
Owner does not regularly
work at this business 1% 18% of surveyed nonemployer
firms perform gig work4
1 Non-Hispanic Native American, not shown, account for less than 1 percent of nonemployer firms.
2 SBCS responses throughout the report are weighted using Census Bureau data to represent the nonemployer firm population in the United States by age,
industry, geographic location, gender of owner(s), and race or ethnicity of owner(s). Employer firm responses are weighted using Census Bureau data to
represent the US small employer firm population on the following dimensions: firm age, number of employees, industry, geography, race/ethnicity of owner, and
gender of owner. For details on weighting, see Methodology.
3 Percentages may not sum to 100 due to rounding.
4 The SBCS questionnaire describes a gig as a single project or task for which a worker is hired, sometimes through a digital marketplace, to work on demand.
Examples include Uber driver, freelancer, etc.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 2
DEMOGRAPHICS
Firm Characteristics
Compared to employer firms, nonemployer firms are smaller, as measured by
revenues. Nonemployer firms are more concentrated in service industries.
REVENUE SIZE OF FIRM 1,2 (% of nonemployer and employer firms)
<1%
2% 5% ≥ $10M
28% $1M to < $10M
For purposes of this 30%
$100K to < $1M
report, “Smaller
nonemployer firms” ≤$100K
are those with $100K
or less in annual
revenues. “Larger
nonemployer firms” 50%
are those with more 70%
than $100K in annual
revenues.
15%
Nonemployer firms Employer firms
(N=4,230) (N=9,440)
INDUSTRY 1,3,4 (% of nonemployer and employer firms)
Manufacturing
Finance &
insurance
Non-manufacturing Business Healthcare & Leisure &
goods production support & education hospitality
Professional services & & associated consumer
real estate services services Retail
Nonemployer firms
(N=4,531) 26% 23% 21% 11% 8% 7% 3% 1%
Employer firms
(N=9,693)
20% 18% 15% 13% 13% 11% 6% 4%
1 SBCS responses throughout the report are weighted using Census Bureau data to represent the nonemployer firm population in the United States by age,
industry, geographic location, gender of owner(s), and race or ethnicity of owner(s). Employer firm responses are weighted using Census Bureau data to
represent the US small employer firm population on the following dimensions: firm age, number of employees, industry, geography, race/ethnicity of owner, and
gender of owner. For details on weighting, see Methodology.
2 Categories have been condensed and simplified for readability. Actual categories are: ≤$25K, $25,001–$50K, $50,001–$100K, $100,001–$500K, $500,001–$1M,
$1,000,001–$5M, $5,000,001–$10M, >$10M.
3 Percentages may not sum to 100 due to rounding.
4 Within non-manufacturing goods production and associated services, the share of nonemployer firms is higher than the share of employers for transportation
and wholesale businesses.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 3
PERFORMANCE & CHALLENGES
Revenue Change and Financial Condition
A majority of nonemployer firms experienced declines in revenues during the prior
12 months.
NONEMPLOYER FIRM REVENUE PERFORMANCE INDEX, Prior 12 Months 1,2 (% of nonemployer firms)
16% 16% 19% 18%
2016 Survey 2017 Survey 2018 Survey 2019 Survey
(N=5,225) (N=5,380) (N=5,622) (N=3,849)
-63%
2020 Survey
(N=4,520)
36% of smaller nonemployers and 23% of larger nonemployers were in poor financial
condition at the time of the survey. Overall, 32% of nonemployers reported that
their firm was in poor financial condition.
SHARE OF FIRMS IN “POOR” FINANCIAL CONDITION, At Time of Survey3,4 (% of nonemployer and employer firms)
36%
23% 23%
Smaller Larger Employer
nonemployer nonemployer firms
firms firms (N=9,664)
(N=3,022) (N=1,195)
1 The index is the share reporting revenue growth minus the share reporting a reduction.
2 Prior 12 months is approximately the second half of the prior year through the second half of the surveyed year.
3 Firm’s financial condition was self-reported by the respondent. Response options were excellent, very good, good, fair, and poor. See Appendix for more detail.
4 At time of survey, September through October 2020.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 4
PERFORMANCE & CHALLENGES
Financial Challenges and Reliance on Personal Funds
Nonemployer firms reported more financial challenges in 2020 than in prior years.
Compared to employer firms, nonemployer firms were more likely to rely on the
owners’ personal funds to address challenges.
SHARE OF FIRMS WITH FINANCIAL CHALLENGES, Prior 12 Months 1 (% of nonemployer firms)
81%
2020 Survey
(N=4,511)
69%
64% 2019 Survey
62% (N=3,986)
2017 Survey
(N=5,511) 2018 Survey
(N=5,764)
SHARE OF FIRMS USING OWNERS’ PERSONAL SHARE OF FIRM OWNERS REPORTING IMPACT
FUNDS TO ADDRESS FINANCIAL CHALLENGES, ON PERSONAL FINANCES FROM THEIR FIRMS’
Prior 12 Months 2,3 PANDEMIC-RELATED CHALLENGES 4
(% of nonemployer and employer firms) (% of nonemployer and employer firms)
Smaller nonemployer firms Smaller nonemployer firms 88%
(N=2,451)
73% (N=2,146)
Larger nonemployer firms 70% Larger nonemployer firms 85%
(N=948) (N=876)
Employer firms Employer firms 80%
(N=7,897)
62% (N=6,794)
1 Prior 12 months is approximately the second half of the prior year through the second half of the surveyed year.
2 Prior 12 months is approximately the second half of 2019 through the second half of 2020.
3 Select response option shown. See Appendix for more detail on other actions taken in response to financial challenges.
4 Data on personal finances were drawn from questions in the optional end-of-survey module (completed by approximately 80% of respondents). This subset of
respondents is re-weighted to be reflective of the overall small firm population. See Appendix for more detail on responses.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 5
EMERGENCY FUNDING
Pandemic-Related Emergency Funding Needs
Nonemployer firms were less likely than employer firms to apply for Paycheck
Protection Program (PPP) loans. Smaller nonemployer firms were least likely
to apply.
APPLICATIONS FOR EMERGENCY ASSISTANCE FUNDS 1,2 (% of nonemployer and employer firms)
Nonemployer firms
82% (N=4,408)
Employer firms
(N=9,565)
47%
37% 35% 35% 34%
29% 28%
21%
6% 8% 5% 8% 9%
EIDL loan Paycheck EIDL grant Grant from state/ Grant from Loan from state/ Did not complete
Protection local government nonprofit or local government emergency
Program fund foundation fund assistance funding
application
SHARE OF FIRMS THAT APPLIED FOR A PPP LOAN 3 (% of nonemployer and employer firms)
Smaller nonemployer firms
(N=2,943) 28%
Larger nonemployer firms
(N=1,179) 55%
Smaller employer firms
(N=5,911) 77%
Larger employer firms
(N=3,417) 93%
30% of nonemployer firm owners collected
unemployment insurance benefits.4
1 The Paycheck Protection Program (PPP) and Economic Injury Disaster Loan (EIDL) are administered through the US Small Business Administration. Select
response options shown. See Appendix for more detail.
2 Respondents could select multiple options.
3 For purposes of this report, “Smaller employer firms” are those with $1M or less in annual revenues. “Larger employer firms” are those with more than $1M in annual
revenues.
4 The CARES Act gives states the option of extending unemployment compensation to independent contractors and other self-employed workers who are
ordinarily ineligible for unemployment benefits.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 6
EMERGENCY FUNDING
PPP Nonapplicants
Nonemployer firms that did not seek PPP loans most often said they chose not
to apply because they did not expect they would qualify for the loan or for loan
forgiveness.
REASONS FIRMS DID NOT APPLY FOR A PPP LOAN 1,2,3 (% of nonemployer firms that did not apply for PPP) N=2,965
Business would not qualify for the loan
51%
or loan forgiveness
Program/process was too confusing 17%
Nonemployer firms
Business did not need funding 16%
that did not apply for
PPP were more likely
than their employer
Unaware of program
firm counterparts
11%
to expect they
would not qualify
for the loan or for
Sought other funding instead 10%
forgiveness, as 37%
of employer firms
Could not find a lender cited this reason.
to accept the application 8%
Missed deadline 8%
Uninterested in government aid 5%
Loan forgiveness was a concern even for nonemployers that applied for and
received PPP loans. Among those that received PPP loans, 31% did not expect full
loan forgiveness or were unsure, compared to 20% of employer firms.
1 The Paycheck Protection Program (PPP) is administered through the US Small Business Administration.
2 Respondents could select multiple options.
3 Top response options shown. See Appendix for more detail.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 7
EMERGENCY FUNDING
Applications and Outcomes
Overall, nonemployer firms were less likely than their employer firm
counterparts to seek emergency funding and less likely to be approved.
PANDEMIC-RELATED EMERGENCY ASSISTANCE APPLICATIONS AND OUTCOMES 1,2
Share that did not seek
assistance but needed
funding
Share that sought Share that did not seek
assistance and any form of assistance
received funding Share that sought
assistance and were and did not need
denied funding funding
Smaller nonemployer firms 62% 20% 9%
(N=2,813)
8%
Larger nonemployer firms 78% 5% 10%
(N=1,120)
7%
Employer firms 87% 4% 6% 3%
(N= 9,294)
PPP FUNDING RECEIVED, AS SHARE OF AMOUNT SOUGHT 1 (% of nonemployer and employer PPP applicant firms)
Nonemployer firms 57% 7% 16% 20%
All Most Some None
(N=1,375) 51–99% 1–50%
Employer firms 77% 11% 8% 4%
All Most Some None
(N=7,575) 51–99% 1–50%
1 The Paycheck Protection Program (PPP) is administered through the US Small Business Administration.
2 Percentages may not sum to 100 due to rounding.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 8
EMERGENCY FUNDING
PPP Applications and Outcomes
Nonemployer PPP applicant firms were more likely than employer PPP applicant
firms to apply at an online lender. Smaller nonemployers were the most likely to
apply at an online lender.
PPP APPLICATIONS AT SOURCE 1,2 (% of nonemployer and employer PPP applicants)
Nonemployer firms
48% (N=1,393)
43% Employer firms
41% (N=7,696)
35%
19%
9% 8%
5% 5% 2%
3% 3%
Large bank3 Small bank Online lender4 Credit union Nonbank CDFI6
finance
company5
SHARE OF FIRMS THAT APPLIED FOR PPP AT ONLINE LENDERS 1,4,7 (% of nonemployer and employer PPP applicants)
Smaller nonemployer firms
(N=730)
24%
Larger nonemployer firms 15%
(N=623)
Smaller employer firms
(N=4,392)
11%
Larger employer firms 4%
(N=3,172)
1 The Paycheck Protection Program (PPP) is administered through the US Small Business Administration.
2 Respondents could select multiple options; respondents may have submitted more than one application.
3 Respondents were provided a list of large banks (those with at least $10B in total deposits) operating in their state.
4 “Online lenders,” also called fintech lenders, are nonbanks that lend online. Examples include Lending Club, OnDeck, CAN Capital, Paypal Working Capital,
Kabbage, etc.
5 “Finance company” includes nonbank lenders such as mortgage companies, equipment dealers, insurance companies, auto finance companies, etc.
6 Community development financial institutions (CDFIs) are financial institutions that provide credit and financial services to underserved markets and
populations. CDFIs are certified by the CDFI Fund at the US Department of the Treasury.
7 For purposes of this report, “Smaller employer firms” are those with $1M or less in annual revenues. “Larger employer firms” are those with more than $1M in
annual revenues.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 9
EMERGENCY FUNDING
PPP Applications and Outcomes (Continued)
Nonemployer firms that sought PPP were most successful at small banks and least
successful at online lenders and credit unions. Regardless of source, nonemployer
firms were less likely than employer firms to receive all the PPP funding sought.
SHARE OF PPP APPLICANTS THAT RECEIVED ALL OF THE PPP FUNDING SOUGHT, By Source 1
(% of nonemployer and employer PPP applicants)
Nonemployer firms Employer firms
Small bank
(N=496–3,621)
63% 78%
Large bank2
(N=566–3,389) 52% 70%
Credit union
(N=126–391) 46% 63%
Online lender3
(N=277–671) 45% 47%
1 Select lenders shown. See Appendix for more detail.
2 Respondents were provided a list of large banks (those with at least $10B in total deposits) operating in their state.
3 “Online lenders,” also called fintech lenders, are nonbanks that lend online. Examples include Lending Club, OnDeck, CAN Capital, Paypal Working Capital, Kabbage, etc.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 10
LOOKING AHEAD
Performance Expectations, Next 12 Months
The net share of nonemployer firms expecting revenue growth in the coming
year declined sharply from levels observed in prior surveys. Still, about a quarter
of nonemployers plan to add employees in the next 12 months, a slight decline
from 2019.1
NONEMPLOYER FIRM REVENUE EXPECTATIONS INDEX, Next 12 Months 2,3
(% of nonemployer firms)
63%
62%
59% 59%
2016 Survey 2017 Survey
(N=5,255) (N=5,445) 2018 Survey 2019 Survey
(N=5,691) (N=3,854)
4%
2020 Survey
(N=4,515)
25% of nonemployer firms and 31% of employer firms
expect to add employees in the next 12 months.4
1 The share of nonemployer firms that expected to add employees in the next 12 months declined slightly, from 29% in 2019 to 25% in 2020.
2 The index is the share reporting expected growth minus the share reporting a reduction.
3 Expected change in approximately the second half of the surveyed year through the second half of the following year.
4 Next 12 months is approximately the second half of 2020 through the second half of 2021.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 11
LOOKING AHEAD
Expected Pandemic-Related Challenges, Next 12 Months
94% of nonemployers anticipated pandemic-related challenges in the 12 months
following the survey.
CHALLENGES FIRMS EXPECT TO FACE AS A RESULT OF THE PANDEMIC, Next 12 Months 1,2 N=4,435
(% of nonemployer firms)
Weak demand for products/
60%
services
Government-mandated
43%
restrictions/closures
Limited credit availability 28%
Supply chain disruptions 26%
Personal/family obligations 24%
Labor shortages 11%
No significant challenges 6%
1 Respondents could select multiple options.
2 Next 12 months is approximately the second half of 2020 through the second half of 2021.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 12
DEBT & FINANCING
Debt Outstanding
The share of nonemployer firms with debt increased from 2019, pandemic-related
assistance aside.
SHARE OF FIRMS WITH DEBT OUTSTANDING, At Time of Survey 1,2
(% of nonemployer and employer firms)
Nonemployer firms Employer firms
79%
71% 71%
70%
68%
59%
51% 51%
46%
45%
2016 Survey 2017 Survey 2018 Survey 2019 Survey 2020 Survey
(N=5,298–9,802) (N=5,474–8,081) (N=5,769–6,540) (N=3,962–5,101) (N=4,445–9,530)
AMOUNT OF DEBT, At Time of Survey 1,2,3 (% of nonemployer and employer firms)
Nonemployer firms
(N=4,420)
41% 50% 9%
Employer firms
(N=9,443)
21% 34% 45%
No debt outstanding ≤$100K >$100K
1 Respondents were instructed to exclude loans they expected would be forgiven from their outstanding debt (for example, PPP loans).
2 At time of survey, September through October 2020.
3 Categories have been condensed and simplified for readability. Actual response options are: ≤$25K, $25,001–$50K, $50,001–$100K, $100,001–$250K,
$250,001–$1M, >$1M.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 13
DEBT & FINANCING
Financial Services Providers
Compared to employer firms, nonemployer firms were less likely to use a large or
small bank for financial services, and they were more likely to report they did not
use any financial services providers.
USE OF FINANCIAL SERVICES PROVIDERS 1,2,3 (% of nonemployer and employer firms)
49% Nonemployer firms
45% (N=4,487)
41% Employer firms
(N=9,646)
28%
16% 18%
12% 10% 11%
4% 8% 7%
Large bank 4
Small bank Credit union Nonbank online/ Nonbank Business
fintech lender5 finance does not use
company6 financial
services
SHARE SATISFIED WITH SUPPORT FROM PRIMARY FINANCIAL SERVICES PROVIDER DURING THE
PANDEMIC 7 (% of nonemployer and employer firms that use provider)
Nonemployer firms
29%
Large bank4 Employer firms
(N=1,522–3,893)
41%
42%
Small bank
(N=1,026–3,259)
61%
39%
Credit union
(N=544–575)
48%
28%
Online lender5
(N=169–346)
18%
1 Financial services providers are those at which the firm has an account or uses other financial services (including loans, payments processing, etc.).
2 Respondents could select multiple options.
3 Select providers shown. See Appendix for detail.
4 Respondents were provided a list of large banks (those with at least $10B in total deposits) operating in their state.
5 Online lenders/fintech companies are nonbanks that operate online. Examples include OnDeck, Kabbage, Paypal, Square, etc.
6 “Finance company” includes nonbank lenders such as mortgage companies, equipment dealers, insurance companies, auto finance companies, etc.
7 Satisfaction is available for only respondents’ primary financial services providers. Select providers shown. See Appendix for details on primary financial
services providers.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 14
DEBT & FINANCING
Financing Demand and Outcomes, Prior 12 Months
Demand for traditional financing declined among both nonemployer and employer
firms between the 2019 and 2020 surveys.
SHARE THAT APPLIED FOR FINANCING, Prior 12 Months 1,2 (% of nonemployer and employer firms)
2020 application rate excludes PPP and other pandemic-related emergency funding applications.
Nonemployer firms Employer firms
45%
43% 43%
40%
37%
29% 29%
25% 26%
24%
2016 Survey 2017 Survey 2018 Survey 2019 Survey 2020 Survey
(N=5,345–9,868) (N=5,547–8,169) (N=5,841–6,614) (N=4,020–5,154) (N=4,400–9,407)
Overall, 60% of nonemployer firms received at least some of the financing they
sought. Larger nonemployers were more likely to obtain the financing they sought
than smaller nonemployers.
TOTAL FINANCING RECEIVED 3,4 (% of nonemployer and employer applicant firms)
Smaller nonemployer firms 42% 31% 9% 17%
None Some Most All
(N=596) 1–50% 51–99%
Larger nonemployer firms 35% 22% 14% 29%
None Some Most All
(N=324) 1–50% 51–99%
Employer firms 25% 23% 15% 37%
None Some Most All
(N=3,500) 1–50% 51–99%
1 In the 2020 survey, respondents were asked first about their applications for pandemic-related emergency funding, and then were asked to exclude these
emergency funding applications from subsequent responses on the applications for financing.
2 Prior 12 months is approximately the second half of the prior year through the second half of the surveyed year.
3 Excludes emergency funding applications.
4 Percentages may not sum to 100 due to rounding.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 15
DEBT & FINANCING
Financing Needs and Outcomes
FUNDING NEEDS AND OUTCOMES 1,2 (% of nonemployer firms) N=4,294
To gauge funding success and shortfalls, we combine applicants’ financing outcomes and nonapplicants’ reasons for not applying. Firms
that had their funding needs met emerge in two forms:
1) Applicant firms that received the full amount of financing sought; or
2) Nonapplicant firms that did not apply for financing because they already had sufficient financing.
The remaining firms have unmet funding needs. When applicant firms did not obtain the full amount of financing sought, we consider
them to have a funding shortfall. When nonapplicant firms reported they did not have sufficient financing, we consider them to have unmet
funding needs.
24% 76%
Applied for financing Did not apply for financing
9% 7% 3% 5% 33% 14% 21% 8%
None Received Received Received all Sufficient Debt averse Discouraged3 Other
some most financing
19% 38% 43%
Had a financing Financing Have unmet
shortfall needs met funding needs
1 Based on the prior 12 months, which is approximately the second half of 2019 through the second half of 2020.
2 Excludes emergency funding applications.
3 Discouraged firms are those that did not apply for financing because they believed they would be turned down.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 16
DEBT & FINANCING
Loan, Line of Credit, and Cash Advance Sources
Compared to employer firms, nonemployer firms that sought financing were less
likely to apply for financing at small banks and more likely to apply at online lenders.
CREDIT SOURCES APPLIED TO 1,2 (% of nonemployer and employer loan, line of credit, and cash advance applicant firms)
Nonemployer firms
45% (N=598)
Large bank 3
42% Employer firms
(N=2,574)
30%
Small bank
43%
25%
Online lender4
20%
15%
Finance company5
15%
Credit union 12%
9%
5%
CDFI6
3%
1 Excludes emergency funding applications.
2 Respondents could select multiple options.
3 Respondents were provided a list of large banks (those with at least $10B in total deposits) operating in their state.
4 “Online lenders,” also called fintech lenders, are nonbanks that lend online. Examples include Lending Club, OnDeck, CAN Capital, Paypal Working Capital,
Kabbage, etc.
5 “Finance company” includes nonbank lenders such as mortgage companies, equipment dealers, insurance companies, auto finance companies, etc.
6 Community development financial institutions (CDFIs) are financial institutions that provide credit and financial services to underserved markets and
populations. CDFIs are certified by the CDFI Fund at the US Department of the Treasury.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 17
DEBT & FINANCING
Loan, Line of Credit, and Cash Advance Application Outcomes
Both nonemployer and employer applicants were more successful obtaining
financing at small banks than at other sources.
APPROVAL RATES FOR LOAN, LINE OF CREDIT, AND CASH ADVANCE APPLICATIONS, By Source 1,2,3
(% of nonemployer and employer loan, line of credit, and cash advance applicants at source)
Nonemployer firms
74% Employer firms
62% 65%
56%
50%
41%
Small bank Large bank4 Online lender5
(N=171–995) (N=258–1,069) (N=149–455)
APPROVAL RATES FOR LOAN, LINE OF CREDIT, AND CASH ADVANCE APPLICATIONS, Prior 12 Months 1,2,6
(% of nonemployer and employer loan, line of credit, and cash advance applicants)
Nonemployer firms Employer firms
81%
64% 70%
51%
Before March 1, 2020 After March 1, 2020
(N=234–1,137) (N=441–1,679)
1 Approval rate is the share approved for at least some credit.
2 Excludes emergency funding applications.
3 Select sources shown. See Appendix for more detail.
4 Respondents were provided a list of large banks (those with at least $10B in total deposits) operating in their state.
5 “Online lenders,” also called fintech lenders, are nonbanks that lend online. Examples include Lending Club, OnDeck, CAN Capital, Paypal Working Capital,
Kabbage, etc.
6 Prior 12 months is approximately the second half of 2019 through the second half of 2020.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 18
METHODOLOGY
DATA COLLECTION industry, geographic location (urban or models is used to attempt to impute the
rural location), gender of owner(s), and race missing data. When the models are able
The Small Business Credit Survey or ethnicity of owner(s). We first limit the to predict with an average accuracy of
(SBCS) uses a convenience sample sample in each year to only nonemployer 80 percent in out-of-sample tests, the
of establishments. Businesses are firms. We then post-stratify respondents by predicted values from the models are
contacted by email through a diverse set of their firm characteristics. Using a statistical used for the missing data.5 When the
organizations that serve the small business technique known as “raking,” we compare model is less certain, those data are not
community.1 Previous SBCS participants the share of businesses in each category imputed, and the responses are dropped.
and small businesses on publicly available of each stratum (for example, within the After data are imputed, descriptive
email lists are also contacted directly by industry stratum, the share of firms in the statistics of key survey questions with
the Federal Reserve Banks.2 The survey sample that are manufacturers) to the share and without imputed data are compared to
instrument is an online questionnaire that of nonemployer businesses in the nation ensure stability of estimates. In the final
typically takes 6 to 12 minutes to complete, that are in that category.3 As a result, sample of nonemployers, seven percent
depending on the intensity of a firm’s underrepresented firms are up weighted, of observations have imputed values for
search for financing. The questionnaire and overrepresented businesses are down the gender, race, or ethnicity of a firm’s
uses question branching and flows based weighted. We iterate this process several ownership.
on responses to survey questions. For times for each stratum in order to derive a
example, financing applicants receive sample weight for each respondent. This To impute for owners’ race and ethnicity,
a different line of questioning than weighting methodology was developed in a series of logistic regression models is
nonapplicants. Therefore, the number of collaboration with the National Opinion used that incorporates a variety of firm
observations for each question varies by Research Center (NORC) at the University characteristics, as well as demographic
how many firms receive and complete a of Chicago. The data used for weighting information on the business owners’ zip
particular question. come from data collected by the US Census code. First, a logistic regression model
Bureau.4 is used to predict if business owners
are members of a minority group. Next,
WEIGHTING for firms classified as minority-owned,
RACE/ETHNICITY AND GENDER a logistic probability model is used to
A sample for the SBCS is not selected
IMPUTATION predict if business owners are of Hispanic
randomly; thus, the SBCS may be subject ethnicity.6 Finally, the race for the business
to biases not present with surveys that Nine percent of nonemployer respondents owners is imputed separately for Hispanic
do select firms randomly. For example, completed the survey but did not provide and non-Hispanic firms using a multinomial
there are likely firms not on our contact information on the gender, race, and/or logistic probability model. A similar process
lists, and this may lead to a noncoverage the ethnicity of their business’ owner(s). is used to impute the gender of a business’s
bias. To control for potential biases, the This information is needed to correct owners. First, a logistic model is used to
sample data are weighted so the weighted for differences between the sample and predict if a business is owned by a man.
distribution of firms in the SBCS matches the population data. To avoid dropping
the distribution of the nonemployer firm these observations, a series of statistical
population in the United States by age,
1 For more information on partnerships, please visit www.fedsmallbusiness.org/partnership.
2 System for Award Management (SAM) Entity Management Extracts Public Data Package; Small Business Administration (SBA) Dynamic Small Business Search
(DSBS); state-maintained lists of certified disadvantaged business enterprises (DBEs); state and local government procurement vendor lists, including minority
and women-owned business enterprises (MWBEs); state and local government maintained lists of small or disadvantaged small businesses; and a list of veteran-
owned small businesses maintained by the Department of Veterans Affairs.
3 Age strata are 0–2 years, 3–4 years, 5–12 years, and 13+ years. Industry strata are non-manufacturing goods production and associated services, manufacturing,
retail, leisure and hospitality, finance and insurance, healthcare and education, professional services and real estate, and business support and consumer
services. Race/ethnicity strata are Hispanic, non-Hispanic Asian, non-Hispanic Black or African American, non-Hispanic Native American, and non-Hispanic white.
Gender strata are men-owned or equally owned, and women-owned. See Appendix for industry definitions and urban and rural definitions.
4 Data on industry and urban/rural location come from the US Census Bureau’s 2018 Nonemployer Statistics (NES). Data from the US Department of Agriculture’s
Rural-Urban Continuum Codes are used to classify a business’s county as urban or rural. Data on firm age come from the US Census Bureau’s 2012 Survey of
Business Owners. Data on the race, ethnicity, and gender of business owners are derived from the US Census Bureau’s 2016 NES-D release.
5 Out-of-sample tests are used to develop thresholds for imputing the missing information. To test each model’s performance, half of the sample of non-missing data
is randomly assigned as the test group, while the other half is used to develop coefficients for the model. The actual data from the test group is then compared with
what the model predicts for the test group. On average, prediction probabilities that are associated with an accuracy of around 80 percent are used, although this
varies slightly depending on the number of observations that are being imputed.
6 For some firms that were originally missing data on the race/ethnicity of their ownership, this information was gathered from public databases or past SBCS data.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 19
METHODOLOGY
(Continued)
Then, for firms not classified as men- survey years. After implementing changes CREDIBILITY INTERVALS
owned or equally owned, another model is to the weighting methodology, post-2015
used to predict if a business is owned by a survey years have been weighted with a The analysis in this report is aided by
woman. For some firms that were originally uniform set of variables. Data for the 2015 the use of credibility intervals. Where
missing data on the race/ethnicity of their survey year are thus not displayed in this there are large differences in estimates
ownership, this information was gathered report, as they lack information on several between types of businesses, we perform
from public databases or past SBCS of the weighting variables. The data in this additional checks on the data to determine
surveys. report are, however, comparable to the whether such differences are statistically
report containing 2018 survey data that significant. The results of these tests
was published in 2019, and 2017 survey help guide our analysis and help us
COMPARISONS TO PAST REPORTS data that were published in 2018. For more decide what ultimately is included in the
information on the methodological changes report. To determine whether differences
Because previous SBCS reports have to the “time-consistent” weights, please are statistically significant, we develop
varied in terms of the population scope, refer to the methodology section of the credibility intervals using a balanced half-
geographic coverage, and weighting Small Business Credit Survey 2019 Report sample approach.7 Because the SBCS does
methodology, the survey reports are on Employer Firms. In addition, many survey not come from a probability-based sample,
not directly comparable across time. questions are not comparable over time the credibility intervals we develop should
Geographic coverage and weighting due to changes in the response options. be interpreted as model-based measures of
strategies have varied from year to year. For example, the option “Finance company” deviation from the true national population
For example, the 2016 data were not was added as an application source in the values.8 We list 95 percent credibility
originally weighted by race, ethnicity, or 2019 survey; thus, the application rates by intervals for key statistics in Table 1. The
gender of owner(s), whereas the 2017 source displayed in the 2021 report are not intervals shown apply to all nonemployer
through 2020 data (presented in this report) directly comparable to reports prior to the firms in the survey. More granular results
did include these owner demographics 2019 survey. with smaller observation counts will
in the weighting scheme, as described generally have larger credibility intervals.
previously. In addition to being weighted
by different firm characteristics over
time, the categories used within each
characteristic have also differed across
TABLE 1
Percent Credibility Interval
Share that applied 23.9% +/- 1.9%
Share with outstanding debt 59.3% +/- 1.8%
Share of firms that received at least some
59.9% +/- 2.0%
of the financing they sought
Share of firms with financial
18.6% +/- 0.7%
challenges in prior 12 months
Share of firms in poor condition 32.0% +/- 0.8%
7 Wolter. Survey Weighting and the Calculating of Sampling Variance. 2007.
8 AAPOR. Task Force on Non-probability Sampling. 2013.
SMALL BUSINESS CREDIT SURVEY | 2021 REPORT ON NONEMPLOYER FIRMS 20
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