The Impact of the COVID-19 Pandemic on Business Ownership Across Racial/Ethnic Groups and Gender.

This study examined the economic impact of the COVID-19 pandemic on US older entrepreneurs' businesses using the Health and Retirement Study. We estimated logistic regression models to document the odds of experiencing economic impact. The COVID-19 pandemic has affected nearly 76% of US older entrepreneurs but has disproportionately impacted the businesses of Black, Hispanic, Asian/other races, and women entrepreneurs. Older Black entrepreneurs had significantly higher odds of facing business closure (OR = 2.31, p < .01), implementing new procedures (OR = 2.44, p < .01), workers quitting (OR = 2.95, p < .001), and difficulty paying regular bills (OR = 2.88, p < .001) than their White counterparts. Older Hispanic entrepreneurs also had significantly higher odds of instituting new procedures (OR = 2.27, p < .05), workers quitting (OR = 2.26, p < .01), and difficulty paying regular bills (OR = 2.35, p < .01) than their White counterparts. Similarly, older Asian/other races entrepreneurs were significantly more likely to report difficulty paying regular bills since the start of the pandemic than their White counterparts (OR = 3.11, p < .01). Women entrepreneurs were significantly more likely to close their businesses than their male counterparts (OR = 2.11, p < .001). These significant associations persisted after controlling for confounders. Support for underserved racial/ethnic groups and older women entrepreneurs should focus on accessibility to financial services, capital, and support packages as well as legislative support for ensuring business continuity and success.

As of March 2022, there have been nearly 500 million confirmed cases of COVID-19, including over 6 million deaths worldwide. However, the devastation of this global pandemic goes beyond grieving for those who were not able to win their battle against the virus. The impact of the pandemic on the livelihoods of individuals has also been catastrophic, especially those who had no savings, became unemployed, or faced pay cuts (World Economic Forum, 2021). According to the 2020 Global Risks Perception Survey (GRPS), working hours equivalent to 495 million jobs were lost in the second quarter of 2020 (International Labour Organization, 2020). As a percentage, this is essentially 14% of the world’s workforce (World Bank Open Data, 2021). Employment sectors most affected by social distancing protocols were restaurants/bars, travel and transportation, entertainment, personal services, retail, and manufacturing (Vavra, 2020). These sectors employ relatively higher percentages of women, African American/Black, and Hispanic employees (Bureau of Labor Statistics, 2020). Additionally, reports show those most affected by unemployment due to COVID-19 are less educated and have fewer economic resources and liquid assets (Mongey et al., 2020). With each state implementing varying mandates in an effort to control the virus, states with stricter mandates for a greater length of time may have suffered harsher consequences from an economic business perspective.

While we often look at economic impacts at the employee level, employers also faced difficult decisions regarding how long they could keep their businesses afloat. Changes in business operations due to COVID-19 safety restrictions for workers and patrons were only one part of the problem during the height of the pandemic in the USA. Staffing shortages due to employees’ fear of working in public settings or inability to work due to exposure to or testing positive with COVID-19 served devastating blows to businesses. Many of these businesses were able to remain open in a limited capacity but were already facing financial struggles.

Another overlooked area is the impact of the economy on older entrepreneurs. It is anticipated that although younger workers might fare worse with initial job loss, older workers will fare worse in reentering the workforce (Morrow-Howell et al., 2020). For this reason, we chose to focus on the impact of the COVID-19 pandemic on older adult business owners and partners.

Using data from the Health and Retirement Study (HRS), a nationally representative survey of US older adults, we explored the impact of the pandemic on businesses and the perceived economic hardship that followed among older entrepreneurs in the USA. A primary interest was whether the business was affected by the COVID-19 pandemic and, if so, to what extent. We evaluated whether older entrepreneurs have experienced the following: business closures, changes in new procedures, and staffing shortages due to turnover. Furthermore, we focused on economic impact and hardship as it relates to changes in financial situation regarding missed regular bill payments. Additionally, we explored COVID-19-related economic hardships among older entrepreneurs in respect to racial/ethnic groups and gender after controlling for health, demographic, and socioeconomic factors.

Literature Review

Entrepreneurship is often regarded as a mechanism that allows for individuals to achieve financial stability and personal success despite a person’s background or resources. Although there are many benefits to entrepreneurship, those benefits are not always equitably benefitted by all, particularly Black and Hispanic business owners (Mills & Battisto, 2020). While many historically marginalized groups view entrepreneurship as a path to reduce inequality allowing for improved living conditions for their families and communities (Orozco et al. 2020), the COVID-19 pandemic may have served to narrow that pathway by highlighting the prevalence of structural racism that is still overly prevalent in our society. Hispanic businesses also experienced closures due to an overrepresentation in businesses that were adversely affected by the pandemic. Hispanic businesses exist at a disproportionately higher rate in sectors such as construction, accommodation and food services, and transportation (Gonzalez, 2020). For example, accommodation and food service accounts for 9% of employer-owned businesses in the USA; however, 13% of these businesses are Hispanic owned (Gonzalez, 2020). Overall, these sectors experienced higher job losses and closures because of the pandemic compared to other industries in the private sector.

Given the heavy concentration of Black and Hispanic businesses in many metropolitan areas coupled with Black businesses being overrepresented in industries like personal services, (e.g., transportation, food services) (Fairlie & Robb, 2007; Orozco et al. 2020), “stay-at-home” orders passed by many states to decrease the risk of infection from COVID-19 contributed to the temporary and permanent closures of many of these businesses (Johnson & Marte, 2020). Due to the population density of major cities and metropolitan areas, these areas experienced higher rates of COVID-19 infections (Muro et al. 2020). This resulted in many cities creating ordinances restricting or limiting businesses’ operations to reduce rates of infection. Businesses such as hair salons, barber shops, and restaurants were forced to close their businesses or change operating procedures as their operations were deemed non-essential, further complicating minority-owned businesses’ operations.

Moreover, the recent survey data from the U.S. Chamber of Commerce (2020) showed that the COVID-19 pandemic has disproportionately affected women-owned small businesses more than men-owned small businesses. The survey also revealed that women small business owners have less optimistic future business plans, revenue projections, and staffing expectations than their men counterparts (U.S. Chamber of Commerce, 2020).

The Paycheck Protection Program’s (PPP) “first-come, first served” design also disadvantaged small businesses (Humphries et al. 2020a, b; Neilson et al., 2020). In addition to smaller businesses applying later to the program, they also faced longer processing times and were less likely to be approved (Humphries et al. 2020a, b; Neilson et al. 2020). An analysis by Granja et al. (2020) that evaluated the distribution of PPP loans showed that funds from this program flowed to areas that were less impacted in terms of declines in hours or business shutdowns. Moreover, smaller businesses may have encountered challenges related to access to banks and not understanding the application process (needing to find a bank that would accept the application and being able to acquire and provide documentation of payroll). This has been supported by a study by Lederer et al. (2020) that focused on race and showed that when using a matched-pair audit test of financial institutions in Washington, D.C. there were disparities between Black and White testers’ encouragement in not only applying for a PPP loan, but also the products and information offered by the bank representative.

Furthermore, past studies found that Black and Hispanic businesses have greater difficulty obtaining business loans from financial institutions compared to White-owned firms (Bates & Robb, 2013). These businesses experience higher rejection rates for loan applications and receive smaller loans with higher interest rates, if approved (Bates & Robb, 2013). Compounding the effects of discrimination in lending, Hispanic business owners’ income is further impacted by additional constraints such as lack of wealth, age, and lower education levels (Fairlie, 2018). These limitations in financial and human capital have created barriers to growing business income for Hispanic entrepreneurs.

Income Volatility of Black-, Hispanic-, and Women-Owned Businesses

Due to discrimination and the adverse impact of economic and financial policies, Black, Hispanic, and women entrepreneurs are left at a disadvantage (Wingfield & Taylor, 2016). Black and Hispanic business owners were less likely to have sufficient financial resources to weather economic shocks to their businesses compared to White business owners (Fairlie & Robb, 2007; Orozco et al., 2020). Fairlie and Robb (2007) indicated that Black businesses fell behind in areas such as sales, profits, employee retention, and ability to remain in operation compared to White businesses. The authors found that Black business owners often lacked prior work experience to operate their own business which could inhibit them from being able to acquire the necessary capital for their businesses’ operations. This aligns with the concept of evolutionary economics, which suggests that businesses that are better able to adapt, renew, and build on prior knowledge will be more likely to succeed (Dencker et al., 2009).

Black and Hispanic businesses often face barriers to prosperity. Both groups are more likely to have higher credit risks which can limit their ability to secure capital to grow their businesses (Henderson et al., 2015). The disproportionate difference between White businesses and Black and Hispanic businesses was heightened by the COVID-19 pandemic. Farrell et al. (2019) found that in majority Black or Hispanic communities, “most small businesses had fewer than twenty-one cash buffer days.” For example, 94% and 89% of businesses in majority Black and Hispanic communities respectively reported that they had fewer than a 14-day “cash-buffer” in 2019 compared to 35% of White businesses (Farrell et al., 2019).

Prior to the pandemic when small business owners were asked what actions they would take if faced with a 2-month revenue loss, roughly 50% responded that they would use their own funds, while 17% said that they would close their business (Mills et al., 2020). The problem with this plan is that Census data indicates the median level of wealth among Black families is $9,600, and around $25,000 among Latino families compared to $172,000 among White families (U.S. Census Bureau, 2017). The effect of the pandemic only worsened the conditions of these vulnerable businesses. Throughout the pandemic, many small businesses laid off employees and changed business operations that may have resulted in decreased revenue (Bartik et al., 2020a, b; Humphries et al., 2020a, b). Women workers were especially impacted as it relates to lost jobs during the pandemic, which has exacerbated gender inequalities in the labor market (International Labour Organization, 2020).

Additionally, after COVID business restrictions were eased, customers were hesitant to spend due to economic uncertainty (Charm et al., 2021). Many also avoided the use of services such as personal care and restaurants, industries with higher levels of Black and Hispanic business ownership, out of fear of being infected by COVID-19 (Charm et al., 2021). Prior to the pandemic, there were wealth disparities across all income brackets with White households having 10 times the wealth of Black households (Kochhar & Cilluffo, 2017). It has been hypothesized that many underrepresented minorities were left more vulnerable to the pandemic due to the unmet social needs that resulted in them having to engage in occupational hazards that increased their exposure to COVID-19. A lack of financial resources due to years of structural racism in which societies have reinforced inequitable systems (Bailey et al., 2017) may explain why business owners of color were left with fewer options to help them remain in the business sector. Early in the pandemic, Time predicted that people with low incomes—disproportionately people of color—would face higher exposure to the virus because they are less likely to be able to work from home, more likely to work in service sectors, and more likely to live in multi‐family apartment buildings (Vesoulis, 2020). They also had less access to sick leave and medical care if they became sick (Vesoulis, 2020).

A growing body of interdisciplinary literature has also begun to pay critical attention to the gender dynamics in entrepreneurship (Gompers & Wang, 2017; Jha et al. 2018; Villaseca et al., 2021). Prior research has explored the obstacles that women entrepreneurs face in starting or growing their businesses (Roper & Scott, 2009). In times of COVID-19, Villaseca et al., (2021) have explored women entrepreneurs’ approaches to acquiring financial and other resources. Women entrepreneurs have been dealing with not only unprecedented challenge for economies and companies due to the COVID-19 pandemic, but also trying to overcome pre-existing barriers including lack of access to finance, as well as lack of networks and mentors (Villaseca et al., 2021). Lack of networks and mentorship is an evolutionary dilemma in that it decreases women entrepreneurs’ ability to comprehend, apply new information, and adapt to new situations in a way that those with tighter and more specialized network connections are able to (Foster & Metcalfe, 2012; Weick, 1996).

The Present Study

The current study aimed to examine the associations of race/ethnicity and gender with the impact of the COVID-19 pandemic on business among older entrepreneurs. Specifically, we further evaluated whether older entrepreneurs have experienced the following: business closures, changes in new procedures, workers quitting, and financial hardship. Based on previous research, we hypothesized that underserved racial/ethnic entrepreneurs would be more likely to experience harsher impacts of the COVID-19 pandemic on their businesses than their White counterparts. Likewise, women entrepreneurs would be more likely to experience adverse impact of the pandemic on their businesses than men entrepreneurs. Our analyses also are adjusted for potential confounding factors (i.e., health conditions, demographic, and socioeconomic characteristics).

Methods

Data and Sample

Data are from the 2020 Health and Retirement Study (HRS), a biennial nationally representative longitudinal survey of Americans aged 51 and older. The HRS added a special topic module on COVID-19 and the data collection period for the 2020 interview was March 2020 through June 2021 (Health and Retirement Study, 2022). HRS is supported by the National Institute on Aging and the Social Security Administration and conducted by the Institute for Social Research at the University of Michigan. The HRS survey provides data on health, work, and economic circumstances associated with aging at both individual and population levels (Sonnega et al. 2014). More details on study design are described in Sonnega et al. (2014) and Health and Retirement Study (2022).

Inclusion and Exclusion Criteria

This study limited analysis to individuals who were an owner or a partner in a business when the COVID-19 pandemic started in early 2020. Among the 10,307 respondents, 834 (8.1%) were business owners or partners. We excluded respondents ages 50 and younger (n = 32) in the analyses to focus on older entrepreneurs. Our analytic sample included 802 persons aged 51 and older who were an owner or a partner when the pandemic started to examine the impact of the pandemic on businesses. We also excluded participants who did not report their race/ethnicity (n = 11). Our final analyses included a total of 791 entrepreneurs aged 51 and older based on all our inclusion/exclusion criteria. All participants provided informed consent with study approval from the University of Michigan Institutional Review Board.

Measures

Dependent Variables

Changes in Business Due to the COVID-19 Pandemic

Our primary outcomes refer to changes in one’s business due to the COVID-19 pandemic. Respondents were asked whether their business was affected by the pandemic with a question, “Was your business affected because of the coronavirus pandemic?” (yes; no). Furthermore, respondents were asked a series of questions assessing the impact of the pandemic on their businesses. Our outcomes encompass four types of changes in business due to the COVID-19 pandemic. The survey evaluated whether a respondent (a) closed business (“Did you have to close down business?), (b) instituted new procedures (“Did you have to institute new procedures, like sanitizing and/or distancing?”), (c) experienced staff shortages due to workers quitting or no longer coming to work (“Did workers quit or stop coming into work?”), and (d) difficulty paying regular bills ("Did you miss any regular payments on rent, mortgage, credit cards, other debt, utilities, or insurance since the start of the pandemic?") (yes; no).

Independent Variables

Race/Ethnicity.

By combining two variables, a respondent’s race (White/Caucasian, Black/African American, or Asian/other races) and Hispanic status (Hispanic or non-Hispanic), we created four categories of race/ethnicity: non-Hispanic White (reference), non-Hispanic Black, Hispanic of any race, and non-Hispanic Asian/other race.

Gender.

Gender was dichotomously coded: women and men (reference).

Covariates

We controlled for several factors that may confound the associations among race/ethnicity, gender, and changes in business during the pandemic. Health covariates included self-rated health (range: 1 = poor; 5 = excellent), chronic health conditions (high blood pressure, diabetes, cancer, lung disease, heart problems, stroke, psychiatric problems, and arthritis, range: 0 to 8), and depressive symptoms (range: 0 to 8). Depressive symptoms were assessed using the eight-item version of the Center for Epidemiologic Studies Depression (CES-D) scale (Radloff, 1977). Demographic and socioeconomic characteristics included age, marital status, educational attainment, total household income, total household non-housing wealth, and total household housing wealth. To reduce skewness, we used the natural logarithm for household income and wealth.

Analytic Plan

We started with descriptive analyses for the core variables of the study (Table 1). We estimated binary logistic regression models predicting whether a respondent’s business was affected by the COVID-19 pandemic among older American business owners/partners when the pandemic started (Specification 1, Table 2). Furthermore, we estimated multivariate logistic regression models to predict each of four specific types of changes in business outcomes (Specification 2, business closures; Specification 3, institute new procedures; Specification 4, workers quitting; and Specification 5, difficulty paying regular bills). We evaluated the effects of our focal measures—race/ethnicity and gender—on changes in business, net of all covariates. All models were adjusted for health conditions, demographic and socioeconomic characteristics.

Table 1

Sample characteristics, HRS COVID-19 sample, 2020–2021 (N = 791)

Variables	Mean ± SD (Median) or %
Age (in years)	64.60 ± 8.13 (63)
51–59	31.2
60–69	45.8
70–79	16.1
80 +	7.0
Gender
Men	56.3
Women	43.7
Marital status
Married	74.6
Separated or divorced	14.9
Widowed	7.4
Never married or other	3.2
Race and ethnicity
non-Hispanic White	60.2
non-Hispanic Black	17.6
Hispanic of any race	14.9
non-Hispanic Asian/other race	7.3
Years of education	14.00 ± 3.06 (14)
Total household income ($)	187,892.26 ± 372,576.72 (95,279)
Total non-housing wealth ($)	1,023,762.15 ± 3,049,407.13 (184,000)
Total housing wealth ($)	272,536.07 ± 966,580.98 (140,000)
Self-rated health (1–5)	3.41 ± 0.95 (3)
Poor	2.1
Fair	15.0
Good	34.0
Very good	37.5
Excellent	11.3
Depressive symptoms (CES-D score, 0–8)	1.18 ± 1.82 (0)
Number of chronic health conditions (0–8) a	1.78 ± 1.40 (2)

Notes: aSum of chronic health conditions included ever had high blood pressure, diabetes, cancer, lung disease, heart problems, stroke, psychiatric problems, and arthritis

Table 2

Multivariate logistic regression predicting the impact of the COVID-19 pandemic on business among older entrepreneurs, HRS COVID-19 sample, 2020–2021 (N = 791)

	Specification 1			Specification 2			Specification 3			Specification 4			Specification 5
	Business was affected			Closed business			New procedures			Workers quitting			Missed regular payments
	OR	[95% CI]		OR	[95% CI]		OR	[95% CI]		OR	[95% CI]		OR	[95% CI]
Race and ethnicity
non-Hispanic White (ref.)
non-Hispanic Black	0.787	[0.46, 1.36]		2.307**	[1.33, 3.99]		2.442**	[1.32, 4.50]		2.947***	[1.68, 5.18]		2.879***	[1.66, 4.99]
Hispanic	0.626	[0.36, 1.08]		1.080	[0.58, 2.00]		2.272*	[1.11, 4.66]		2.264**	[1.21, 4.25]		2.347**	[1.26, 4.37]
non-Hispanic Asian/other race	1.221	[0.54, 2.79]		0.937	[0.43, 2.05]		1.948	[0.82, 4.61]		1.091	[0.47, 2.56]		3.108**	[1.44, 6.73]
Gender
Men (ref.)
Women	1.049	[0.72, 1.54]		2.113***	[1.40, 3.18]		1.218	[0.80, 1.86]		1.092	[0.70, 1.70]		1.066	[0.68, 1.67]
Intercept	10.630*			43.761*			1.602			0.515			33.059*
-2 Log likelihood	712.106			599.346			574.942			527.830			534.829
Nagelkerke R2	0.056			0.220			0.105			0.131			0.267

Notes: Exponentiated betas (odds ratios, OR) and confidence intervals [95% CI] are presented. All models are adjusted for health conditions (i.e., self-rated health, comorbid chronic conditions, and depressive symptoms), demographic and socioeconomic characteristics (i.e., age, educational attainment, marital status, log of total household income, log of total non-housing wealth, and log of total housing wealth)

ref., reference group; statistical significance denoted as *p < .05; **p < .01; ***p < .001

Results

Descriptive Statistics

Descriptive statistics for the sample characteristics are presented in Table 1. The respondents’ mean age was 64.6 (SD = 8.1) and the median was 63. The sample included more men (56.3%) and married (74.6%) business owners or partners. Regarding race/ethnicity, 60.2% (n = 476) of participants were non-Hispanic Whites, 17.6% (n = 139) were non-Hispanic Blacks, 14.9% (n = 118) were Hispanics of any race, and 7.3% (n = 58) were non-Hispanic Asian/other race. The mean years of educational attainment was 14. The mean total household income was $187,892 and the median was $95,279. The mean total household non-housing wealth (i.e., liquid assets) was $1,023,762 and the median was $184,000. The mean total household housing wealth (i.e., non-liquid assets) was $272,536 and the median was $140,000.

Healthwise, 17% of the sample self-reported as poor (2.1%) or fair (15%), whereas 34% reported as good, 37.5% reported as very good, and 11.3% reported as excellent health. The average of depressive symptoms and chronic medical conditions were 1.2 and 1.8, respectively.

Changes in Business Due to the COVID-19 Pandemic Among Older Entrepreneurs

Approximately one in four older business owners or partners reported no impact of the pandemic on their business (24.2%) in the USA; we observed that nearly 76% of business owners or partners reported that their business was affected by the COVID-19 pandemic. Furthermore, we explored how their business was specifically affected because of the COVID-19 pandemic. We observed that 43.9% of respondents had to close their business; the majority of the closures were temporary (81%) but 19% experienced a permanent closure. More than four in five experienced substantial changes in business volume (82%).

Nearly every business owner or partner experienced decreases in their business volume (90.4%) during the COVID-19 pandemic. Most business owners or partners (70.8%) had to institute new procedures such as sanitizing or new arrangements for distancing. Additionally, 28.8% of business owners or partners experienced workers quitting during the pandemic. Because of the COVID-19 pandemic, about 16% switched to new business ventures. Additionally, 30.9% of participants also reported that their business was affected in other ways. Regarding economic hardships, about one-fifth of business owners or partners reported that they missed regular bill payments due to the COVID-19 pandemic (18.3%).

Multivariate Logistic Regression Analyses

We estimated binary logistic regression models predicting whether a respondent’s business was affected by the COVID-19 pandemic among older American business owners or partners when the pandemic started (Table 2). As shown in Specification 1 in Table 2, regardless of race/ethnicity and gender, overall respondents reported that their businesses were affected by the COVID-19 pandemic.

Furthermore, we estimated a series of binary logistic regression models predicting how one’s business was affected by the COVID-19 pandemic (Table 2). More specifically, this study investigated the prospective associations of race/ethnicity and gender with the four different types of changes in business due to the COVID-19 pandemic: business closure (Specification 2), new procedures (Specification 3), workers quitting (Specification 4), and missing any regular bill payments (Specification 5).

The results presented in Table 2 showed that non-Hispanic Black business owners/partners had significantly higher odds of facing business closure (OR = 2.31, p < 0.01), new procedures (OR = 2.44, p < 0.01), workers quitting (OR = 2.95, p < 0.001), and missing any regular payments (OR = 2.88, p < 0.001), relative to non-Hispanic White business owners/partners after controlling for gender, health conditions, demographics, and socioeconomic characteristics. Compared with non-Hispanic White business owners/partners, Hispanics had also significantly higher odds of instituting new procedures (OR = 2.27, p < 0.05), workers quitting (OR = 2.26, p < 0.01), and missing any regular payments (OR = 2.35, p < 0.01) due to the pandemic after controlling for gender, health conditions, demographics, and socioeconomic characteristics. Similarly, non-Hispanic Asian/other races business owners/partners were significantly more likely to report difficulty paying regular bills such as rent, mortgage, credit cards, or insurance since the start of the pandemic than their non-Hispanic Whites counterparts (OR = 3.11, p < 0.01).

Moreover, the results presented in Table 2 showed the association between gender and changes in business due specifically to the COVID-19 pandemic. Notably, women business owners/partners were significantly more likely than men to close their businesses since the COVID-19 pandemic started (OR = 2.11, p < 0.001) after controlling for race/ethnicity, health, demographics, and socioeconomic factors. The associations of gender with instituting new procedures (OR = 1.22, p = 0.363), workers quitting (OR = 1.09, p = 0.698), and missing any regular payments (OR = 1.07, p = 0.781) were statistically nonsignificant after adjusting for race/ethnicity, health conditions, demographics, and socioeconomic factors in our sample of older US entrepreneurs.

Discussion

Our study is the first we know of to explore whether underrepresented older racial/ethnic minorities and women entrepreneurs were particularly vulnerable to the devastating impact during the COVID-19 pandemic. Our analyses yielded two main findings. First, although the COVID-19 pandemic affected every business, the devastating impact of the pandemic on business was observed in non-Hispanic Blacks, Hispanics, and non-Hispanic Asian/other races (versus non-Hispanic Whites). We found evidence that non-Hispanic Black entrepreneurs were significantly more likely to close businesses than their non-Hispanic Whites counterparts. Non-Hispanic Blacks, Hispanics, and non-Hispanic Asian/other races entrepreneurs were significantly more likely to report difficulty paying regular bills since the start of the COVID-19 pandemic than their non-Hispanic Whites counterparts. Furthermore, non-Hispanic Black and Hispanic entrepreneurs were significantly more likely to institute new procedures and experience workers quitting than non-Hispanic White entrepreneurs. Second, women entrepreneurs were significantly more likely to close businesses than men entrepreneurs. Women entrepreneurs were the ones hit harder during the COVID-19 pandemic. These significant associations persisted after adjusting for health, demographics, and socioeconomic characteristics.

Reasons for higher incidences of closures for Black and Hispanic businesses during the pandemic might be due to a combination of geographical restraints, limited access to the PPP (paycheck protection program), and the financial vulnerability of businesses (Orozco et al., 2020; Mills & Battisto, 2020; Zhou, 2020). Because financing the business is one of the biggest challenges for entrepreneurs (Coleman et al., 2016; Amrita et al., 2018), these results suggest that targeted interventions, including financial assistance, may be particularly effective in meeting the unmet needs of older entrepreneurs during and after the pandemic. To help businesses impacted by disruptions to their operations due to COVID-19 closures, the federal government implemented several programs to keep businesses afloat. One program implemented is the PPP. The PPP is a loan program administered by the U.S. Small Business Administration (SBA), and its purpose is to help employers keep their workforces employed during the COVID-19 crisis (U.S. SBA, n.d.). However, recent studies have shown that the effectiveness of the PPP was limited and that many businesses who may have benefited from the program were not able to obtain funding (Bartik et al., 2020a, b; Doniger & Kay, 2021). This illustrates the emotional strain that many were faced with when having to determine whether they would continue to operate their business at some level even at the risk of their own health.

Minority-owned businesses, in particular, struggled to gain access to loans through the federal government’s PPP (Liu & Parilla, 2020). While the PPP was created to help businesses avoid workforce reductions (U.S. SBA, n.d.), many Black- and Hispanic-owned businesses were denied these loans and experienced longer wait times for loan dispersals compared to White businesses (Liu & Parilla, 2020). Initially, the Treasury Department did not consistently track the race and ethnicities of PPP recipients; however, a geographic analysis of locations of businesses that received PPP loans revealed that communities of color were least likely to receive a PPP loan (Liu & Parilla, 2020). These businesses were also least likely to have a banking relationship with larger, traditional banks that were originally tapped to disburse PPP loans. Many of these banks would only work with established customers leaving many Black- and Hispanic-owned businesses without access to PPP funds due to having banking relationships with financial institutions not approved to disburse PPP loans or being underbanked or unbanked. Previously existing financial barriers coupled with the inability to gain access to PPP loans resulted in revenue declines for many Black- and Hispanic-owned businesses (Vinopal, 2021). However, there appears to be differences in revenue declines as well. A report that evaluated small business declines between February and April 2020 found that Black-owned businesses declined by 41%, Hispanic-owned businesses by 32%, and White-owned businesses by only 17% (Fairlie, 2020). In many instances, these businesses would be unable to sustain the revenue decline and face the risk of ultimately closing their businesses.

During the COVID-19 pandemic, we are witnessing that the access to financing sources is critical for business survival in times when entrepreneurs need cash urgently (Bartik et al., 2020a, b; Kuckertz et al., 2020). The theory of the three “Ms” (Bates et al., 2007) identifies three main barriers to overcome: markets, money, and management. For women entrepreneurs, there are additional obstacles, which raise the theory of the five “Ms” (Brush et al., 2009): motherhood (caregiving for family members in general), and the macro- and meso-environment. Indeed, when the market was most constrained during a recession, women-owned businesses were significantly more likely to be denied funding than the ones owned by their men counterparts (Thébaud & Sharkey, 2016). Thébaud and Sharkey (2016) demonstrate that macroeconomic conditions could be a moderator of the probability of gender-based discrimination in entrepreneurship financing, suggesting that gender-differentiated standards of performance are being applied in these uncertain times.

Limitations and Future Research

Several limitations of the current study pave the way for future research. First, we used the nationally representative data of older adults in the USA. In the context of the global consequences of the outbreak, future studies should use data that allows researchers to explore further impact of the COVID-19 pandemic on businesses during the COVID-19 pandemic in other countries across the life course. Second, we were unable to discuss our findings by the type of business due to lack of data. Future research is warranted to explain further some of the observed gaps and concentrated adverse experiences by the type of business. Third, the mandates of the lockdowns and restrictions of social distancing varied by type of industry and by state, county, and city in the USA. These legal requirements may have affected business closures. Temporary closures occurred in most of the nonessential industries due to the governmental mandates, but we were unable to specify the industry and geographical residence of respondents due to data restrictions. Fourth, it should be noted that the data from the 2020 HRS COVID-19 project that was used for this analysis was produced under an accelerated time frame. As such, the data were collected at the respondent level and relied on self-reported responses. Our measure of perceived health status was assessed with a single item, self-rated health. Future studies should include more comprehensive ratings of health condition that allow for increased variability. Finally, with the data being collected in waves, we can only interpret the effects on older adult business owners in operation in the pandemic. However, given that additional data will be collected and released after the COVID-19 pandemic, this allows for post-pandemic recovery longitudinal effects to be explored across the sample once those data are made available. Future studies are warranted to evaluate the protective effects of coping resources and financial literacy on post-pandemic economic recovery among older entrepreneurs.

Implications and Conclusion

For many business owners, the assets in their business were doubling as their retirement accounts. If an individual worked hard to build a successful business, this would provide an opportunity to sell the business and its assets, at a later date, to have financial support once they are no longer able to run the business. In instances where owners unexpectedly closed their businesses permanently, as seen during the pandemic, selling their business assets for retirement is no longer an option. During the pandemic, this situation may have been exacerbated for older business owners since they had fewer years left to pay off debt and rebuild savings, but also did not have the savings or income to carry them when their businesses were required to close in compliance with stay-at-home orders. This raises the question of whether older entrepreneurs engaged in business planning prior to and throughout the life cycle of their business. In accordance with evolutionary economic based reasoning, it would follow that entrepreneurs with less resources and capabilities would be less likely to adapt to sudden changes such as those brought about by the pandemic.

Older adults may be more vulnerable to the impact of the pandemic due to decreased economic security or having insufficient income to cover living costs (Mutchler et al., 2018). About half of older adults between the ages of 60 to 79 do not have emergency savings and among those 80 years of age and over, close to 40% lack emergency savings (Harvey, 2019). Economic security has been especially elusive among older women and racial/ethnic minorities (Mutchler et al., 2017). While the older population was prioritized for vaccine distribution, less attention has been paid to those older adults who were still working when the pandemic hit and the economic challenges that they faced as a result. Approximately 35 million Americans aged 55 years and older were participating in the labor force prior to the pandemic (Bureau of Labor Statistics, 2020). However, it should be noted that many older workers were employed in industries that were especially impacted by the pandemic resulting in elevated risk of unemployment and income loss (Bureau of Labor Statistics, 2020). For those already in precarious economic situations, they may have opted to enroll for Social Security benefits earlier than anticipated (Rutledge et al., 2012) in an effort to not join the 10% of Americans 65 years or older who live in poverty (Semega et al., 2019). This behavior, in and of itself, exemplifies vulnerability arising from experience—living or being in a world in which we have devalued a group of people based on their age, race, social position, and resources.

From a policy perspective, support for older underserved racial/ethnic and women entrepreneurs should focus on accessibility to financial planning services, capital, and support packages as well as legislative support for ensuring business continuity and success. Policymakers should review and repeal practices, policy, and legislations that discriminate against older adults, racial/ethnic minorities, and women entrepreneurs. Financial service providers should also attempt to remedy these historical barriers by providing financial access to older racial/ethnic minorities and women entrepreneurs. Specialized lending and financial education services for older entrepreneurs could aid in their economic recovery from the pandemic. Moreover, increased business knowledge and resources on how to adapt one’s business to increase survival when crises arise will serve to create more sustainable businesses in the long run.

Data Availability

The authors used a public survey data, the Health and Retirement Study. All participants provided informed consent with study approval from the University of Michigan, Institutional Review Board.