Examining the Pandemic's Economic Effects on Women

This issue of Consumer & Community Context is being released in conjunction with the Federal Reserve Board's Gender and the Economy Conference. Together, these efforts demonstrate the Federal Reserve's interest in understanding the barriers to gender equality and strategies that achieve the benefits of a more inclusive economy. Indeed, gender disparities in the labor market, education, and other areas impede opportunity and progress for many women and present a loss to our economy and communities. Research into the causes and effects of these barriers is particularly important in this moment as the economic pains of COVID-19 have fallen disproportionately on women, especially on women of color and those with children.

In this issue, researchers from the Federal Reserve System present analysis of the pandemic's economic impact on women. The first article finds that the pandemic disrupted childcare or in-person schooling for nearly 70 percent of parents, with 25 percent of mothers reporting that they did not work or worked less as a result. The second shows that single mothers had slim financial cushions going into the COVID-19 recession and had higher unemployment rates during the recession than single fathers and women without children. The third notes that, in 2020, women were more likely to have credit card debt, to be denied or approved for less when they applied for credit products, and to put off applying for credit at higher rates than men. Finally, the fourth concludes that businesses owned by women, and, in particular, by Black women, faced more financial and operational challenges during the pandemic and were less likely to receive financing than men-owned businesses.

Thank you for your interest in Consumer & Community Context. To subscribe to future issues, email [email protected]. For past issues, visit https://www.federalreserve.gov/publications/consumer-community-context.htm.

Footnotes

Note: Anna Alvarez Boyd, senior associate director in the Federal Reserve Board Division of Consumer and Community Affairs, authored this introduction.

Childcare Disruptions and Mothers' Availability to Work during the Pandemic: Evidence from the Survey of Household Economics and Decisionmaking

by Alicia Lloro, Federal Reserve Board Division of Consumer and Community Affairs

The pandemic disrupted childcare or in-person schooling for nearly 70 percent of parents, with 25 percent of mothers reporting they did not work or worked less as a result. Black mothers were nearly twice as likely as White mothers to report not working or working less due to disruptions in childcare or in-person schooling.

Figure 1. Two-thirds of parents experienced childcare or in-person K–12 schooling disruptions since the pandemic's onset
Figure 1. Two-thirds of parents experienced childcare or in-person K–12 schooling disruptions since the pandemic's onset

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Note: Among parents. Parental status is based on whether the respondent lived with their own children under age 18. Respondents could choose both options.

Source: 2020 Survey of Household Economics and Decisionmaking.

With the onset of the COVID-19 pandemic in March 2020 and the subsequent closure of schools and childcare centers, much has been said about the impact on mothers' ability to work, particularly mothers of color.1

Before the pandemic, childcare responsibilities had already prevented many mothers from entering or fully participating in the labor force.2 According to the 2019 Survey of Household Economics and Decisionmaking (SHED), 20 percent of mothers said that childcare or family obligations contributed to their not working, compared with 4 percent of fathers.3

During the COVID-19 pandemic, family and childcare responsibilities increased for many parents due to school closures and disruptions to childcare. Since the onset of the pandemic, one-fourth of all parents experienced disruptions to their childcare (figure 1).4 Additionally, 55 percent of all parents said that their youngest school-aged child's classes involved distance learning as of November 2020, when the latest SHED was conducted.

Childcare Challenges a Barrier to Employment for Many, Particularly Black Mothers

It is clear from the SHED data that childcare reflects a barrier for many mothers who want to work. But did the increased need for childcare further depress employment?

The evidence for mothers overall is somewhat mixed. One-fourth of mothers said they were not working or working less because of disruptions to childcare or in-person schooling since March 2020 (figure 2). On the other hand, results from a separate SHED question suggest that while childcare remained a barrier to employment during the pandemic, childcare and family obligations did not appear to further depress employment overall: one in five mothers said that childcare or family obligations contributed to their not working in 2020, which was unchanged from 2019.5

It is clear from the SHED data that childcare reflects a barrier for many mothers who want to work. But did the increased need for childcare further depress employment? The evidence for mothers overall is somewhat mixed.

Looking by race and ethnicity shows similar mixed results for Hispanic and White mothers: sizable shares said they were not working or working less due to childcare or K–12 schooling disruptions since the onset of the pandemic in March 2020, yet the share citing childcare or family responsibilities as a reason for not working was similar in 2019 and 2020.6

Figure 2. One-fourth of mothers said they were not working or working less due to childcare or in-person K–12 schooling disruptions
One-fourth of mothers said they were not working or working less due to childcare or in-person K–12 schooling disruptions

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Note: Key identifies bars in order from left to right. Since COVID-19 pandemic onset in March 2020. Other races/ethnicities not shown due to sample size limitations. Parental status is based on whether the respondent lived with their own children under age 18.

Source: 2020 Survey of Household Economics and Decisionmaking.

Among Black mothers, however, the results indicate that childcare was a barrier to employment for many and that the prevalence of childcare or family responsibilities as a reason for not working grew during the pandemic. Thirty-six percent of Black mothers reported not working or working less because of disruptions to childcare or in-person K–12 schooling. For lower-income Black mothers, this share was over 40 percent. Moreover, in 2020, one in four Black mothers said that childcare or family obligations contributed to their not working, which was nearly double the 13 percent that said so in 2019.

Many mothers who were not working or working less because of childcare or schooling disruptions faced substantial financial difficulty. As of fall 2020, just over half were able to pay their current month's bills in full, compared with nearly three-fourths of mothers overall.

Federal Reserve Bank of Dallas researchers also found that labor force participation among Black mothers was particularly affected by the pandemic.7 They compared the decline in labor force participation between Black mothers and Black women without children and found that Black mothers saw much larger declines (a 6 percentage point decline in labor force participation among Black mothers versus a 2 percentage point decline for Black women without children).

Such differences between mothers and women without children were not seen among White or Hispanic women. Taken together with SHED findings, these results suggest childcare issues disproportionately affected the employment of Black mothers in 2020.

Many Mothers Experienced Financial Fragility

Many mothers who were not working or working less because of childcare or schooling disruptions faced substantial financial difficulty. As of fall 2020, just over half were able to pay their current month's bills in full, compared with nearly three-fourths of mothers overall. Only 37 percent said they would cover a $400 expense with cash, savings, or a credit card paid off at the next statement (referred to, altogether, as "cash or its equivalent").8 Additionally, only 46 percent of mothers who were not working or working less said they were doing at least okay financially, compared with 65 percent of mothers overall (figure 3).

Two things may explain these results on financial fragility: (1) mothers not working or working less because of childcare or schooling disruptions may have already been more likely to face financial fragility prior to the pandemic; and (2) childcare and schooling disruptions, and their impact on mothers' ability to work, may have increased financial fragility. Evidence from the subset of respondents who participated in the SHED before and after the pandemic suggest that both factors were at play.9

Figure 3. Mothers not working or working less due to childcare or in-person K–12 schooling disruptions were more likely to exhibit financial fragility
Figure 3. Mothers not working or working less due to childcare or in-person K–12 schooling disruptions were more likely to exhibit financial fragility

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Note: Key identifies bars in order from top to bottom. Since COVID-19 pandemic onset in March 2020. Cash or its equivalent is defined as cash, savings, or a credit card paid off at the next statement. Parental status is based on whether the respondent lived with their own children under age 18.

Source: 2020 Survey of Household Economics and Decisionmaking.

In support of the first factor, figure 4 shows that mothers who were not working or working less because of disruptions to childcare or in-person K–12 schooling during the pandemic already had lower financial well-being going into the pandemic. Fifty-six percent said they were doing at least okay financially in the fall of 2019, compared with 74 percent doing at least okay in the fall of 2019 among all other mothers. Other measures of financial fragility, such as ability to pay bills, showed a similar pattern.

Figure 4 also provides insight into the second factor—i.e., whether childcare and schooling disruptions, and their effect on mothers' ability to work, increased financial fragility.

Figure 4. Mothers not working or working less due to childcare or in-person K–12 schooling disruptions saw financial well-being declines after the pandemic's onset
Figure 4. Mothers not working or working less due to childcare or in-person K–12 schooling disruptions saw financial well-being declines after the pandemic's onset

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Note: Key identifies lines in order from top to bottom.

Source: 2020 Survey of Household Economics and Decisionmaking.

Examining the financial trajectory of mothers before and after the onset of the pandemic shows that mothers who were not working or working less because of disruptions to childcare or K–12 schooling saw a large decline in financial well-being. The share doing at least okay financially fell 14 percentage points, from 56 percent in 2019 to 41 percent in 2020.10 This large decline supports the notion that childcare and schooling disruptions, and their effect on mothers' ability to work, increased financial fragility.11

Addressing Childcare Issues with Targeted, Long-Run Support

For many parents, family and childcare responsibilities increased during the pandemic due to school closures and disruptions in childcare services. For Black mothers in particular, these disruptions limited their ability to work. The SHED findings also showed the substantial financial stress faced by mothers whose employment was affected by childcare or K–12 schooling disruptions during the pandemic.

These findings underscore the support that families—and especially mothers—need to balance childcare responsibilities with work. While the stimulus payments and expanded unemployment insurance provided during the COVID-19 pandemic helped many families, these results suggest additional measures may have been beneficial.

Examining the financial trajectory of mothers before and after the onset of the pandemic shows that mothers who were not working or working less because of disruptions to childcare or K–12 schooling saw a large decline in financial well-being.

Moreover, given that childcare issues predate the pandemic, the COVID-19 specific stimulus measures likely will not address them in the long run. To the extent that childcare continues to be a barrier to employment going forward, expansion of affordable, quality childcare may help increase mothers' ability to work and thereby promote greater financial well-being.

Footnotes

 1. For example, see Misty L. Heggeness et al., "Tracking Job Losses for Mothers of School-Age Children during a Health Crisis," U.S. Census Bureau, https://www.census.gov/library/stories/2021/03/moms-work-and-the-pandemic.html; and Claire Cain Miller, "The Pandemic Created a Child-Care Crisis," New York Times, May 17, 2021, https://www.nytimes.com/interactive/2021/05/17/upshot/women-workforce-employment-covid.html. The World Health Organization declared COVID-19 a pandemic on March 11, 2020 (see https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020). Return to text

 2. Taryn W. Morrissey, "Child Care and Parent Labor Force Participation: A Review of the Research Literature," Review of Economics of the Household 15 (2017): 1–24, https://doi.org/10.1007/s11150-016-9331-3Return to text

 3. The 2019 Survey of Household Economics and Decisionmaking was conducted in the fall of 2019. Return to text

 4. Parental status is based on whether the respondent lived with their own children under age 18. Return to text

 5. Future work will explore whether survey question design can explain, at least in part, why these two measures differ. Return to text

 6. While the SHED was weighted to match the race and ethnicity of the entire U.S. adult population, evidence shows that the Hispanic population in the SHED was somewhat more likely to speak English at home than the overall Hispanic population in the United States. According to the SHED, 64 percent of Hispanic adults speak Spanish at home versus 74 percent in the 2019 American Community Survey. See table B16006 at https://data.census.gov. See the Report on the Economic Well-Being of U.S. Households in 2017 (https://www.federalreserve.gov/publications/2018-economic-well-being-of-us-households-in-2017-preface.htm) for a comparison of results to select questions administered in Spanish and English. Return to text

 7. Tyler Atkinson and Alex Richter, "Pandemic Disproportionately Affects Women, Minority Labor Force Participation," Federal Reserve Bank of Dallas website, https://www.dallasfed.org/research/economics/2020/1110Return to text

 8. The sample size was not large enough to disaggregate these results by race and ethnicity. Return to text

 9. One feature of the SHED is that a subset of respondents also participated in prior waves of the survey. About one-third of respondents who participated in the fall 2020 SHED also participated in the fall 2019 SHED. Return to text

 10. Difference of 14 percentage points reflects rounding. Return to text

 11. This finding alone does not necessarily imply causality. Return to text

Single Mothers Have Little Wealth to Withstand Outsized COVID-19 Impact

by Ana Hernández Kent, Federal Reserve Bank of St. Louis External Engagement & Corporate Communications Division

Single mothers had slim financial cushions going into the COVID-19 recession and had higher unemployment rates during the recession than single fathers and women without children. Black and Hispanic single mothers, in particular, struggled financially during the pandemic.

As the COVID-19 pandemic took hold in the United States and a recession began, many families faced sudden economic instability. The overall unemployment rate shot up to 14.8 percent in April 2020 and reached unprecedented highs for certain industries, like leisure and hospitality (39.3 percent).1 As a result, many individuals with minimal savings faced financial difficulties.

This article examines the particularly slim financial cushion single mothers had heading into the COVID-19 recession. As a group, these women had very low levels of wealth prior to the recession and were more likely to indicate they were experiencing financial instability. During the recession, their situation worsened, as single mothers had high unemployment rates and dropped out of the labor force at higher rates than single fathers and women without children. This research also touches on the gender wealth gap as of 2019, how the COVID-19 recession affected the financial well-being of single mothers, and what these trends might mean for the future of women's economic stability.

COVID-19 Has Disproportionately Affected Women Financially

The COVID-19 recession was very different from those in the past, not just because it resulted from a health crisis—rather than a recalibration of a malfunctioning economy—but also because it disproportionately affected women and particularly women of color.2 Past recessions (such as the Great Recession) had typically resulted in more job losses for men due to the nature of job types affected and the gendering of industries. However, because in-person, service-sector jobs (which disproportionately employ women) were hard-hit during this recession, women's unemployment rate jumped more than men's and remained higher through October 2020.

In addition, mothers were pushed out of the labor force at higher rates than fathers and were less likely to return.3 As will be discussed further in this article, working mothers may have had a more difficult time staying engaged in the labor force due to the burdens of childcare and eldercare and disruptions to schooling.

Single Mothers Have Very Little Wealth

When an unexpected financial emergency occurs, particularly one that lasts for months, savings and liquid assets are critical for food security, housing stability, and financial well-being.4 However, among singles (never-married or divorced, separated or widowed), mothers by far had the lowest levels of family wealth, with about $7,000 at the median (see figure 1).5 Single women without children had over nine times more wealth than single mothers.6 Single fathers, on the other hand, had more than eight times the wealth of single mothers. Furthermore, they did not experience a wealth penalty associated with parenthood, meaning their wealth was not significantly different from that of single men without children.

Single women without children had over nine times more wealth than single mothers. Single fathers, on the other hand, had more than eight times the wealth of single mothers.

Notably, these statistics illustrate how wealth levels between singles did not significantly differ from each other except for single mothers, who had much lower wealth than all other groups. Due to limitations of this dataset, causal conclusions cannot be drawn. In other words, motherhood may negatively impact women's wealth (e.g., through paying for childcare and other added expenses), single women with less wealth may be more likely to become mothers, or alternative possibilities may explain this relationship. Regardless of directionality and cause, however, it is clear that single mothers had significantly fewer financial resources at their disposal in 2019 than did other single groups.7

Figure 1. Wealth for single mothers was very low in 2019
Figure 1. Wealth for single mothers was very low in 2019

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Note: Wealth is rounded to the nearest $1,000; 95 percent confidence intervals are shown; overlapping error bars indicate wealth values did not significantly differ.

Source: Federal Reserve Board's Survey of Consumer Finances and author's calculations.

Single Mothers of Color Had Much Less Wealth Than White Single Mothers

Racial and ethnic wealth gaps are ubiquitous, and Black and Hispanic women are much more likely to be single mothers than are White women (21 percent, 15 percent, and 9 percent, respectively).8 This means these mothers of color are also more likely to be the primary or sole breadwinners of their families. Therefore, mapping the financial standing of single women of color is essential to understanding the well-being of families of color and racial and ethnic wealth gaps more generally.

Single Black and Hispanic mothers each had about $4,000 in median wealth in 2019 (see figure 2). This extreme lack of a financial cushion indicates that a shock like the COVID-19 recession, as described in the next section, could have devastating effects, particularly for those who were laid off or had reduced hours.9 In contrast to mothers of color, single White mothers had $46,000, or about 11 times more wealth (see figure 2). These disparities illustrate the importance of accounting for race and ethnicity in addition to gender and parental status.

Single Black and Hispanic mothers each had about $4,000 in median wealth in 2019.... In contrast to mothers of color, single White mothers had $46,000, or about 11 times more wealth.

Wealth outcomes by race and ethnicity for single women without children mirrored the patterns found for single mothers. Single White women without children had seven to eight times as much wealth as Black and Hispanic women without children. Comparing women of the same race and ethnicity, single women without children consistently had higher wealth than mothers. However, these differences were not statistically significant for women of color and large gaps with White women remained, as shown in figure 2.

Figure 2. Wealth of single mothers of color much lower than that of single White mothers
Figure 2. Wealth of single mothers of color much lower than that of single White mothers

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Note: Wealth is rounded to the nearest $1,000; 95 percent confidence intervals are shown; overlapping error bars indicate wealth values did not significantly differ.

Source: Federal Reserve Board's Survey of Consumer Finances and author's calculations.

Working Mothers Face Labor Disruptions and Additional Stressors

Disparate labor force outcomes compounded financial challenges for single mothers during the COVID-19 recession. Prime-working-age mothers had higher unemployment rates than fathers during this recession despite having similar rates in early 2020.10 In fact, while the gap was only 0.2 percentage points in February 2020, by April 2020 it was 3.3 percentage points and mothers had a high unemployment rate of 13.3 percent. Additionally, mothers (particularly those with children under age five) experienced larger declines in labor force participation rates than women without children.11

Bouts of unemployment and dropping out of the labor force are detrimental to a family's financial well-being and can have long-lasting consequences.12 For example, mothers whose paid employment was affected by this recession may have drawn down assets, had reduced or no income to save, and accumulated more debt to pay for expenses than they otherwise would have. Each of these would diminish a family's wealth, constrain choices, and reduce the ability to invest in their own future and their children's.

These hardships were reflected in the data and extended well beyond the official end date (April 2020) of the COVID-19 recession. For example, one-in-five single mothers who experienced school or childcare disruptions during the COVID-19 pandemic indicated they were no longer working in November 2020.13 This rate was nearly twice that of all other parents who experienced disruptions. As mothers spend more time caring for children than fathers, it stands to reason that mothers—especially single mothers—would be more affected by virtual learning, school closures, and daycare disruptions.14

One-in-five single mothers who experienced school or childcare disruptions during the COVID-19 pandemic indicated they were no longer working in November 2020. This rate was nearly twice that of all other parents who experienced disruptions.

Among singles, unemployed mothers, in particular, reported high levels of financial instability. About one-third of single unemployed mothers were unable to pay monthly bills in full and on time, nearly half reported they were finding it difficult to get by or were just getting by, and 35 percent said they were worse off financially compared to 12 months ago. Employed mothers, other unemployed parents, and unemployed women without children struggled as well, though to a lesser degree (see figure 3). All single employed counterparts experienced greater financial stability (not shown in figure).

Figure 3. Unemployed single mothers report high levels of financial instability
Figure 3. Unemployed single mothers report high levels of financial instability

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Note: Key identifies bars in order from left to right. Responses were given in November 2020.

Source: Federal Reserve Board's 2020 Survey of Household Economics and Decisionmaking and author's calculations.

Racial and ethnic disparities were present within the group of unemployed single mothers as well. Single mothers of color were disproportionately negatively affected, as can be seen in figure 4. Strikingly, unemployed Black single mothers were more than twice as likely to be unable to pay bills than White mothers. On the other hand, unemployed mothers of each race and ethnicity had similar rates of reporting that they were worse off compared to the previous year.

Taken together, these data suggest that while subjective evaluations of financial hardship (with one's past self as the comparison) were similar, unemployed mothers of color experienced higher levels of instability in absolute terms. Given these women's very low levels of wealth, unemployment would make it very difficult to stay financially afloat.

Figure 4. Single unemployed mothers of color more likely to report struggling financially
Figure 4. Single unemployed mothers of color more likely to report struggling financially

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Note: Key identifies bars in order from left to right. Responses were given in November 2020.

Source: Federal Reserve Board's 2020 Survey of Household Economics and Decisionmaking and author's calculations.

Investing in Policies That Support Women Can Promote Broad Social and Economic Gains

Before the COVID-19 recession, women were making great strides in the labor force, education, and business. They outnumbered men in the nonfarm civilian workforce, there was a larger share of college-educated women in the workforce, and the annual growth rate of women-owned businesses was more than double that of all businesses.15 Yet, single mothers and Black and Hispanic women had very little wealth with which to bear a financial crisis.

When the economy came to a screeching halt in March 2020, many single mothers faced a variety of impossible conditions: juggling work with disrupted childcare, being laid off with little to no savings, and risking their and their families' health as they continued essential work.

Many of the stressors and responsibilities working mothers faced were not new, but the pandemic elevated these issues. Research shows that there are benefits to a stronger care infrastructure, including improved access to quality, affordable childcare.16 Research has long shown the benefits of high-quality childcare on child development, school success, and behavior.17 High-quality early education also yields a very high rate of return.18

Additionally, policies that could help women enter into and stay engaged in the labor force, such as paid family and medical leave, could also have a positive effect on closing racial employment and income gaps.19 Paid family leave has been found to support employment especially among lower-income workers and mothers.20 And recent research has shown broader potential gains to gross domestic product from closing gender and racial gaps, which suggests that addressing such issues could translate into widespread economic and social benefits.21

Based on this research, centering wealth-building and recovery efforts on single mothers, particularly mothers of color, could be beneficial given their low wealth levels and the outsized effect COVID-19 had on them. Doing so could help not only the current generation of mothers but also create a more inclusive and prosperous economy for the children they are raising.

Footnotes

 1. U.S. Bureau of Labor Statistics, "Unemployment Rate [UNRATE]," retrieved from FRED, Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/UNRATE, June 24, 2021; and U.S. Bureau of Labor Statistics, "Unemployment Rate—Leisure and Hospitality, Private Wage and Salary Workers" [LNU04032241], retrieved from FRED, Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/LNU04032241, August 4, 2021. Return to text

 2. Serdar Birinci and Aaron Amburgey, "How Job Separations Differed between the Great Recession and COVID-19 Recession," St. Louis Fed On the Economy (blog), June 22, 2021, https://www.stlouisfed.org/on-the-economy/2021/june/job-separations-differed-between-recessions; and Meredith Covington and Ana H. Kent, "The ‘She-Cession' Persists, Especially for Women of Color," St. Louis Fed On the Economy (blog), December 24, 2020, https://www.stlouisfed.org/on-the-economy/2020/december/she-cession-persists-women-of-colorReturn to text

 3. Tyler Boesch, Rob Grunewald, Ryan Nunn, and Vanessa Palmer, "Pandemic Pushes Mothers of Young Children out of the Labor Force," Federal Reserve Bank of Minneapolis website, February 2, 2021, https://www.minneapolisfed.org/article/2021/pandemic-pushes-mothers-of-young-children-out-of-the-labor-forceReturn to text

 4. Emily Gallagher and Jorge Sabat, "Cash on Hand Is Critical for Avoiding Hardship," Federal Reserve Bank of St. Louis, In the Balance(September 11, 2017), https://www.stlouisfed.org/publications/in-the-balance/2017/cash-on-hand-is-critical-for-avoiding-hardshipReturn to text

 5. Throughout this article, parenthood refers to those who have minor children living with them. These numbers come from the author's calculations of the Federal Reserve Board's 2019 Survey of Consumer Finances, https://www.federalreserve.gov/econres/scfindex.htm. Wealth is measured at the family level (for example, singles may have non-partner others living with them). Return to text

 6. Age differences may partially explain this result, as single mothers are younger on average than single women without children and have thus not had as much time to pay down debts and accumulate assets. Return to text

 7. While this article presents wealth gaps for singles, previous work has shown gender gaps for married and partnered families as well. See Ana H. Kent and Lowell R. Ricketts, "Gender Wealth Gap: Families Headed by Women Have Lower Wealth," Federal Reserve Bank of St. Louis, In the Balance (January 12, 2021), https://www.stlouisfed.org/publications/in-the-balance/2021/gender-wealth-gap-families-women-lower-wealthReturn to text

 8. Throughout this article, White and Black people are non-Hispanic, while Hispanic people may be of any race. Ana H. Kent and Lowell R. Ricketts, "Has Wealth Inequality in America Changed over Time? Here Are Key Statistics," Federal Reserve Bank of St. Louis, Open Vault(blog), December 2, 2020, https://www.stlouisfed.org/open-vault/2020/december/has-wealth-inequality-changed-over-time-key-statistics. These numbers come from the author's calculations of the U.S. Census Bureau's 2019 American Community Survey. Return to text

 9. Board of Governors of the Federal Reserve System, Economic Well-Being of U.S. Households in 2020 (Washington: Board of Governors, May 2021), https://www.federalreserve.gov/publications/files/2020-report-economic-well-being-us-households-202105.pdfReturn to text

 10. Covington and Kent, "The ‘She-Cession' Persists."   Return to text

 11. Boesch et al., "Pandemic Pushes Mothers."  Return to text

 12. Zachary Parolin, "Unemployment and Child Health during COVID-19 in the USA," The Lancet Public Health 5, no. 10 (October 2020): e521–e522, https://doi.org/10.1016/S2468-2667(20)30207-3Return to text

 13. These numbers come from the author's calculations of the Federal Reserve Board's 2020 Survey of Household Economics and Decisionmaking, https://www.federalreserve.gov/consumerscommunities/shed.htmReturn to text

 14. Almudena Sevilla and Sarah Smith, "Baby Steps: The Gender Division of Childcare during the COVID-19 Pandemic," Oxford Review of Economic Policy 36, Supplement_1 (2020): S169–S186, https://academic.oup.com/oxrep/article/36/Supplement_1/S169/5899014Return to text

 15. Richard Fry, "U.S. Women Near Milestone in the College-Educated Labor Force," Pew Research Center website, June 20, 2019, https://www.pewresearch.org/fact-tank/2019/06/20/u-s-women-near-milestone-in-the-college-educated-labor-force/; U.S. Bureau of Labor Statistics, Employment Situation News Release, January 10, 2020, https://www.bls.gov/news.release/archives/empsit_01102020.htm; and American Express, The 2019 State of Women-Owned Businesses Report (2019), https://s1.q4cdn.com/692158879/files/doc_library/file/2019-state-of-women-owned-businesses-report.pdfReturn to text

 16. Taryn W. Morrissey, "Child Care and Parent Labor Force Participation: A Review of the Research Literature," Review of Economics of the Household 15, no. 1 (March 2017): 1–24, https://link.springer.com/article/10.1007/s11150-016-9331-3Return to text

 17. Elizabeth E. Davis and NaiChia Li, "Affordable Childcare: Is There a Crisis?" Cura Reporter 3, no. 34 (Summer 2004). Return to text

 18. Arthur J. Rolnick and Rob Grunewald, "Early Childhood Development: Economic Development with a High Public Return," Federal Reserve Bank of Minneapolis website, March 1, 2003, https://www.minneapolisfed.org/article/2003/early-childhood-development-economic-development-with-a-high-public-returnReturn to text

 19. Ann Bartel et al., "Racial and Ethnic Disparities in Access to and Use of Paid Family and Medical Leave: Evidence from Four Nationally Representative Datasets," Monthly Lab. Rev. 142, no. 1 (2019); Anjali Sakaria and Jacqueline Tosto, "Paid Family and Medical Leave: Impact and Implementation," Federal Reserve Bank of Boston Issue Brief, June 19, 2018, https://www.bostonfed.org/-/media/Documents/Community%20Development%20Issue%20Briefs/cdbrief22018.pdf; and Katherine B. Stevens, Workforce of Today, Workforce of Tomorrow: The Business Case for High-Quality Childcare (Washington: United States Chamber of Commerce, June 2017), https://www.myfuturenc.org/wp-content/uploads/2018/09/Workforce-of-Today-Workforce-of-Tomorrow-Report.pdfReturn to text

 20. Heidi I. Hartmann and Jeffrey Hayes, "Estimating Benefits: Proposed National Paid Family and Medical Leave Programs," Contemporary Economic Policy 39, no. 3 (July 2021), 537–56, https://doi.org/10.1111/coep.12526; and Pamela Winston et al., Supporting Employment among Lower-Income Mothers: The Role of Paid Family Leave (Washington: U.S. Department of Health and Human Services, Assistant Secretary for Planning and Evaluation, May 2019), https://aspe.hhs.gov/reports/supporting-employment-among-lower-income-mothers-role-paid-family-leave. Return to text

 21. Federal Reserve Community Development Staff, "How Much Could U.S. States Gain by Closing Racial and Gender Gaps in the Labor Market?" Fed Communities website, June 21, 2021, https://fedcommunities.org/data/closethegaps/Return to text

Gender and Credit in 2020: Evidence from the Survey of Household Economics and Decisionmaking

by Jennifer Fernandez and Anna Tranfaglia, Federal Reserve Board Division of Consumer and Community Affairs

In 2020, women were more likely to have credit card debt, to be denied or approved for less when they applied for credit products, and to put off applying for credit at higher rates than men. Despite the challenges from the COVID-19 pandemic, these gender differences were remarkably unchanged from 2019.

The COVID-19 pandemic and subsequent recession caused financial hardships and challenges for many families. Despite unprecedented levels of financial support in the form of economic stimulus, enhanced unemployment benefits, federal student loan debt forbearance, and rental housing assistance, financial setbacks were unavoidable for many. One resource that could help individuals weather financial shocks during the uncertainty of the crisis is affordable credit. But access to credit varies across gender, race and ethnicity, and other factors.

This article provides a snapshot of the different experiences of men and women using and applying for credit during this period of financial turbulence. In it, we explore how women's credit access and credit card use varied from men's, using data from the Federal Reserve's 2020 Survey of Household Economics and Decisionmaking (SHED), which evaluates the economic well-being of U.S. households.1 We also document that men and women, overall, differ in their likelihood of having unpaid credit card debt and having a credit application be denied.

The 2020 SHED results show that these gender differences are not uniform with respect to race and ethnicity, income level, and parental status. Non-White women, lower-income women, and women living with their children routinely experienced worse credit outcomes compared to others in 2020.2 For the set of credit outcomes also included in the 2019 SHED, the gender disparities were similar.

Why Credit Access Matters

One benefit to credit access is the ability to smooth consumption when income unexpectedly declines. The large increase in unemployment due to pandemic-mitigating measures and the potential lag in receiving unemployment benefits and stimulus payments is one such example.

Since unused portions of credit card lines allow individuals to borrow money without additional lending decisions, they also are particularly advantageous when financial circumstances shift rapidly. Without access to a credit card or other forms of credit, individuals and families who are already facing income shortfalls may find themselves relying on products with lower barriers to entry, but higher long-term fees.

An individual's experience with formal financial channels and credit can also affect their financial health. One important reason to study gender differences in these financial outcomes is that those who struggle to access affordable, safe credit products or have less familiarity with simple financial instruments (such as deposit accounts and credit cards) may have difficulty using more complex financial products (such as investment products and housing credit) and accumulating wealth in the future.

Women Were More Likely Than Men to Carry Credit Card Debt, and at Higher Levels, in 2020

Most adults have at least one credit card, yet there are distinct gaps for credit ownership.3 Those who were White, non-Hispanic, and have higher family incomes reported higher rates of credit card ownership. However, among respondents with a credit card, women were significantly more likely to have credit card debt during 2020 than men (table 1).

Those who were White, non-Hispanic, and have higher family incomes reported higher rates of credit card ownership. However, among respondents with a credit card, women were significantly more likely to have credit card debt during 2020 than men.

Credit card debt differs by race and ethnicity in addition to gender, with non-White adults more likely to carry unpaid credit card debt. Additionally, the gender gaps within race and ethnicity cohorts are also unequal. The difference in the share of non-White men and women credit card owners who have debt (6.4 percentage points) is nearly one and half times the magnitude of difference among White, non-Hispanic men and women (4.3 percentage points). The larger gender gap among non-White individuals suggests potential compounding effects, and future research is warranted.

Credit card debt is also strongly correlated with whether respondents have children.4 Respondents with children, and especially women, are more likely to have outstanding unpaid credit card debt. More than 4 in 10 women living with at least one child carried unpaid debt, well above the level seen among fathers or adults of either gender without children.

Table 1. Credit card ownership and payment behavior

Percent

Characteristic Share of adults with
a credit card
Share of adults with unpaid credit
card debt
Share of adults with more credit card debt than 12 months prior
Overall
Men 82.3 32.9 7.7
Women 83.7 38.0 11.0
Race/ethnicity
Non-White men 75.8 35.6 9.3
Non-White women 77.1 41.9 12.4
White, non-Hispanic men 86.0 31.3 6.8
White, non-Hispanic women 87.8 35.6 10.2
Family income
Men, less than $50,000 63.8 28.0 8.7
Women, less than $50,000 70.5 36.2 12.7
Men, $50,000–$99,999 94.2 40.5 10.0
Women, $50,000–$99,999 93.0 45.1 11.9
Men, $100,000 or more 97.6 33.5 4.4
Women, $100,000 or more 98.1 34.9 7.5
Family status
Men, no children 81.7 31.7 6.5
Women, no children 85.3 36.7 9.3
Men, children 84.2 36.4 11.4
Women, children 79.9 41.3 15.8

Note: Among all adults. Adults with children live with at least one child under the age of 18.

Source: Author's computations using 2020 SHED data.

Overall, slightly less than one-tenth of SHED respondents had more outstanding credit card debt in 2020 than one year earlier.5 Adults with children were more likely to experience increased credit card debt levels during the prior year. In particular, women with children were more likely to have accumulated more credit card debt during 2020 compared to both men with children in the home and women without kids (table 1).

Despite reports that some individuals lowered their credit card debt by applying stimulus payments or saving more during periods of COVID closures, these levels remained comparable to values from the 2019 survey, with female credit card holders being more likely to have increased credit card debt compared to the year before. The difference between the share of men and women with increased debt levels was also identical in the 2020 and 2019 SHED results.6

Women Were More Likely to be Denied Credit Than Men and Were
Less Confident about Application Approval

While there is no significant gender difference in credit card prevalence, men and women differed in their application success rates in 2020. Thirty-seven percent of adults applied for credit last year.7 Among those who applied for credit over the 12 months prior to the survey, women were denied, or approved for amounts that were less than requested, more than men (32 percent and 29 percent, respectively).

Among those who applied for credit over the 12 months prior to the survey, women were denied, or approved for amounts that were less than requested, more than men (32 percent and 29 percent, respectively).

While income and labor market shocks from the pandemic may have affected individuals' credit profiles, there is no evidence from the SHED that more adults were denied or approved for less than requested in 2020 compared to 2019.8

It is clear from the 2020 SHED data that, of those who applied for credit, women living with at least one child under the age of 18 were more likely to be denied credit than their child-free counterparts (33 percent and 21 percent, respectively).

They were also more likely to report other limitations to borrowing. The incidence of denial or limitations on credit also differs by gender, even among those with children: slightly more than 4 out of 10 women living with at least one child under age 18 were denied or approved for less, compared to slightly more than 3 out of 10 men (table 2).

Table 2. Percent who received a credit denial or approved for less than requested
Characteristic Denied Denied or approved for
less than applied for
Overall
Men 22.4 28.9
Women 25.0 32.3
Race/ethnicity
Non-White men 31.3 40.6
Non-White women 33.4 42.2
White, non-Hispanic men 17.2 22.1
White, non-Hispanic women 19.9 26.4
Family income
Men, less than $50,000 40.7 50.6
Women, less than $50,000 37.5 46.1
Men, $50,000–$99,999 18.6 25.6
Women, $50,000–$99,999 21.9 30.2
Men, $100,000 or more 8.1 11.1
Women, $100,000 or more 10.0 14.6
Family status
Men, no children 21.8 28.0
Women, no children 20.8 28.0
Men, children 24.0 30.6
Women, children 32.9 40.5

Note: Among adults who applied for some form of credit in the prior 12 months.

Source: Author's computations using 2020 SHED data.

Low confidence, or fear of being denied, can also serve as a barrier to credit to those who need it. That is, individuals can voluntarily lower the amount of credit extended to them by delaying or simply not applying for credit. This occurs when someone has a faulty assumption about one's own creditworthiness and does not apply for desired credit when they would have been approved. In this case, a lack of confidence on the part of the individual, not underwriting from a lending company, results in less credit. The decision to not request additional credit could also be the result of a previous denial or bad experience using financial services. While one might expect more individuals to hold off on submitting credit applications in 2020 due to elevated rates of
furloughs and high unemployment, these figures are nearly unchanged from the previous
survey period.9

After accounting for race and ethnicity, family income, and parental status, women were more likely to put off applying for at least one credit application.

In 2020, women were more likely than men to put off applying for at least one credit application (figure 1). The percentage point difference separating men and women varied by income, race and ethnicity, and parental status. However, after accounting for race and ethnicity, family income, and parental status, women were more likely to put off applying for at least one credit application. This is illustrated in figure 1 by the point estimates for women (maroon markers) being further to the right (greater) than the estimates for men (blue markers).

More Data Is Needed to Uncover the Origins of the Gender Disparities in
Credit Outcomes

The data used in this analysis do not allow us to look into the reasons for credit outcomes, including unfavorable ones such as denials, among survey participants. While we see markedly different results among women and people of color, further information is needed to better understand the nuance behind credit decisions. Additionally, lending decisions for credit products are increasingly automated. This is especially true for credit cards—the most common credit instrument—where a majority of applications are submitted online, and the applicant instantaneously receives a response.

Figure 1. Percent of respondents who put off applying for at least one credit application
Figure 1. Percent of respondents who put off applying for at least one credit application

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Note: Key identifies circles in order from left to right. Put off applying for credit includes adults who put off applying for additional credit as well as those who did not apply for any credit during the previous year but desired it.

Source: Author's computations using 2020 SHED data.

The automated nature of these decisions means they are theoretically less susceptible to human bias, which can lead to uneven outcomes. Algorithms making underwriting decisions can be prone to a systemic bias that favors certain groups over others—such as those with a propensity to work part time versus full time or by specific occupation type, which may correlate with gender and race and ethnicity. More complete data on credit decisions, including demographic information for the borrower, is needed to better understand the issues.

Results from the 2020 SHED show that men and women had different credit payment behavior and credit perceptions, as well as experienced different outcomes when seeking credit during 2020. Importantly, the magnitude of the gender gaps was largely unchanged from a year prior, before the pandemic and subsequent economic downturn. Even if men and women's experiences with credit products did not change drastically as a result of the COVID-19 pandemic, any disparities that existed beforehand could still affect how individuals fared throughout the downturn. While much attention has been given to gender differences in labor force outcomes throughout the pandemic, it is important to be aware of other types of financial strain, such as increasing credit card debt levels and postponing seeking additional credit due to fear of being denied.

This analysis also illustrates the need to dig deeper than aggregate statistics. Monitoring not just overall gender disparities in credit behavior and outcomes but also how these gaps change with respect to race and ethnicity, parental status, and family income establishes a more nuanced view of credit access and wellbeing. This fuller understanding of credit outcomes may assist policymakers in reducing financial and credit inequities through policies designed for populations who face barriers to credit access.

Footnotes

 1. Since 2013, the Survey of Household Economics and Decisionmaking (SHED) has been conducted annually during the fourth quarter via an online panel. During 2020, two supplemental surveys were fielded in April and July. The survey measures the economic well-being of U.S. households and includes a range of topics such as credit access, education, economic fragility, retirement, and savings. The SHED questionnaire and anonymized data for all years, including 2020 and 2019, are available through the Federal Reserve Board's website at https://www.federalreserve.gov/consumerscommunities/shed.htmReturn to text

 2. The SHED questionnaire asks respondents to identify as White, Non-Hispanic; Black, Non-Hispanic; Asian, Non-Hispanic; Other, Non-Hispanic; Two or More Races, Non-Hispanic; or Hispanic. In order to preserve statistical power throughout the analysis, we compare White, Non-Hispanic and Non-White individuals for all breakdowns by race and ethnicity. Return to text

 3. Eighty-three percent of adults owned at least one credit card in 2020. Board of Governors of the Federal Reserve System, Economic Well-Being of Households in 2020 (Washington: Board of Governors, May 2021), https://www.federalreserve.gov/publications/files/2020-report-economic-well-being-us-households-202105.pdfReturn to text

 4. Parental status is defined by adults living with at least one child under the age of 18. Return to text

 5. The exact wording from the survey instrument (for this question as well as others) asks "do you [and/or your spouse (or partner)] have more credit card debt…." so it is not possible to differentiate between the survey respondent and their spouse/partner (for those who have a spouse or partner). As a robustness check, we ran all results by adults who are single and those living with a spouse/partner. The results hold, and gender differences remain among sets of adults. For this reason, aggregate gender results will be reported throughout the analysis. Return to text

 6. Results from the 2019 SHED data show that overall, among adults who own at least one credit card, 11 percent had more credit card debt than 12 months prior. This includes 9.3 percent of men who own at least one credit card and 12.6 percent of women. Return to text

 7. Split nearly identically with 37 percent of women reporting applying for any type of credit, compared to 36 percent of men (2020 Survey of Household Economics and Decisionmaking). Return to text

 8. Results from the 2019 SHED show that 32 percent of women reported a denial or being approved for less credit than applied for, compared to 30 percent of men. Board of Governors of the Federal Reserve System, preface to Report on the Economic Well-Being of Households in 2019 (Washington: Board of Governors, May 2020), https://www.federalreserve.gov/publications/2020-economic-well-being-of-us-households-in-2019-preface.htmReturn to text

 9. Eleven percent of men and 13 percent of women put off submitting at least one credit application (2019 Survey of Household Economics and Decisionmaking). Return to text

The Pandemic's Effects on Women-Owned Small Firms: Findings from the Small Business Credit Survey

by Ann Marie Wiersch and Lucas Misera, Federal Reserve Bank of Cleveland Community Development Department

Analysis of small business survey data show that businesses owned by women—and, in particular, by Black women—faced more financial and operational challenges during the pandemic and were less likely to receive financing than men-owned businesses.

The COVID-19 pandemic had wide-reaching effects on small businesses, including outsized effects on businesses owned by women. The Federal Reserve's Small Business Credit Survey (SBCS) finds that women-owned firms faced more financial and operational challenges than men-owned firms, and they were less likely to receive financing. Black women-owned firms, in particular, reported worse outcomes on applications for both traditional financing and emergency funding.

This article explores data from the 2020 SBCS, an annual survey of U.S. small firms conducted through a collaboration of the 12 Federal Reserve Banks. Data from the SBCS provide policymakers and service providers with important insights on small business conditions and the experiences of business owners.

Over 15,000 firms were surveyed in September and October of 2020 about their business performance, financing outcomes, and the actions they took to weather the pandemic.1 This analysis focuses on SBCS findings for employer businesses—that is, those with at least one employee other than the business owner(s). Unless otherwise stated, the statistics referenced reflect findings for those employer firms.2 That said, most of the differences between women- and men-owned employer firms were also observed between women- and men-owned nonemployer firms—those small businesses with no employees other than the business owner(s). Statistics on firm size, age, and industry are drawn from the Census Bureau data used to weight the Small Business Credit Survey responses.

Women-Owned Firms Are Newer, Smaller, and More Often Led by People of Color

To understand the challenges faced by women-owned firms, it is useful to understand how they are different from men-owned firms. Women-owned employer firms are more likely to be newer firms: 41 percent have been in business five or fewer years, compared to 29 percent of men-owned firms. They are also smaller, as measured by annual revenues and number of employees.3

These differences are important because historical data on small business performance and credit access show that smaller, newer firms are less profitable, have more financial challenges, and are less likely to be approved for financing.4 In addition, women-owned firms are more concentrated in the health-care and education industry (23 percent of women-owned employers versus 9 percent of men-owned firms), which was harder-hit during the pandemic than other sectors of the economy.5

Furthermore, women-owned firms are more likely to be led by people of color—22 percent of women-owned employer firms, compared to 18 percent of men-owned firms. As described in the Small Business Credit Survey 2021 Report on Firms Owned by People of Color, these firms—which have always faced greater challenges, especially with respect to financing outcomes—saw these challenges exacerbated during the pandemic.6 It is also notable that women-owned firms are more likely to be nonemployer firms. Indeed, women-owned firms account for 21 percent of employers but 42 percent of nonemployers.7

Women-Owned Firms Faced Outsized Financial and Operational Challenges

Women-owned firms faced more operational challenges than men-owned firms throughout the pandemic. As shown in figure 1, women-owned firms were more likely to report they had temporarily closed or reduced their operations as a result of the pandemic's effects. And, they more commonly reported declines in revenues during the prior 12 months.

Figure 1. Effects of the pandemic on business operations and performance among employer firms
Figure 1. Effects of the pandemic on business operations and performance among employer firms

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Note: Key identifies bars in order from top to bottom.

Source: Authors' calculations using data from the 2020 Small Business Credit Survey.

Furthermore, women-owned firms were more likely to have faced financial challenges in the prior 12 months, as 86 percent did, compared to 78 percent of men-owned firms. Specifically, they more often reported challenges paying operating expenses, including wages (71 percent versus 61 percent of men-owned firms) and paying rent (51 percent versus 39 percent).

Relatedly, women-owned employers were more likely to report declines in the number of workers they employed (49 percent compared to 45 percent of men-owned employer firms). However, of firms that took action to reduce employment, women-owned firms were more likely to have attempted to rehire their workers (73 percent of women-owned firms versus 68 percent of men-owned firms).

Women-owned firms faced more operational challenges than men-owned firms throughout the pandemic. For example, women-owned firms were more likely to report they had temporarily closed or reduced their operations as a result of the pandemic's effects.

Looking ahead, small businesses widely anticipated ongoing challenges in the next 12 months as a result of the pandemic. Women-owned firms were more likely than men-owned firms to expect challenges related to the owners' or employees' personal or family obligations (26 percent versus 21 percent). Concerns associated with personal or family obligations were more pronounced for younger women business owners (those age 45 and under), as one-third of these firms expected such challenges.

Taken together, as women-owned firms faced significant operational and financial challenges—many of which were driven by the pandemic—their owners were less optimistic about the state of their business. At the time of the survey, women-owned firms were more likely than men-owned firms to be in fair or poor financial condition (65 percent compared to 55 percent).

Women-Owned Firms Were Less Likely to Receive the Funding They Sought

In response to widespread shutdowns and operational challenges, the federal government introduced new financial assistance programs and expanded others to help small businesses weather the pandemic. The largest of these programs was the Paycheck Protection Program (PPP) administered by the Small Business Administration (SBA), which provided nearly $800 billion in forgivable loans to small businesses across the U.S.8

The federal government also dedicated funding toward the SBA's Economic Injury Disaster Loan (EIDL) program, which provides low-interest loans and grants to small businesses experiencing a temporary loss in revenues. Other financial support programs for small businesses included aid from state and local governments as well as grants from nonprofits and foundations.

Given the weaker financial condition of women-owned firms, in aggregate, access to emergency assistance funding was important to keeping these firms afloat during the pandemic.

Women-owned firms were more likely than men-owned firms to seek emergency assistance funding, as 93 percent of firms with women owners applied for some form of emergency support, compared to 90 percent of firms led by men. While men-owned firms were slightly more likely to have sought PPP loans, women-owned firms applied more often than men-owned firms for EIDL assistance.9 Fifty-one percent of women-owned firms and 46 percent of men-owned firms applied for loans through the EIDL program. Women-led businesses also were more likely to have sought EIDL grants (41 percent, compared to 32 percent of men-owned firms).

Of firms that did apply for PPP, women-owned firms were somewhat less likely to receive all or most of the funding they sought. Specifically, 84 percent of women-owned firms received more than half the amount they sought, while the same was true for 89 percent of men-owned firms.

Even among firms with strong credit scores, women-owned applicant firms were more likely to be denied financing than men-owned businesses (27 percent, compared to 20 percent).

While pandemic-related emergency funding programs were essential to the continued operation of small businesses, firms also continued to utilize traditional financing like business loans, lines of credit, and credit cards. Women- and men-owned firms were equally likely to have sought traditional financing in the prior 12 months, but women-owned firms were less likely to have received all of the financing they sought (33 percent, compared to 37 percent of men-owned applicant firms). Even among firms with strong credit scores, women-owned applicant firms were more likely to be denied financing than men-owned businesses (27 percent, compared to 20 percent).

Women-owned applicant firms also sought smaller amounts of financing; 61 percent of women-owned firms applied for $100,000 or less, compared to 43 percent of men-owned applicant firms. However, the propensity of women-owned firms to submit small-dollar applications, which are generally less likely to be approved, does not explain the entirety of the gap in access to financing between men- and women-owned firms. Even when comparing small-dollar applicant firms owned by women to those owned by men, women-owned firms were less likely to report successful outcomes, as 66 percent of women-owned firms were approved for at least some financing, relative to 74 percent of men-owned firms.

Women-owned nonapplicant firms—those that had not applied for new financing in the prior 12 months—were more debt averse than their men-owned counterparts (29 percent and 24 percent, respectively) and less likely to report they had sufficient financing (48 percent of women-owned nonapplicant firms, compared to 53 percent of men-owned firms).

Businesses Owned by Black Women Reported the Steepest Challenges

While these SBCS data highlight the greater challenges faced by women-owned firms relative to men-owned firms, a closer look at the population of women-owned firms reveals important differences by race and ethnicity. Black women-owned firms, in particular, consistently reported worse outcomes than other segments of small businesses. Overall, the survey reveals that Hispanic and Asian women-owned firms faced more challenges than their respective men-owned counterparts and than firms owned by White women.10

Comparing Black- and White-owned firms across gender, businesses owned by Black women faced more financial challenges than other firms. Ninety-four percent reported at least one financial challenge in the prior 12 months, compared to 92 percent of Black men-owned firms, 85 percent of White women-owned firms, and 77 percent of White men-owned firms.

Comparing Black- and White-owned firms across gender, businesses owned by Black women faced more financial challenges than other firms. Ninety-four percent reported at least one financial challenge in the prior 12 months, compared to 92 percent of Black men-owned firms, 85 percent of White women-owned firms, and 77 percent of White men-owned firms. Furthermore, as shown in figure 2, Black women-owned firms were the most likely to report that their business was in fair or poor financial condition.

Figure 2. Share of firms in fair or poor financial condition
Figure 2. Share of firms in fair or poor financial condition

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Source: Authors' calculations using data from the 2020 Small Business Credit Survey.

Faced with greater financial challenges, Black women-owned firms also fared worse than other firms in their attempts to secure funding to sustain their businesses. As shown in table 1, these firms were least likely to have received all of the PPP funding they sought. Furthermore, those Black women-owned firms that applied for traditional credit products were far less likely to receive financing than White men- and White women-owned firms who sought credit. While 57 percent of firms owned by White men received most or all of the financing they sought, the same is true for just 17 percent of firms owned by Black women.

Table 1. Outcomes on applications for emergency funding and traditional financing, by gender and race of business owner

Percent

Outcome White-owned Black-owned
Men Women Men Women
PPP share received (all) 80 76 45 38
PPP share received (most or all) 91 86 55 52
Financing received (all) 41 34 13 12
Financing received (most or all) 57 49 24 17

Source: Authors' calculations using data from the 2020 Small Business Credit Survey.

Policy Implications of the Credit Gap

Through the pandemic, women-owned firms faced more challenges than their men-owned counterparts and were less successful obtaining funding to deal with those challenges. To some extent, the differences in experiences and outcomes for women-owned firms are driven by factors other than the gender of the firm's owner—including firm size, firm age, industry, and especially race and ethnicity of the owner. For example, women-owned firms are more concentrated than men-owned firms in the health care and education, a sector of the economy that was acutely affected by government mandates and declines in demand stemming from the pandemic.11 The concentration in health care and education is even higher among businesses owned by Black women, likely contributing to the difficulties those firms have endured since the onset of the pandemic.

As the effects of the pandemic wane, small business revenues will likely recover as business conditions improve. However, gaps between women- and men-owned firms in credit availability may make for a rockier return to normal.

These disparities in financing outcomes precede the pandemic: data from the 2016 SBCS, for example, found that 36 percent of women-owned firms received all of the financing they sought, compared to 44 percent of men-owned businesses.12 Longstanding gaps in credit access may be a consideration for programs intended to promote broad access to financial support.

Footnotes

 1. The 2020 SBCS gathered 9,693 responses from employer firms and 4,531 responses from nonemployer firms. Among employer firm responses, 4,865 were from men-owned firms, 3,795 were from women-owned firms, and 1,033 were from equally owned firms. Equally owned firms are excluded from this analysis. Return to text

 2. The variances cited in this article are statistically different at a significance level of 0.05. Return to text

 3. Women-owned employer firms are more likely to have $100,000 or less in annual revenues (25 percent versus 12 percent for men-owned firms), and they are more likely to have four or fewer employees (61 percent versus 52 percent for men-owned firms). See the Small Business Credit Survey 2021 Report on Employer Firms at https://www.fedsmallbusiness.org/survey/2021/report-on-employer-firms for details on the weighting methodology. Return to text

 4. For example, see the 2017 Small Business Credit Survey: Report on Employer Firms https://www.fedsmallbusiness.org/survey/2018/report-on-employer-firmsReturn to text

 5. Lei Ding and Alvaro Sánchez, "What Small Businesses Will Be Impacted by COVID-19?" Federal Reserve Bank of Philadelphia research brief, April 2020, www.philadelphiafed.org/community-development/housing-and-neighborhoods/what-small-businesses-will-be-impacted-by-covid-19Return to text

 6. Small Business Credit Survey: 2021 Report on Firms Owned by People of Color, https://www.fedsmallbusiness.org/survey/2021/2021-report-on-firms-owned-by-people-of-colorReturn to text

 7. Compared to women-owned employers, women-owned nonemployers are also more concentrated in certain sectors, including professional services/real estate (e.g., real estate agents), nonmanufacturing goods production (e.g., arts and crafts makers), and business support/consumer services (e.g., personal care services). Return to text

 8. For more information about the Paycheck Protection Program, see https://www.sba.gov/funding-programs/loans/covid-19-relief-options/paycheck-protection-program/ppp-dataReturn to text

 9. Of firms that did not seek PPP loans, women-owned firms were less likely to say it was because their firm did not need the funding (10 percent, compared to 22 percent of men-owned firms). Return to text

 10. For example, firms owned by Asian women experienced steeper revenue declines year-over-year relative to other firms. Firms owned by Hispanic women reported poorer outcomes on financing applications relative to White-owned firms, though they were narrowly more likely to receive financing compared to Black women-owned firms. Return to text

 11. Ding and Sánchez, "What Small Businesses Will Be Impacted?"   Return to text

 12. 2016 Small Business Credit Survey: Report on Women Owned Firms, https://www.fedsmallbusiness.org/survey/2017/report-on-women-owned-firmsReturn to text

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Last Update: November 12, 2021