Applying for and receiving unemployment insurance benefits during the coronavirus pandemic

The coronavirus disease 2019 (COVID-19) pandemic has greatly affected the U.S. labor market starting in March 2020. More than twice as many jobs were lost in the initial months of the pandemic than during the Great Recession (2007–09). In addition, only a third of those jobs were recovered in the subsequent 2 months.¹ The large number of job losses at the beginning of the pandemic caused the employment–population ratio to plummet from 61.1 percent in February 2020 to 51.3 percent in April 2020. By December 2020, it had partially recovered to 57.4 percent.²

In the midst of the initial wave of job losses, the federal government made several major changes to the unemployment insurance (UI) program.³ The Families First Coronavirus Response Act (FFCRA), enacted on March 18, 2020, allowed states to relax several conditions for applicants to receive UI benefits.⁴ These conditions include the requirement that applicants be actively seeking work and the requirement that applicants left work because of an employer action, such as a layoff.⁵ The Coronavirus Aid, Relief, and Economic Security (CARES) Act, enacted on March 27, 2020, created three federally funded temporary UI programs:⁶

1. The Pandemic Unemployment Assistance (PUA) program expanded eligibility for UI benefits to self-employed workers, independent contractors, and part-time workers.
2. The Pandemic Emergency Unemployment Compensation program extended benefits by 13 weeks for those persons who exhaust their regular UI benefits.
3. The Federal Pandemic Unemployment Compensation (FPUC) program provided a $600-a-week supplement to UI benefits through July 31, 2020.

After the FPUC program expired, on August 8, 2020, the President issued an executive order that allowed states to supplement UI benefits by $300 a week, funded by federal disaster relief aid (Lost Wages Assistance), for up to 6 weeks of unemployment.

Because of the expansion of UI programs and substantial job loss, the number of initial claims rose tremendously during the pandemic. When a person applies for UI benefits, an initial claim is the first claim filed by the person in determining eligibility for benefits. A state UI office reviews each initial claim and either accepts or rejects it. If the claim is accepted, benefits are paid. As shown in chart 1, initial claims for benefits under the regular UI program, which were around 200,000 a week before the pandemic, shot up to about 6 million a week in late March and early April 2020. After that time, initial claims fell as the pandemic progressed but remained above 2 million a week through mid-May and above 1 million a week through early August. By the end of December, initial claims were around 800,000 a week.

Estimates of the number of people who applied for UI benefits and the number of people who received benefits during the pandemic are useful for measuring the impact of the UI program. UI benefits are a key part of the federal government’s policy response to the pandemic.⁷ With individual-level UI estimates, analysts can precisely compare the extent of UI payments with the extent of stimulus payments and other less targeted government interventions that directly support individuals.

In this article, we use the Household Pulse Survey (HPS) to estimate the number of people (and share of the adult population) who applied for UI benefits and who received benefits during the first 9 months of the pandemic (March through December 2020). We also estimate a measure of the success rate of UI applicants in obtaining benefits: the share of applicants who received benefits. To show which groups were more or less likely to receive UI benefits during the pandemic, we examine differences by demographic group, education, and prepandemic household income. These estimates can be compared with the pattern of job losses during the pandemic, as documented in other research (as discussed later in this article).

States are important as program administrators in the federal–state UI system and as geographical areas capturing the spatial dimension of labor markets and the spread of the coronavirus. Given states’ importance, we estimate for each state the percentage of the population who applied for UI benefits, the percentage of the population who received benefits, and the success rate of UI applicants. We relate these state-level estimates to UI recipiency before the pandemic, job loss during the pandemic, the differential spread of the coronavirus across states, and the differential use of COVID-19 restrictions by state governments. The relationship between these state-level estimates and UI recipiency before the pandemic is intended to partially capture differences that existed in state UI programs before the pandemic.

Our analysis investigates some empirical consequences of the expanded eligibility for UI benefits to self-employed workers, low-wage workers, and other workers typically not covered in the regular UI program. The UI outcomes (application rate, receipt rate, and success rate) for workers with less education and lower prepandemic household income show the extent to which the UI program helped low-wage workers during the pandemic. Evaluating UI outcomes for the self-employed shows, in part, how successful the expansion of the UI program to self-employed individuals during the pandemic was. We also analyze UI outcomes for parents of school-age children who faced varying levels of disruption to their school routines, which is relevant for the expansion of the range of “good cause” exceptions for leaving work to include caring for a family member.

Finally, we go beyond measuring the receipt of UI benefits to examine whether receiving benefits improved the well-being of individuals and their households. This question is critically important during the pandemic, given the large number of people who received benefits and the expanded benefit amounts (because of the federal supplement). The survey data provide measures of well-being in a variety of domains, including household finances, food security, and mental health. To gauge the effect of receiving benefits on well-being, we compare those who received benefits with those who applied for benefits but did not receive them. Taken together, our analysis provides information relevant to evaluating how successful the targeted UI program was in mitigating the effects of the pandemic on individuals who were directly affected by it.

Household Pulse Survey

The Employment and Training Administration (ETA) publishes various reports that summarize UI administrative data at the state level.⁸ It is not possible to use the data in these reports to gauge the number of people who applied for UI benefits and the number of people who received benefits across all UI programs during the pandemic.⁹ The main reason we cannot use the ETA data is that over time, a person can apply for and receive benefits from more than one UI program. Thus, simply summing the claims for each program would result in an unknown degree of double counting.¹⁰ The number of individuals included in more than one UI program may be substantial during the pandemic because many states have required individuals to exhaust or be denied regular state UI benefits to be eligible for benefits under the pandemic-related programs. Double counting of individuals during the pandemic can also occur within programs, particularly when one is trying to determine the number of people who have applied for benefits.¹¹

Given these issues with the administrative data, we use the HPS to construct individual-level estimates. The HPS is an experimental rapid-response survey designed to measure how the coronavirus pandemic is affecting U.S. households from a social and economic perspective. The U.S. Census Bureau conducts the survey in partnership with other federal agencies, including the U.S. Bureau of Labor Statistics (BLS). The HPS is a 20-minute online survey conducted in 66 sample areas throughout the nation. The sample frame is based on the Census Bureau’s Master Address File records and existing email and telephone records. The HPS started on April 23, 2020, and phase 1 lasted until July 21, 2020. The data for this article were collected during the period August 19–December 21, 2020, which covers all of phase 2 (August 19–October 26) and the first part of phase 3 (which started October 28).

Phase 2 was made up of five data collection periods (each was about 2 weeks), with a separate sample for each period. In each period, the sample size was about 1.03 million housing units. Households chosen for the sample were contacted by email and text message and asked to complete the survey online. Across periods, the number of respondents varied from 88,716 to 109,051, with corresponding response rates between 8.1 percent and 10.3 percent (see appendix table 1). Over the first four data collection periods of phase 3, the sample size was similar to that for phase 2, but the response rates were lower (5.3 percent to 6.7 percent). The sampling methods and questionnaire were the same in phase 2 and phase 3. Although the HPS data are timely and relevant, we caution that the data are labeled as experimental and do not necessarily meet the high standards of other Census Bureau and BLS data products. For example, how representative HPS respondents are of the entire U.S. population has not been fully explored.¹²

In households sampled for the HPS, one adult responds to the survey. These adults report individual experiences only for themselves, not other members of their household. Throughout our analysis, we use the person weights created by the Census Bureau.¹³ The person weights were designed to produce biweekly estimates for the total number of persons age 18 and older living within housing units. The Census Bureau created these weights by adjusting the household-level-sampling base weights for various factors to account for nonresponse, adults per household, and coverage. In addition, the person weights are controlled to independent population controls by various demographics within each state. The demographic characteristics involved in this process are age, gender, race, Hispanic origin, and educational attainment.¹⁴

The HPS has several advantages for studying UI. It includes questions on whether individuals applied for UI benefits during the pandemic and, if so, whether they received benefits. The responses to these questions can be used to produce unduplicated estimates of the number of people who have applied for benefits and received benefits across all the UI programs in place during the pandemic. The HPS also collects information on demographics, educational attainment, total household income (from 2019), current work status, and the reason for not working. Various measures of household and individual well-being can be constructed from the HPS questions covering several domains, including household finances, food security, and mental health.

The information on who applied for UI benefits and who received benefits comes from two questions that BLS designed and tested.¹⁵ The first question asks about applying for benefits: “Since March 13, 2020, have you applied for Unemployment Insurance (UI) benefits?” For those who answer “yes” to this question, a follow-up question asks, “Since March 13, 2020, did you receive Unemployment Insurance (UI) benefits?” March 13 is used to indicate the beginning of the pandemic in the United States. On this date, the President declared a National Emergency concerning COVID-19.¹⁶ A third question asks about the receipt of benefits at the household level: “Including yourself, how many people in your household received Unemployment Insurance (UI) benefits since March 13, 2020?” We do not use responses to the third question in this article.¹⁷ Because the questions refer to UI generically, we interpret the survey responses to encompass both the regular UI program and the pandemic UI programs.

To measure employment at the time of the survey, the HPS asks, “In the last 7 days, did you do ANY work for either pay or profit?” For those who answer “yes,” a followup question is asked to determine whether the respondent is employed by government, a private company, or a nonprofit organization; self-employed; or working in a family business. For those who are not working, the HPS asks, “What is your main reason for not working for pay or profit?” The respondent is given a list of 13 potential reasons, and we classify the responses into three categories: COVID-19-related reasons that are employer initiated, COVID-19-related reasons that are not employer initiated, and non-COVID-19-related reasons (see appendix table 2).

Note that the reference period (the last 7 days) for the employment questions is different from the reference period (between March 13 and the survey date) for the UI questions. The UI questions identify those people who have received benefits at some point during the pandemic but were not necessarily receiving benefits at the time of the survey. Similarly, those who were working at the time of the survey may have received benefits during the pandemic, although not necessarily while they were working. All respondents were asked the UI questions, regardless of whether they were currently working. The employment information reported in the HPS reflects the respondent’s situation at the time of the survey but does not necessarily reflect the respondent’s situation at other points during the pandemic. In addition, the HPS does not provide any information about the respondent’s employment situation before the pandemic.

Aggregate estimates

We use the HPS responses together with the person weights to estimate the number of people who applied for UI benefits and the number of people who received benefits during the first 9 months of the pandemic (March 13 to December 21, 2020). Our estimates are based on the combined sample of 775,788 HPS respondents from August 19 to December 21, 2020. Our estimates refer to the population age 18 and older.

We estimate that 52 million people applied for UI benefits from March 13 to December 21, or 21.0 percent of the U.S. adult population of 249 million. We also estimate that 40 million people received UI benefits during the pandemic, or 16.0 percent of the adult population.¹⁸ By way of comparison, 84 percent of the population age 18 and older received stimulus payments (i.e., Economic Impact Payments) that were authorized as part of the CARES Act.¹⁹ This comparison demonstrates the extent to which UI benefits were more targeted toward those experiencing economic hardship than were stimulus payments.

We estimate that 77.2 percent of those who applied for UI benefits since March 13 had received benefits by the survey date (August 19 to December 21, 2020). This measure, which we refer to as the success rate, reflects both individual eligibility and the capability of state UI offices to process claims.²⁰ Given that some people applied for UI benefits before the survey date and started receiving benefits after the survey date, our estimated success rate is an underestimate of the share of applicants who ultimately received benefits. However, given the long reference period (back to March 13, 2020) and the time pattern of initial claims (the spike in initial claims was early in the pandemic), the extent of the understatement is likely not large.

Estimates by demographic characteristics, education, and household income

Our estimates by demographic characteristics are shown in table 1. In terms of the share of the population who applied for UI benefits or the share of the population who received benefits, no gender differences essentially exist: about 21 percent of men and women applied for UI benefits and about 16 percent received benefits. The lack of gender differences in these estimates makes the pandemic recession stand out from prior U.S. recessions. In prior recessions, the share of women who applied for (or received) UI benefits was lower than the corresponding share of men.²¹ Therefore, our HPS estimates reflect a larger role for employment declines among women in the pandemic recession (especially in the initial wave of job losses) than in prior U.S. recessions.²² The success rate is the same for men and women. Regardless of gender, those with children present in the household were more likely to receive UI benefits than were those without children present in the household.

Among racial groups, Blacks had the highest rates of applying for UI benefits (28.5 percent) and receiving benefits (20.4 percent). However, the success rate was lower among Blacks (72.8 percent) than among Asians (82.9 percent) and Whites (78.2 percent). Hispanics were more likely to have applied for and received UI benefits than were non-Hispanics. The success rate was somewhat lower among Hispanics (75.6 percent) than among non-Hispanics (77.6 percent). The higher rates of applying for UI benefits among Blacks and Hispanics are consistent with Black and Hispanic workers being disproportionately affected by job losses, layoffs, and disruptions to small businesses during the pandemic.²³

Estimates by educational attainment and household income are shown in table 2. Among individuals age 25 and older, those with bachelor’s degree or higher were less likely to have applied for and received UI benefits than were those with a high school education or some college. The success rate generally increased with the level of education. However, the rate was lowest among those with less than a high school education (68.8 percent) and highest among those with a bachelor’s degree (80.8 percent). People with lower household incomes in 2019 were more likely to have applied for and received UI benefits (see chart 2), which suggests that they had fewer nonwage income sources to draw on.²⁴ For example, among those with incomes of less than $25,000, 28.1 percent applied for benefits and 19.6 percent received benefits. By comparison, among those with incomes of $200,000 or more, 9.2 percent applied for benefits and 7.4 percent received benefits. As it did with education, the success rate generally increased with household income.

The higher rates of applying for UI benefits and receiving benefits among those with less education and lower income are consistent with employment declines during the pandemic that were greater among low-wage workers.²⁵ This pattern may also reflect the higher replacement rates that arose from the $600-a-week federal supplement (available from April through July 2020), which was independent of a worker’s prior wage and therefore had the largest effect on replacement rates for low-wage workers.²⁶ Most workers, especially low-wage workers, could receive more money from the enhanced UI benefits than they received in wages while working.²⁷

Workers with less education and lower income had lower success rates (see chart 3). This finding could reflect that low-wage workers were less likely to be eligible for regular UI (in part, because of not meeting the minimum earnings requirement), although the PUA program expanded UI eligibility for individuals lacking sufficient work history and individuals working part-time hours.²⁸ The pattern of success rates by race may partly reflect the higher prevalence of low-wage work among Blacks compared with Whites and Asians. In 2019, according to data from the Current Population Survey, median weekly earnings for full-time workers were $735 for Blacks, $945 for Whites, and $1,174 for Asians.²⁹

Estimates by state and relationship to state-level factors

The UI system is a federal–state partnership that is funded by federal and state taxes on employers and administered by states. States set eligibility, duration, and benefit levels within federal guidelines. Because of state differences within the UI system, we examine variation by state in the share of the population who applied for UI benefits, the share of the population who received benefits, and the success rate of UI applicants. In addition to their role in administering the UI program, states show the geographic dimension to labor markets, COVID-19 spread, and COVID-19 restrictions imposed by governments. During the pandemic, states and local areas have imposed a variety of restrictions on economic activity to slow the spread of COVID-19, including closing nonessential businesses, closing schools and daycare facilities, requiring residents to stay at home, canceling public events, and restricting the size of gatherings.

The estimated share of the population who applied for UI benefits varies substantially across states, ranging from 11.4 percent to 30.3 percent (see appendix table 3). Four states have more than 25 percent of their population who applied (Nevada, Michigan, Hawaii, and New York). Three states have less than 13 percent who applied (Utah, South Dakota, and Wyoming). The estimated share of a state’s population who received benefits follows a similar pattern, ranging from 7.6 percent to 25.5 percent. States with a larger share of their population who applied for benefits also have a larger share of their population who received benefits, and the relationship is very tight (see chart 4).

What accounts for this variation across states? To understand the variation, we examine how the HPS state-level estimates relate to the extent of UI coverage in a state before the pandemic, state-specific job loss during the pandemic, and the differential spread of the coronavirus across states. Each of these facets is discussed separately in the later paragraphs.

As a measure of the extent of UI coverage in a state before the pandemic, we use the UI recipiency rate in 2019. This measure, which is the share of unemployed workers who received UI benefits, varies widely across states: 7 states had recipiency rates of greater than 40 percent in 2019, whereas 17 states had recipiency rates of less than 20 percent.³⁰ Prior research indicates that variation in state recipiency rates reflects state laws (regarding who is covered by UI and for how long) and administrative practices, although labor market variables and other factors are also important.³¹ States with higher recipiency rates before the pandemic had both a larger share of the population who applied for UI benefits and a larger share of the population who received benefits (see chart 5a).³² This relationship suggests that despite the temporary expansions of UI coverage during the pandemic, preexisting aspects of a state’s UI system still mattered for the number of people who received UI benefits during the pandemic.

View Chart Data

States with a higher average unemployment rate between March and December 2020 had both a larger share of the population who applied for UI benefits and a larger share of the population who received benefits (see chart 5b). This relationship provides support for the HPS-based estimates, but it is not surprising because many people who are classified as unemployed receive UI benefits. However, receiving UI benefits and being unemployed are not the same.³³ For instance, some people who are unemployed do not qualify for UI benefits (e.g., new entrants to the labor force and those who do not have sufficient work experience), some people who are eligible for UI benefits do not apply for benefits, and some people who are receiving UI benefits are not considered unemployed (e.g., if they are not searching for work).³⁴ In addition, some people are classified as employed but still eligible for UI benefits (e.g., those whose hours were reduced by their employers or who were participating in a work-sharing program).

View Chart Data

The share of the population who applied for UI benefits and the share of the population who received benefits are also positively correlated with the cumulative number of COVID-19 deaths per 100,000 population (see chart 5c). This effect presumably operates through the disruptions to the labor market caused by the coronavirus and by countermeasures taken by states and local areas to combat the virus’s spread. Another COVID-19 measure that focuses on states’ countermeasures is the Stringency Index compiled by the Oxford COVID-19 Government Response Tracker.³⁵ This index measures the strictness of states’ closure and containment policies that primarily restrict people’s behavior. This measure is also positively correlated with the shares of the population who applied for or received UI benefits during the pandemic, and the magnitude of the correlation is stronger than that for the COVID-19 death rate (see chart 5d).

View Chart Data

View Chart Data

The success rate of UI applicants varies from 63.9 percent (Arkansas) to 87.1 percent (Rhode Island). States with higher recipiency rates before the pandemic have a higher success rate (see chart 5a). Beyond that, one concern is that states with a larger extent of job loss during the pandemic may have experienced “crowding effects” in their UI systems—whereby some applicants could not have their applications processed promptly—leading to declines in the success rate. If this crowding hypothesis were true, the success rate would be negatively correlated with demand for UI benefits. However, the scatter plots of the drivers of demand for UI benefits show the opposite pattern: if anything, the success rate is positively correlated with the unemployment rate, COVID-19 deaths per capita, and the COVID-19 Stringency Index (see charts 5b–5d). As a complementary way of looking at the data, the success rate is positively correlated with the share of the population who applied for UI benefits (see chart 6). Although this evidence does not support the crowding hypothesis, our approach is not overly sensitive to crowding issues early in the pandemic because the HPS data we use were collected from August 19 to December 21, 2020, and the questions on applying for and receiving UI benefits have a reference period going back to March 13, 2020.

Given the possibility of multiple factors driving the variation in HPS state-level estimates, we now turn to a multivariate approach that allows us to explore the effects of a given factor while controlling for one or more other factors. In the results reported in table 3, we estimate linear regressions with a given HPS state-level estimate as the dependent variable and different combinations of the factors as independent variables. Across regressions, a consistent finding is that the recipiency rate before the pandemic is positively correlated with the share of the population who applied for UI benefits, the share of the population who received benefits, and the success rate of UI applicants. When we hold the prepandemic recipiency rate constant, the unemployment rate is positively correlated with the share of the population who applied for UI benefits and the share of the population who received benefits but is not correlated with the success rate. These results suggest that, among states with a similar recipiency rate, when the unemployment rate increases, the increased number of people applying for UI benefits can be accommodated without reducing the success rate.

Instead of looking at the effect of the unemployment rate, we look at the effects of the COVID-19 measures. Because the COVID-19 measures capture what might be causing the higher unemployment rates, we do not include the unemployment rate in the same model with the COVID-19 measures. When we consider both COVID-19 measures together and control for the recipiency rate, each COVID-19 measure is positively correlated with the share of the population who applied for UI benefits, the share of the population who received benefits, and the success rate of UI applicants. However, the magnitude of the effect is more than twice as large for the Stringency Index than the death rate.³⁶ This finding suggests that although both COVID-19 measures explain variation in the state-level HPS estimates, the Stringency Index contributes more than the death rate.

Estimates by employment income, work status, and children’s school routines

A measure of whether an HPS respondent lives in a household where a member’s labor earnings were negatively affected during the pandemic comes from the question, “Have you, or has anyone in your household experienced a loss of employment income since March 13, 2020?” In the HPS data for August 19 to December 21, 2020, 46.5 percent of individuals responded “yes.” Those who responded “yes” did not necessarily lose their job during the pandemic or experience a reduction in hours at work. Respondents could have answered “yes” for several reasons, including that someone else in their household lost employment. However, the set of respondents who said “yes” likely includes people who experienced either job loss or a reduction in work hours during the pandemic. Among adults in households that lost employment income, 41.2 percent applied for UI benefits and 31.8 percent received benefits (see table 4).

We examine current work status using the question on whether the respondent was doing any work for pay or profit in the last 7 days. For this analysis, the “not working” category includes those who are not working for a variety of reasons, including stay-at-home parents and those who are retired. To focus the analysis on individuals for which usual employment rates are relatively high, we restrict the sample for this part of our analysis to prime-working-age (25–54) people. For those not working, we classify the main reasons for not working into three categories: COVID-19-related reasons that are employer initiated, COVID-19-related reasons that are not employer initiated, and non-COVID-19-related reasons (see appendix table 2 for a fuller explanation of this categorization).

Among prime-working-age persons who received UI benefits at some point during the pandemic, 51.3 percent were at work in the last 7 days, 30.9 percent were not working in the last 7 days because of a COVID-19-related reason initiated by their employer, and 4.4 percent were not working because of a COVID-19-related reason not associated with their employer (see table 5). By comparison, among all prime-working-age individuals regardless of whether UI benefits were received, 71.4 percent were at work. Thus, although more than half of UI recipients had either returned to work or never lost their jobs (e.g., had their hours reduced), the extent of job loss among UI recipients (on the basis of employment status at the time they were surveyed) was still substantial. Among prime-working-age individuals not working in the last 7 days because of a COVID-19-related reason initiated by the employer, 61.3 percent had received UI benefits. By contrast, only 26.6 percent of individuals not working because of other COVID-19-related reasons had received benefits.

In the rest of this section, we look at people of all ages. Among those who were working in the last 7 days, 18.3 percent had applied for UI benefits and 14.0 percent had received benefits since March 13, 2020 (see table 4). There is wide variation by class of worker in the share of workers who had received UI benefits. This share is 6.5 percent among workers in government, 8.5 percent among workers in nonprofit organizations, 12.5 percent among those employed in a family business, 15.2 percent among the self-employed, and 16.5 percent among wage and salary workers in the private sector. One factor in this pattern is the success rate among UI applicants, which is higher among wage and salary workers in the private sector than among workers in the other classes.

The variation by class of worker in the share of workers who received UI benefits may also be related to differences by class of worker in the extent of employment disruption during the pandemic. Employment estimates from the Current Population Survey are broadly consistent with this explanation: employment losses during the first 9 months of the pandemic were greater for wage and salary workers in the private sector than for workers in government and the self-employed. From February to April 2020, employment fell 17.9 percent for wage and salary workers in the private sector but only 8.8 percent for workers in government and 7.8 percent for the self-employed. These differences persisted to some extent during the recovery: by December 2020, employment was down 5.9 percent (compared with February 2020) for wage and salary workers in the private sector but only 3.2 percent for workers in government and 4.2 percent for the self-employed.³⁷ Consistent with the pattern of employment losses, the share of wage and salary workers in the private sector who applied for UI benefits was more than double the share of workers in government who applied. For the self-employed, the share of people who applied for UI benefits was higher than is suggested by the employment losses. This finding might reflect that many of the self-employed continued to work during the pandemic but experienced reduced income from employment.

Our analysis of UI application and receipt by class of worker provides a perspective on the effect of UI expansions during the pandemic. The PUA program, created under the CARES Act, expanded eligibility for UI during the pandemic to self-employed workers, independent contractors, and part-time workers.³⁸ Among those who were working in the last 7 days and were self-employed, 21.6 percent had applied for UI benefits and 15.2 percent had received benefits (see table 4). These rates are similar to those for wage and salary workers in the private sector who worked in the last 7 days. However, the success rate was much lower for self-employed workers (72.2 percent) than for private wage and salary workers (80.5 percent). This finding suggests that the PUA program expanded UI coverage for self-employed workers during the pandemic, but a gap in coverage remained, compared with private wage and salary workers.

With another policy change that broadened eligibility for UI benefits during the pandemic, the FFCRA allowed states the flexibility to expand the range of “good cause” exceptions for leaving work to include caring for a child, parent, or spouse/partner.³⁹ This change is relevant for parents of school-age children who contended with the shift to remote learning during the pandemic. With children at home instead of in school buildings during the day, some parents had to stop working or reduce their hours of work to supervise and support their children with remote learning and care.⁴⁰ From the perspective of the UI system, it is of interest whether the changes to school routines affected parents’ use of UI benefits during the pandemic. For households with any children enrolled in a public or private school in kindergarten through 12th grade, the HPS asked, “How has the coronavirus pandemic affected how the children in this household received education for the 2020–2021 school year?”⁴¹

The responses to this question show that parents whose children experienced more disruptions to their school routine were more likely to have applied for UI benefits and more likely to have received benefits during the pandemic (see table 6). Among parents of students whose classes normally taught in person at the school were canceled, 21.5 percent received benefits. Among parents of students whose classes normally taught in person at the school were moved to a distance-learning format (using either online resources or article materials), 19.2 percent received benefits. Among parents of students who did not experience any change in their school routine (that is, their classes were taught in person at the school), 14.1 percent received benefits.

We also look at the current work status of parents of children enrolled in school (see table 7). Parents whose children experienced more disruptions to their school routine were less likely to be at work in the last 7 days. Among parents of students whose classes normally taught in person at the school were canceled, 63.0 percent were at work. By contrast, among parents of students who did not experience any change in their school routine, 72.6 percent were at work. Furthermore, among parents who were not working, those whose children experienced more disruptions to their school routine were more likely to choose “I am/was caring for children not in school or daycare” as their main reason for not working.

Several possible reasons exist for the correlations among disruption to school routines, parental employment, and parents receiving UI benefits. One reason is that changes to school routines caused parents to leave their jobs and apply for UI benefits. Another is that a third factor (the coronavirus or responses to it at the local level) caused both school disruptions and parental job losses. Our analysis does not allow us to distinguish between these two explanations.

Effect of receiving UI benefits on well-being

What is the impact of UI benefits on the well-being of recipients and their households? One of the fundamental goals of the UI system is to provide a source of income to workers during periods of unemployment. Research using prepandemic data shows that UI benefits support unemployed workers by replacing lost income, increasing spending, and increasing food consumption.⁴² Furthermore, more generous UI benefits increase health insurance coverage and use, and reduce mortgage defaults.⁴³ Before the pandemic, some adults were so financially vulnerable that they would have struggled to pay for an emergency expense as small as $400 or cover expenses if they lost their job.⁴⁴ During the pandemic, the effects of receiving UI benefits on well-being might be stronger because of the federal supplement of $600 a week. During the period when the supplement was available, Peter Ganong and colleagues found that spending of the unemployed after job loss rose substantially above prepandemic levels. Spending of unemployed households also rose compared with the spending of employed households, which is opposite of the normal pattern.⁴⁵

We use the HPS data to construct six measures of the well-being for individuals and households. Each measure is an indicator for whether the individual or household experienced distress in a particular domain (see appendix table 4 for details):

1. In the last 7 days, the household had difficulty paying for usual household expenses.
2. In the last 7 days, the household had experienced food insecurity.
3. The household is not current on mortgage or rent payments.
4. The household is not confident in being able to pay its next mortgage or rent payment.
5. Over the last 7 days, the individual experienced symptoms of anxiety.
6. Over the last 7 days, the individual experienced symptoms of depression.

The anxiety and depression measures are designed to match concepts in surveys sponsored by the National Center for Health Statistics.⁴⁶

Prior research that used the HPS and other data indicates that in the population overall, levels of distress during the pandemic were much higher than before the pandemic. Using data from the COVID Impact Survey and comparable data from the National Health Interview Survey (NHIS), Marianne P. Bitler, Hilary W. Hoynes, and Diane Whitmore Schanzenbach estimated that food insecurity increased sharply from 11 percent in 2018 to 23 percent in April 2020.⁴⁷ HPS data for May 14–19, 2020, indicate that 28.2 percent of adults had symptoms of anxiety disorder and 24.4 percent had symptoms of depressive disorder.⁴⁸ These estimates are 3 to 4 times larger than comparable estimates for January–June 2019 from the NHIS, which indicated 8.2 percent of adults had symptoms of anxiety disorder and 6.6 percent had symptoms of depressive disorder.

To gauge the effect of receiving UI benefits on well-being, we compare those who had received benefits (at some point during the pandemic) with those who applied for benefits but did not receive them.⁴⁹ In our HPS data for August 19 to December 21, 2020, the well-being measures show substantially less distress among UI recipients than among unsuccessful applicants (see table 8 and chart 7). For instance, 18.9 percent of UI recipients were experiencing food insecurity, compared with 29.1 percent of unsuccessful applicants. In addition, 45.2 percent of UI recipients were experiencing anxiety symptoms, compared with 53.2 percent of unsuccessful applicants. The well-being measures for UI applicants (both successful and unsuccessful) are substantially higher (indicating more distress) than for the general population, consistent with the higher incidence of job loss among UI applicants.⁵⁰

The difference in well-being between UI recipients and unsuccessful applicants may not necessarily be the causal effect of receiving UI benefits on well-being. Prepandemic differences could exist between those who received UI benefits and unsuccessful applicants. For instance, differences in prepandemic earnings patterns may be associated with eligibility for UI during the pandemic. As a result, those who received UI benefits may have had higher incomes and higher savings before the pandemic than did unsuccessful applicants. As such, they may have been in a better position to weather losing their job, apart from the UI benefits they received. We find that UI recipients had higher household incomes in 2019 and more education than unsuccessful applicants (see table 8).

To assess the causal effect of receiving UI benefits on well-being, we estimate linear regressions with controls for variables that might differ between UI recipients and unsuccessful applicants. In each regression, the dependent variable is one of the well-being measures and the key independent variable is an indicator for receiving UI benefits. The sample is limited to those who had applied for benefits, so the estimated coefficient on the indicator for having received benefits distinguishes between UI recipients and unsuccessful applicants. Without any controls, the estimated coefficients in column 1 of table 9 match the differences between groups in table 8. As controls for household income (in 2019), education, and demographics (gender, race, and ethnicity) are added, the estimated coefficients on the indicator fall in magnitude—indicating that some of the differences in well-being between the groups in table 8 are due to prepandemic differences rather than receipt of UI benefits.⁵¹

Controlling for household income, education, and demographics reduces the differences between groups by 15 percent to 30 percent, depending on the well-being measure. However, when we control for prepandemic differences in these factors, the differences in well-being between UI recipients and unsuccessful applicants are still large. This finding suggests that receiving UI benefits during the pandemic substantially improved the well-being (reduced the distress) of individuals and households. Using our preferred estimates in table 9 (column 4), one can see that receiving UI benefits reduces the probability of having difficulty with household expenses by 7.8 percentage points and reduces the probability of experiencing food insecurity by 7.5 percentage points. For the housing measures, receiving UI benefits reduces the probability of an applicant not being current on mortgage or rent by 5.6 percentage points and reduces the probability of not being confident on paying the upcoming mortgage or rent payment by 5.8 percentage points. For the mental health measures, receiving UI benefits reduces the probability of an applicant having symptoms of anxiety by 7.2 percentage points and reduces the probability of having symptoms of depression by 7.5 percentage points. These effects are large in relation to the mean among unsuccessful applicants (see table 9).

Conclusion

In this article, we explored who applied for UI benefits and who received benefits during the pandemic, whether state factors and worker characteristics could explain differences in the success rate of UI applicants, and the effect of receiving benefits on applicants’ well-being. We estimate that, through the first 9 months of the pandemic (March through December 2020) in the United States, 21.0 percent of adults applied for UI benefits and 16.0 percent of adults received UI benefits. Among adults in households that lost employment income during the pandemic, 41.2 percent applied for UI benefits and 31.8 percent received benefits. By way of comparison, 84 percent of adults received stimulus payments that were authorized as part of the CARES Act. This comparison shows the extent to which UI benefits are more targeted than stimulus payments.

We found that demographic groups disproportionately affected by job loss during the pandemic, as shown by other sources, were more likely to receive UI benefits. These groups include Blacks, Hispanics, and women. Although similar to the share of men who received UI benefits, the share of women who received benefits was higher than in prior recessions, when women were less likely than men to receive benefits. We also found that states with higher unemployment rates during the pandemic had a larger share of their population who received UI benefits.

Overall, among those who applied for UI benefits, 77.2 percent received benefits. Although workers with less education and lower income were more likely to apply for UI benefits, the success rate of UI applicants was lower among those with less education and lower income. This finding could reflect that low-wage workers were less likely to be eligible for regular UI (because of minimum earnings requirements). Success rates were similar for women and men but varied by race. Among racial groups, Blacks had the lowest success rate and Asians the highest, with a difference of 10 percentage points. This pattern could be due, in part, to Blacks being more likely to work in low-wage jobs and Asians being less likely.

In addition to illustrating differences in economic hardship across demographic groups, we found that success rates are also relevant for understanding the extent to which the expansions of the UI program during the pandemic were successful. The PUA program expanded UI eligibility during the pandemic to cover self-employed workers, low-wage workers, and other workers typically not covered in the regular UI program. Despite the expanded eligibility for individuals lacking sufficient work history, workers with less education and lower income had lower success rates than workers with more education and higher income. A similar pattern emerged for self-employed workers: the success rate for self-employed workers was lower than for private wage and salary workers. These patterns suggest the expansions of UI eligibility under the PUA program, while beneficial to workers not normally covered by the regular UI program, did not eliminate gaps in coverage.

The persistence of differences in UI coverage also emerged from our cross-state analysis. Across states, the success rate is positively correlated with the prepandemic UI recipiency rate, even when we controlled for pandemic factors such as the unemployment rate and COVID-19 measures. Moreover, the prepandemic recipiency rate is positively correlated with the share of the population who applied for UI benefits and the share of the population who received benefits. Taken together, these findings imply that differences in UI recipiency across states before the pandemic contributed to differences in UI recipiency across states during the pandemic.

Despite the persistence of state differences in UI recipiency from before the pandemic, we found that the UI program provided benefits to individuals who were directly affected by the pandemic in the labor market. In addition to providing income support, the UI program improved the well-being of individuals and households. Compared with individuals who applied for UI benefits but did not receive them, individuals who received UI benefits had greater well-being in a variety of domains, including household finances, food security, and mental health.

ACKNOWLEDGMENT: We are grateful to Elizabeth Handwerker and Mark Loewenstein for their helpful comments. We have also benefited from the comments of seminar participants at the Department of Labor’s Chief Evaluation Office.

Appendix: Additional documentation of the Household Pulse Survey and results regarding unemployment insurance applicants and recipients during the coronavirus pandemic