The impact of COVID-19 on small business outcomes and expectations 7/2022
Significance
Drawing on a survey of more than 5,800 small businesses, this paper provides insight into the economic impact of coronavirus 2019 (COVID-19) on small businesses. The results shed light on both the financial fragility of many small businesses, and the significant impact COVID-19 had on these businesses in the weeks after the COVID-19–related disruptions began. The results also provide evidence on businesses’ expectations about the longer-term impact of COVID-19, as well as their perceptions of relief programs offered by the government.
Abstract
To explore the impact of coronavirus disease 2019 (COVID-19) on small businesses, we conducted a survey of more than 5,800 small businesses between March 28 and April 4, 2020. Several themes emerged. First, mass layoffs and closures had already occurred—just a few weeks into the crisis. Second, the risk of closure was negatively associated with the expected length of the crisis. Moreover, businesses had widely varying beliefs about the likely duration of COVID-related disruptions. Third, many small businesses are financially fragile: The median business with more than $10,000 in monthly expenses had only about 2 wk of cash on hand at the time of the survey. Fourth, the majority of businesses planned to seek funding through the Coronavirus Aid, Relief, and Economic Security (CARES) Act. However, many anticipated problems with accessing the program, such as bureaucratic hassles and difficulties establishing eligibility. Using experimental variation, we also assess take-up rates and business resilience effects for loans relative to grants-based programs.
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In addition to its impact on public health, coronavirus disease 2019 (COVID-19) has caused a major economic shock. In this paper, we explore the impact of COVID-19 on the small business landscape in the United States, focusing on three questions. First, how did small businesses adjust to the economic disruptions resulting from COVID-19? Second, how long did businesses expect the crisis to last, and how do expectations affect their decisions? Third, how might alternative policy proposals impact business and employment resilience?
To explore, we surveyed more than 5,800 small businesses that are members of Alignable, a network of 4.6 million small businesses. The survey was conducted between March 28 and April 4, 2020. The timing of the survey allows us to understand expectations of business owners at a critical point in time when both the progression of COVID-19 and the government’s response were quite uncertain.
The results suggest that the pandemic had already caused massive dislocation among small businesses just several weeks after its onset and prior to the availability of government aid through the Coronavirus Aid, Relief, and Economic Security (CARES) Act. Across the full sample, 43% of businesses had temporarily closed, and nearly all of these closures were due to COVID-19. Respondents that had temporarily closed largely pointed to reductions in demand and employee health concerns as the reasons for closure, with disruptions in the supply chain being less of a factor. On average, the businesses reported having reduced their active employment by 39% since January. The decline was particularly sharp in the Mid-Atlantic region (which includes New York City), where 54% of firms were closed and employment was down by 47%. Impacts also varied across industries, with retail, arts and entertainment, personal services, food services, and hospitality businesses all reporting employment declines exceeding 50%; in contrast, finance, professional services, and real estate-related businesses experienced less disruption, as these industries were better able to move to remote production.
Our results also highlight the financial fragility of many businesses. The median firm with monthly expenses over $10,000 had only enough cash on hand to last roughly 2 wk. Three-quarters of respondents only had enough cash on hand to last 2 mo or less.* Not surprisingly, firms with more cash on hand were more optimistic that they would remain open by the end of the year.
Our survey also elicited businesses’ beliefs about the evolution of the crisis, allowing us to study the role of beliefs and expectations in decisions. The median business owner expected the dislocation to last well into midsummer, as 50% of respondents believed that the crisis would last at least until the middle of June. However, beliefs about the likely duration of the crisis varied widely. This raises the possibility that some firms were making mistakes in their forecasts of how long the crisis will last.†
The crisis duration plays a central role in the total potential impact. For a crisis lasting 4 mo instead of 1 mo, only 47% of businesses expected to be open in December compared to 72% under the shorter duration. There is also considerable heterogeneity in how sensitive businesses are to the crisis. In-person industries like personal services or retail reported worse prospects for riding out the pandemic than professional services or other sectors with minimal need for face-to-face contact.
Lastly, our analysis explores variants of stimulus packages that were being discussed at the time of the survey. The results show that over 70% of respondents anticipated taking advantage of aid when asked about a program that resembles the Paycheck Protection Program (PPP) that is part of the CARES Act. Moreover, they expected this funding to influence other business decisions—including layoff decisions and staying in business altogether. At the same time, many businesses were reluctant to apply for funding through the CARES Act because of concerns about administrative complexity and eligibility. A large number of respondents also anticipated problems with accessing the aid, citing potential issues such as bureaucratic hassles and difficulties establishing eligibility.
Our survey was constructed to allow for a counterfactual evaluation of a straight loan policy, which is a stylized representation of traditional Small Business Administration disaster relief programs. While the more generous PPP program does improve take-up and business outcomes, traditional loans with speedy delivery and sufficient liquidity are also found to meaningfully shift business owners’ expectations about survival. When compared to a straight loan without forgiveness provisions, the CARES Act had modestly greater take-up, but at much higher cost to the government. Because the majority of business owners would have taken up aid in the form of less generous loans, our results suggest that liquidity provision was paramount for these owners.
Overall, our paper contributes to our understanding of the economic impact of COVID-19 on the small business ecosystem. The fate of the 48% of American workers who work in small businesses is closely tied to the resilience of the small business ecosystem to the massive economic disruption caused by the pandemic. Our survey was conducted during a period of substantial policy uncertainty and before any federal response had been enacted. Our results provide a unique snapshot into business decisions and expectations at that time, while offering insight for policy designed to aid the recovery. Our results highlight the role the length of the crisis will play in determining its ultimate impact, which policy makers should consider as they contemplate the scale of the required interventions. We estimate that closures alone might lead to 32.7 million job losses if the crisis lasts for 4 mo and 35.1 million job losses if the crisis lasts for 6 mo. While some of these workers will surely find new jobs, these projections suggest that the scale of job dislocation could be larger than anything America has experienced since the Great Depression and larger than the impact of the 1918 influenza epidemic (6–8). Another important take-away of our work is that, during liquidity crunches with significant cash flow disruptions, the form of cash injection (e.g., grant vs. loan) may be less important than making sure that funding is rapidly available with little administrative complexity.‡
The rest of the paper proceeds as follows. Survey Design and Details discusses the survey design. Firm Characteristics and Representativeness discusses the characteristics of the firms that responded to the survey and their representativeness. In Responses to the COVID-19 Pandemic and Lockdown, we explore the current and expected impacts of COVID-19 on these businesses. In Anticipated Response to CARES Act Programs, we present results from a module of the survey that experimentally varies policy proposals, allowing us to explore responses to policies such as the recently passed CARES Act as well as alternative policies. Industry Differences in Response to Crisis Duration considers survival rate differences across industries, and how survival depends on the duration of the crisis. We conclude in Conclusion.
Survey Design and Details
Our survey was sent out in partnership with Alignable, a network-based platform focused on the small business ecosystem. Alignable enables businesses to share knowledge and interact with one another, and currently has a network of 4.6 million small businesses across North America. Much of the network growth has been organic, with little outside marketing.
Alignable also regularly sends out polls (which they call “pulse surveys”) to users. At the end of a regular pulse poll, participants who took that poll received an email inviting them to participate in a more comprehensive survey being conducted by researchers at Harvard Business School. Participants were shown a disclosure statement and consent protocol. No payments were offered; participation was completely voluntary. The survey was approved by the Harvard University Institutional Review Board.
We received 7,511 responses between March 27 and April 4; 5,843 of these can be traced back to US-based businesses, which is the relevant sample for understanding policy. While the 7,511 responses represent a small fraction (0.017%) of Alignable’s total membership, they represent a much larger share of Alignable’s membership that has engaged with their weekly pulse surveys on COVID-19. Alignable estimates that 50,000 to 70,000 members are taking these pulse surveys weekly, which suggests a 10 to 15% conversion rate of these more active respondents.
Our sample, therefore, is selected in three ways: 1) They are firms that have chosen to join Alignable, 2) they are Alignable firms that have chosen to stay actively engaged taking surveys, and 3) they are the set of firms that are active within Alignable that chose to answer our survey. Consequently, there are many reasons to be cautious when extrapolating to the entire universe of America’s small businesses. We will discuss their representativeness based on observable attributes in the next section of this report.
The survey included a total of 43 questions, with basic information about firm characteristics (including firm size and industry), questions about the current response to the COVID-19 crisis, and beliefs about the future course of the crisis. Some questions were only displayed based on skip logic, so most participants responded to fewer questions. The survey also includes an experimental module that randomized scenarios between respondents to understand how different federal policies might impact these firms’ behavior and survival as the crisis unfolds. Specifically, we experimentally varied some of the descriptions of potential policies across the sample to shed light on the potential impact of policy initiatives that, at the time, were very uncertain. We will discuss that module more thoroughly in Anticipated Response to CARES Act Programs. A further experimental module included between-respondent randomization which explored decisions under different hypothetical durations of the crisis.
Firm Characteristics and Representativeness
The survey contains three baseline questions which enable us to assess the representativeness of the sample along observable dimensions: number of employees, typical expenses (as of January 31, 2020), and share of expenses that go toward payroll. We are also able to get rough information about geolocation to assess representativeness by state.
We compare our data with data on businesses from the 2017 Census of US Businesses, using the publicly available statistics published by the US Census Bureau. The underlying data are drawn from the County Business Patterns sampling frame and cover establishments with paid employees, including sole proprietorships if the owner receives a W2. The Census data capture large and small businesses alike, but, for our comparisons, we will look only at businesses with fewer than 500 employees.
The Alignable network allows users to share customer leads, which could potentially skew our sample toward retail and service businesses that interact directly with consumers. Since retail businesses are particularly vulnerable to COVID-19 disruptions, our sample could overstate the aggregate dislocation created by the crisis. Naturally, industries dominated by large firms, such as manufacturing, are underrepresented. However, as we discuss later, our data on the industry mix of responses suggest that the sample represents a wide swath of America’s smaller businesses.
Fig. 1 shows the size distribution of our sample and the size distribution of businesses with fewer than 500 employees in the Economic Census. The match of employment sizes is reassuring. About 64% of the businesses in our sample have fewer than five employees, while about 60% of the firms in the Economic Census are that small. About 18% of businesses in both samples have between five and nine employees. The survey becomes less precisely matched to the Census among the larger employment groupings, and we believe that our survey will capture the experience of larger employers with less accuracy.
Fig. 1.
While our survey does not allow for a direct comparison of payroll expenses with Census data, we constructed a rough comparison by approximating payroll expenses for the Alignable firms from categorical questions about monthly expenses and the share of these expenses going toward payroll. The Census provides annual payroll expenses for W2 employees. To get a sense of the match, we compared our estimated monthly payroll expenses in our sample with one-twelfth of annual expenses in the US Census. To facilitate comparison, we divide by an estimate of total employment.§ Fig. 2 shows the size distribution of monthly estimated payroll expenses in our sample and a comparable breakdown for the Census using a per capita adjustment. The match is imperfect, especially for larger firms. The discrepancy might reflect the underrepresentation of manufacturing or professional services firms in our sample, which are among the highest paying of all two-digit North American Industry Classification System sectors in the Census data. SI Appendix, Table S1 provides further detail on the industry match to the Census.
Fig. 2.
Fig. 3 shows the geographic scope of our sample. The Alignable sample draws particularly from California, the New York region, Florida, and Texas. The sample is sparse in America’s western heartland, which matches the location distribution of smaller businesses in the Economic Census.
Fig. 3.
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