5. Inclusion, material conditions and COVID-19

Lower-paid and less-educated workers were more likely to stop working during the pandemic, and those who remained in employment were less able to telework

Lower-paid and less-educated workers were most exposed to the pandemic’s immediate impacts on the labour market. These workers are less likely to be in roles that are amenable to teleworking (Box 5.1), making them both more adversely impacted by pandemic-related business closures and more likely to be in roles involving higher social contact and infection risk (OECD, 2020[1]). In 22 European OECD countries, low-wage earners make up a much higher share of those who lost their jobs in 2020 (Figure 5.1). It is therefore not surprising that, across the EU 27, it is estimated that the average loss of employment income between 2019 and 2020 was four times higher for workers in the bottom income quintile compared to those in the top income quintile (-10.2% vs. -2.5%) (Eurostat, 2021[2]).1 Evidence from a separate survey conducted in 25 OECD countries in September-October 2020 also shows that people from low-income households were more likely than those in medium- or high-income households to report a job loss or a job-related disruption (OECD, n.d.[3]).2

On average in 34 OECD countries, workers with tertiary education experienced a smaller rise in unemployment in 2020 relative to their less-educated peers. Nevertheless, education gaps related to the change in unemployment between 2019 and 2020 did vary across OECD countries, with some experiencing a greater widening of the education gap than others (Figure 5.2). Evidence from the United States indicates that the magnitude of this education gap also varies by sector (Box 5.2).

Workers with lower levels of education and people facing financial difficulties were most worried about losing their jobs between April-June 2020 and February-March 2021. Data for 22 European OECD countries indicate that 13% of those with a secondary education or less reported that it was “very likely” or “likely” that they would lose their jobs within the next three months, compared to 9% of those with a tertiary or above education level (Figure 5.5, Panel A). Similarly, 29% of people who are having difficulty making ends meet felt this way, relative to 7% of those who reported that they could easily make ends meet (Figure 5.5, Panel B).

Younger workers have been further disadvantaged by the pandemic, experiencing higher job and earnings losses than older workers

Young people aged 15 to 24 experienced a higher risk of job loss than workers aged 25 or over during the pandemic. Indeed, young people are more likely to hold less secure and lower skill jobs and are highly represented in sectors more severely exposed to government lockdowns (OECD, 2021[11]). In nearly all OECD countries, young workers experienced higher rises in unemployment compared to older workers between 2019 and 2020 (Figure 5.7, Panel A). In Q2 2020, the OECD average unemployment rate for workers aged 15-24 was 18.5%, more than twice as high as that of workers aged 25 or over (7.4%) (Figure 5.7, Panel B).

The COVID-19 crisis has reversed the decade-long improvement in the number of young people not in education, employment or training (NEET). At the end of 2019, prior to the COVID-19 outbreak, just over 1 in every 10 young people aged 15 to 29 were NEET (OECD, 2021[11]). By the second quarter of 2020, however, the NEET rate increased by 2.9 percentage points year-on-year across the OECD, with a high share of the increase concentrated in inactivity (Figure 5.8). Despite having decreased in the third quarter of 2020, the share of inactive NEET youth remained elevated in the majority of countries in Q4 2020 (OECD, 2021[11]). Periods of inactivity have proved to be very damaging for young people’s career prospects, and the high levels of NEET present during the pandemic are likely to result in longer-term scarring effects (see (OECD, 2021[11]) and Chapter 9 for more information on youth NEET during the pandemic).

Young people were also more exposed to greater falls in earnings and higher rates of job insecurity during 2020. It is estimated that, in the EU 27, younger workers aged 16-34 suffered higher losses in earnings compared to workers aged 35-65 between 2019 and 2020 – respectively 5.8% and 4.5% (Figure 5.9). The younger age group experienced higher losses in employment income in 20 EU Member States, with declines ranging from 15% to 2% compared with 2019. Nevertheless, income support by governments is estimated to have reduced the losses for both age groups (Eurostat, 2021[2]). In addition, data from 22 European OECD countries collected between April-June 2020 and February-March 2021 suggest that job insecurity was also higher among younger workers on average. Specifically, 19% of young people (aged 18 to 24) felt they were likely to lose their job in the following three months, compared to 11% of people aged 25 or over (Figure 5.10).

COVID-19 also risks compounding existing labour market inequalities between young people. In the 2007-2008 financial crisis, young people with educational attainment below upper secondary level suffered the most from unemployment and inactivity, which persisted during the recovery. Indeed, in 2017, young people with no more than lower-secondary education were three times more likely to be not in employment, education or training (NEET) compared to those with a university degree (OECD, 2020[13]).

Young women were particularly affected by job and income losses during COVID-19. On average across the OECD, the youth unemployment rate for women aged 15 to 24 increased by 3.9 percentage points between 2019 and 2020, while the unemployment rate for young men grew by 2.9 percentage points (Figure 5.11). In addition, among EU 27 countries, young women (aged 16 to 24) are estimated to have experienced higher labour income losses between 2019 and 2020 compared to young men (12.7% versus 11.3%) (Eurostat, 2021[2]).

The pandemic has affected both men and women negatively in terms of employment, but women, especially mothers, face a number of additional vulnerabilities and challenges

A number of factors have made women more vulnerable to job and income loss during the COVID-19 crisis. First, women tend to be less firmly attached to the labour force than men; they also tend to work fewer hours and to have lower wages (OECD, 2021[11]). Second, women are over-represented in the services sector, including retail, catering and hospitality, which were hit the hardest by government lockdown measures. In 2019, the share of employed women in the services sector across 26 OECD countries was 84.1% on average, 22.8 percentage points higher than that of men (61.3%).

Nevertheless, women make up a large share of workers in the sectors defined as essential, including health care and education. As such, women have been facing exceptional work demands and are more likely to be exposed to COVID-19 while working (OECD, 2021[11]). In addition, the pandemic’s impact on employment has been partly shaped by whether people’s jobs enable them to telework, which tends to be possible in both male and female-dominated sectors (e.g. education) (see Box 5.5 for information on teleworking experiences for different population groups) (OECD, 2021[11]).

Therefore, on average across the OECD, women and men experienced similar rises in unemployment in 2020 (respectively by 1.8 and 1.6 percentage points) (Figure 5.12, Panel A). Indeed, while in Q2 2020, right after the onset of the crisis, average unemployment rose slightly more for women than for men, the average gender unemployment gap went back to pre-pandemic levels by Q4 2020 and Q1 2021 (Figure 5.12, Panel B). Patterns vary across countries, however (see Box 5.3 for evidence from Chile and (OECD, 2021[11]) for more information) (Refer to Chapter 7 for information on how the pandemic impacted unpaid work for women and men). Eurostat estimates meanwhile indicate that, at the EU 27 level, there were no substantial differences in labour income losses between women and men (Eurostat, 2021[2]).

In many OECD countries, reduced work hours cushioned the impact of school closures on employment, for both women and men. Indeed, the closure of schools and childcare facilities threatened the labour market attachment of women in particular, as they are more likely than men to move to part-time employment or to leave the labour market due to caregiving responsibilities. In a number of countries, job retention schemes, short-time work schemes or specific care leave allowed women to retain their job while working fewer hours (OECD, 2021[11]). As a result, the gendered impact of the pandemic on unemployment varied across countries. For instance, the impact on women and men was similar in most European countries – where large use of job retention schemes was made – in contrast with the United States and Canada, which mainly relied on temporary layoffs (Figure 5.12, Panel A) (see also Chapter 2).

Government policies mitigated the impact on employment, but parents were still more likely to withdraw from the labour force, especially mothers with young children. In the EU 27, absences from work were higher among women than men between 1 January and the end of June 2020, and they were most frequent during school and childcare centre closure (ILO and UN Women, 2020[14]). Evidence from Chile, Costa Rica and Mexico reveals that partnered women with children experienced sharper pandemic-related drops in labour force participation rates (LFPR) between Q1 and Q2 2020 than partnered men with children – and that these falls were most common among women with children under six-years-old (ILO and UN Women, 2020[14]). In the United States, the participation rates for parents fell more than for non-parents during the first year of the pandemic, and mothers’ participation rates fell more than for fathers. The LFPR of mothers overall was about 3.5 percentage points lower in March 2021 than in January 2020. By contrast, fathers’ LFPR was down only by 1 percentage point. In particular, in March 2021, the LFPR of single mothers and mothers with children under 12 was lower than that for mothers with teenage children (Figure 5.13). Moreover, in the United States in October-November 2020, about 14% of unmarried mothers and mothers whose youngest child was under age 6 reported that they left their job due to child-care responsibilities in 2020, compared with 8% of mothers with children aged 6 to 12 (Bauer, 2021[15]).

On average in 14 OECD countries, the gender wage gap narrowed from 13.7% to 10.4% in 2020 (Figure 5.14). One possible explanation for this is compositional: women are over-represented in low-paid occupations in the sectors hardest hit by the pandemic, and therefore were more exposed to job loss in 2020. As a result of the missing lowest-paid women, the gender wage gap narrowed (Institute for Women’s Policy Research, 2021[16]).

Immigrants and people belonging to racial/ethnic minorities were often the first to lose their jobs at the beginning of the pandemic

Although it is still too early to gauge the full labour market effects of the pandemic – especially in European OECD countries, where job retention schemes have cushioned the immediate impact of the lockdowns – initial evidence shows a disproportionate toll throughout 2020 on migrants in all countries where data are currently available (OECD, 2020[19]).3 Overall, employment trajectories for native- and foreign-born individuals followed similar trends for 23 OECD countries – they dropped sharply in the second quarter of 2020 and slightly recovered in the third. Unlike that of native-borns, however, employment among migrant workers declined again in the last quarter of 2020 (Figure 5.16, Panel A and B). In the first quarter of 2021, the employment rate decreased more for foreign-born than for native-born individuals (Figure 5.16, Panel A). Some care is needed in interpreting the latest developments in the OECD employment rate, as methodological changes to the EU Labour Force Survey blur the comparison between the fourth quarter of 2020 and the first quarter of 2021 for EU countries.4 Migrants were also more affected by unemployment, particularly in the first half of 2020 (OECD, 2020[19]).

Migrants face a number of vulnerabilities in the labour market. They are over-represented among employees with temporary contracts and low wages, in cyclical sectors and in service sectors (such as hospitality, security and cleaning) which were particularly affected by the pandemic (Statistics Canada, 2020[20]; OECD, 2020[19]). In the EU, migrants account for about 12% of the population, but for more than a quarter of employment in the hospitality industry (OECD, 2020[21]). Migrants have fewer networks to rely upon in times of economic downturn, and there is some evidence that discrimination is more pronounced in times of slack labour markets (OECD, 2020[19]).

In addition, the different employment, language training and income support programmes that newcomers rely upon have been suspended or interrupted in the wake of the pandemic in some OECD countries, although they moved to remote delivery modes in some places such as Canada. This is likely to negatively affect migrant employment outcomes in the long term, especially for parents who also faced competing family and childcare priorities during COVID-19. Refugees have been particularly impacted in this regard during the pandemic: for instance, in Germany, 39% of refugee respondents stated that their language skills had deteriorated in 2020 (Brücker, 2021[22]). In Australia, temporary migrants were excluded from the JobKeeper and JobSeeker income support packages introduced for the general population in March 2020. A July 2020 survey of over 6 000 temporary visa holders in Australia, including international students, temporary graduate and skill shortage visa holders as well as refugees and asylum seekers, revealed that 70% of those respondents who were working lost their job or most of their hours or shifts; 28% of these respondents were also unable to pay for meals or food for some period since March (Berg and Farbenblum, 2020[23]).

The limited data available also suggest that people belonging to racial and ethnic minorities have faced greater labour market challenges during the pandemic. In the United Kingdom, the unemployment rate of people identifying as ethnic minority5 stood at 8.5% between July and September 2020, 1.4 percentage points higher than in the same period in 2019. Over the same period, the unemployment rate among white people had risen by only 0.9 percentage points, to 4.5% (ONS, n.d.[24]). Indeed, industries such as transport and storage as well as accommodation and food sectors in which ethnic minority workers are over-represented announced the most redundancies over the summer (ONS, 2020[25]; Powell, Francis-Devine and Foley, 2020[26]). Ethnic minority workers were also less likely to have been placed on job retention schemes, and more likely to have permanently lost their jobs, relative to white British people in April, while their average household earnings fell by slightly more than for white workers between February and April (8.4% compared to 8%) (Benzeval et al., 2020[27]; Hu, 2020[28]). In the United States, while by April 2021 unemployment rates had fallen from their April 2020 heights for all racial/ethnic groups, gaps between white and Black as well as Hispanic/Latino communities markedly widened compared to end 2019 (doubling for the former and tripling for the latter group) (Figure 5.17) (see Box 5.4 for information on the pandemic’s impact on racial/ethnic minority-owned SMEs). In Canada, experimental estimates from the Labour Force Survey suggest that from January 2020 to January 2021, the unemployment rate increased by 5.3 percentage points among Black Canadians, compared to 3.7 percentage points among non-visible minority6 Canadians (excluding Indigenous people). In the three months ending in January 2021, the unemployment rate among Black Canadians (13.1%) was about 70% higher than that among non-visible minority Canadians (7.7%) (Statistics Canada, 2021[29]).

Women and young people belonging to racial/ethnic communities in the United States were particularly hard hit by the pandemic, experiencing exceptionally high levels of unemployment, and slow employment gains in the recovery. Between February and May, Hispanic/Latino (-21%), Asian (-19%) and Black (-17%) women experienced a greater loss in employment than white women (-13%) (Pew Research Center, 2020[33]). By August 2020, Black women had recovered only 34% of their pre-pandemic jobs, compared to 61% of jobs recovered by white women; by September 2020, the unemployment rates of Black (11.1%) and Hispanic/Latino women (11%) were still more than twice as high as prior to the pandemic (National Women’s Law Center, 2020[34]; Long et al., 2020[35]). The unemployment rate for Hispanic/Latino women, who are more likely than others to be employed in hard-hit leisure and hospitality services, continued to increase from 10.5% in August 2020, even as unemployment rates improved for all other groups of workers aged 20 or over by race/ethnicity and gender (National Women’s Law Center, 2020[34]). Higher exposure to the virus also played a role: in an experimental online survey, a significantly higher share of Hispanic/Latino and Black adults compared to white adults (2.8% and 2.6% vs. 0.3%, respectively) stated in August 2020 that they could not go to work in the previous week because they or someone in their family was sick with COVID-19 (CDC, 2020[36]). Similarly, Black teens aged 16 to 19 on average had the highest unemployment rate (18.9%) among all other age and race/ethnicity groups between July 2020 and July 2021. Hispanic/Latino youth aged 16 to 19 also experienced high unemployment rates (16.8% on average) during the same period (Broady, 2021[37]). Additionally, the unemployment rate for Black teens aged 16 to 19 increased from 9.3% in June 2021 to 17.9% in August 2021, while it decreased for most other racial/ethnic and age groups (Broady, 2021[37]).

Emerging evidence also suggests that the crisis may have longer-lasting consequences among some more disadvantaged groups. In Canada, Indigenous and non-Indigenous people were similarly impacted in terms of unemployment initially, but greater disparities appeared as the pandemic progressed. From the three months ending in February to the three months ending in May 2020, the unemployment rate of Indigenous people living off reserve and non-Indigenous people both increased by a similar amount and stood at 16.6% and 11.7%, respectively. However, employment among Indigenous people has been slower to recover. Year-on-year, the employment rate in June-August 2020 was down 6.9 points among Indigenous people living off reserve and down 5.0 points among non-Indigenous people (Statistics Canada, 2020[38]). During the same months, Indigenous women’s employment rate (for those living off reserve) was further away from pre-pandemic levels than the one for Indigenous men (Statistics Canada, 2020[38]).

Members of LGBTQ+ communities have experienced very large job and income losses since the pandemic began

The demographic composition of LGBTQ+ communities and their prevalence in the sectors most affected by government containment measures – such as hospitality, arts and entertainment – makes them more vulnerable to job and income loss (Wenham, 2020[43]). In Canada, in 2018, LGBTQ2+7 Canadians were generally younger than non-LGBTQ2+ Canadians and were significantly less likely to identify as male (Prokopenko and Kevins, 2020[44]). A majority (53%) of LGBTQI2S8 households in Canada have been affected by lay-offs and reduced hours as a result of the pandemic, compared to 39% of overall Canadian households (Innovative Research Group, 2020[45]).9 In the United States, according to a survey conducted in July-August 2020, 64% of LGBTQ households experienced employment loss compared to 45% of non-LGBTQ households (this included losing their jobs, having their hours or wages reduced, having been furloughed, or taking a mandatory unpaid leave) (Movement Advancement Project, 2020[46]). This share rises to 71% of Hispanic/Latino LGBTQ households and 68% of lower-income LGBTQ households (< USD 30 000 per year) (Movement Advancement Project, 2020[46]). Compounding these difficulties, LGBTQ people report higher rates of employment discrimination generally and may struggle to find new jobs.10

Younger, lower-paid and less-educated employees have lost the highest number of hours worked, mostly due to joblessness rather than reduced working time

Working hours fell for different reasons among people of different ages, incomes and education levels: while some lost their jobs, others remained in employment but worked fewer or zero hours (OECD, 2021[11]). Despite the widespread use of job retention schemes in many OECD countries, joblessness accounted for the majority of the hours lost among less-educated, lower-paid and younger workers (OECD, 2021[11]). For example, in Q2 2020 compared to Q2 2019, average hours worked fell by 8.5% among those with a tertiary education, compared to 24.3% among those holding a lower-secondary diploma or less. In addition to having experienced a higher reduction in hours worked, in Q2 2020, half of the total hours lost among less-educated employees was due to joblessness (Figure 5.18, Panel A). By contrast, for people with a tertiary education, net losses in total hours worked are all attributable to reduced working time, while remaining in employment (Figure 5.18, Panel B). Educational disparities were reinforced across the third and the fourth quarters of 2020, when many high-educated employees returned to work, while joblessness persisted among the low-educated (Figure 5.18).

Similarly, younger employees lost a higher number of working hours compared to their older peers. In Q2 2020, across the OECD, young people aged 15-24 saw their working hours reduced by 26.3%, while the working hours of those aged 25 and over decreased by 15% compared to Q2 2019. The reduction in working hours of employees over 25 was largely driven by reduced working time in employment, while for younger workers, joblessness was the primary cause (Figure 5.19). Even when young workers lost their hours due to reduced working time, this largely consisted of zero-hours employment (Figure 5.19) (OECD, 2021[11]).

People who lost their jobs and those with lower levels of educational attainment have been facing particular financial strain

The year 2020 has been characterised by widespread financial difficulty, especially for the less educated and the unemployed, who tend to have less of a financial safety net. Indeed, those who lost their jobs as a result of the COVID-19 crisis tend to belong to more financially vulnerable groups (e.g. young, low-income, racial/ethnic minorities). Similarly, people with higher levels of education typically have greater household wealth to rely upon in times of need and more financial security. Around 2016, data from 28 OECD countries showed that, on average, median wealth among households headed by someone with a tertiary education was around double that of households headed by someone with a below upper secondary education (OECD, 2020[53]). At the same time, 26% of tertiary-headed households on average were financially insecure (measured as having liquid financial wealth to support their household above the poverty threshold for more than three months), while over 35% of households headed by a person lacking tertiary education faced this risk (OECD, 2020[53]).

Given the lower wealth of the less educated before the COVID-19 crisis, it is not surprising that they report greater financial difficulties. Across 25 OECD countries, 33% of respondents with less than a tertiary education reported that they or someone in their household had experienced some form of financial difficulty, compared to 28% of those with at least a tertiary education in September-October 2020 (see note to Figure 5.20 for the full list of financial difficulties) (Figure 5.20, Panel A). Separate evidence collected in 22 European OECD countries reveals that between April-June 2020 and February-March 2021 the share of people with a secondary or lower education facing difficulty in making ends meet increased at a higher rate compared to that of people with a tertiary education (by 1.6 and 0.7 percentage points respectively) (Figure 5.20, Panel B).

In 25 OECD countries in September-October 2020, those who experienced job loss during the pandemic were more than twice as likely to report financial difficulties. Of people reporting that they or someone else in their household had lost their job, 68% had at least one form of financial difficulty during the pandemic (Figure 5.21, Panel A, see the figure note for the full list of financial difficulties). This compares to an average of 26.3% of people who did not experience job loss. Moreover, almost three-quarters (74%) of those who lost their job during COVID-19 were somewhat or very concerned about their household not being able to pay all expenses and make ends meet in the next year or two, compared to 60% of those who did not report job loss (OECD, 2021[54]).

In 22 European OECD countries, the crisis has widened inequalities in financial difficulties between employment groups. In April-June 2020, on average, 51% of unemployed respondents in 22 European OECD countries reported difficulties in making ends meet, compared to only 17% of the employed. Data from 2018 imply that the percentage of unemployed people who could not make ends meet in the same countries increased by 3.9 percentage points between 2018 and April-June 2020, while the share of employed people in the same condition increased by only 2.2 percentage points. What is more, while the share of employed respondents reporting difficulties to make ends meet decreased to 16% by February-March 2021, that of unemployed respondents in the same condition increased to 57% (Figure 5.21, Panel B).

Young people, parents and those from low-income households have been most likely to run into financial difficulties…

In 25 OECD countries, young people, people with children under 18 and those from low-income households have been more likely to be experiencing some kind of financial difficulty in September-October 2020 (Figure 5.22). This reflects the disproportionate job and income losses experienced by these groups since the beginning of the crisis. In particular, as expected, respondents in low-income households – regardless of employment status – were on average the most likely to report having financial trouble (39%), while high-income households were least likely (25%) (Figure 5.22) (see Box 5.6 for evidence from France).

A survey conducted in the United States revealed that low-income households with children were facing high rates of financial difficulty in April 2020. 76% reported concerns about financial stability, 69% about food availability, 43% about employment and 31% about housing stability. What is more, 94% of the families reported being food insecure, with a 22-percentage point increase since the final months of 2019.11 Food insecurity was higher among Hispanic/Latino respondents (95%), relative to other racial/ethnic groups (Sharma et al., 2020[57]) (see also Box 5.7).12

Findings from the United Kingdom and the United States indicate that people with lower personal incomes face greater difficulty in meeting both unexpected and routine household costs. In the United Kingdom, between March and July 2020, 37.9% of people with total annual income below GBP 10 000 were unable to pay an unexpected expense of GBP 850 compared to 10.5% of people with an annual income of GBP 40 000 or over (ONS, 2020[58]). In the United States, among lower-income adults, 46% say they have had trouble paying their bills since the pandemic started, and 32% say they have been struggling to pay rent/mortgage. By contrast only 5% and 3% of people from the upper-income group have been struggling to pay bills and rent/mortgage respectively. In addition, 35% of lower-income adults say they have received food from a food bank/organisation, compared to only 12% of middle-income and 1% of upper-income adults (Parker, Minkin and Bennett, 2020[59]).13

… and women had more financial difficulties than men

Women were more likely than men to experience difficulties in making ends meet. Across 22 European countries, between April-June 2020 and February-March 2021, the share of women reporting difficulties in making ends meet was 23%, which was 3 percentage points higher than for men (Figure 5.24, Panel A). Between June-July 2020 and February-March 2021, the share of women reporting such difficulties increased by 2 percentage points, while that of men remained stable (Figure 5.24, Panel B).

COVID-19 has also exacerbated the material hardship of racial/ethnic minorities

COVID-19 has exacerbated the material hardship of racial/ethnic minorities in the United Kingdom, Canada, and the United States. In the United Kingdom, prior to the pandemic, households headed by someone of Black African or Other Black ethnicity were significantly less likely to have enough financial assets to cover a drop in employment income than those from most other ethnic groups (ONS, 2020[62]). In April 2020, over a quarter of those from Black, African, Caribbean or Black British ethnic groups reported finding it very or quite difficult to get by financially; this level was significantly higher than those from other ethnic backgrounds, with a 5 percentage point increase compared to 2019 (Figure 5.26, Panel A). All other ethnic groups except for white Irish, also experienced increases in financial insecurity. In May, households that included at least one adult who identifies as ethnic minority also experienced levels of food insecurity at least 50% higher than their white peers (Equality and Human Rights Commission, 2020[63]). Similarly, in May-June 2020, Canadians from visible minority14 groups were more likely than white respondents to report that the pandemic had a strong or moderate impact on their ability to meet their financial obligations or essential needs (Figure 5.26, Panel B). In the United States, while deprivations in May 2021 had fallen from their 2020 heights, compared to white adults, all other racial/ethnic groups, but especially Black, Hispanic/Latino and adults in the Other/Multiracial category, continued to report higher financial insecurity, difficulties paying rent, and food insufficiency (Figure 5.27).

In countries with available data, the pandemic worsened the financial situation for LGBTQ+ communities

LGBTQ+ people are particularly vulnerable to financial difficulty in times of crisis. During the pandemic, LGBTQ+ people have been experiencing considerable employment losses. They also tend to have lower incomes and smaller financial buffers to rely on (Wenham, 2020[43]). In Canada, in 2018, a significantly higher proportion of LGBTQ2+15 Canadians (41%) reported a personal income of less than CAD 20 000 per year compared with their non-LGBTQ2+ counterparts (26%) (Prokopenko and Kevins, 2020[44]). Moreover, in 2018, one-third (33%) of LGBTQ2+ Canadians found it difficult or very difficult to meet their needs in terms of transportation, housing, food, clothing, participation in some social activities and other necessary expenses, compared to 27% among non-LGBTQ2+ Canadians (Prokopenko and Kevins, 2020[44]). According to a survey conducted in the United States in July-August 2020, 66% of LGBTQ households experienced a serious financial problem, compared to 44% of non-LGBTQ households, including: paying utilities like gas or electric, affording medical care, paying credit card bills, loans or other debt. Black and Hispanic/Latino LGBTQ households reported even higher rates of serious financial problems relative to white LGBTQ households: 95%, 75% and 62% respectively. In addition, nearly one in five (19%) LGBTQ households in the United States reported that they did not get enough food to eat in July-August 2020, compared to 6% of non-LGBTQ households (Movement Advancement Project, 2020[46]).

Low-income households, young people and people belonging to racial and ethnic minorities struggle to access affordable and quality housing and are more likely to be homeless

Long-standing inequalities in housing conditions were exacerbated by the pandemic, as they affected how different groups experienced lockdown periods as well as their exposure to the virus. Evidence from the United Kingdom shows that poor housing conditions (living in a cold, damp home), which are disproportionately experienced by vulnerable population groups, are likely to exacerbate or induce respiratory and cardiovascular conditions, which in turn increase the risk of contracting COVID-19 (Centre for Ageing Better, 2020[65]). In addition, nearly one-third of British adults reported physical or mental health problems because of poor housing conditions in June 2020 (National Housing Federation, 2020[66]).16

Across the OECD, many low-income households face gaps in both housing affordability and quality. In 2019, across 32 OECD countries, 27.1% of owners with a mortgage or tenants in the bottom income quintile were overburdened by housing costs – i.e. they spent more than 40% of their disposable income on their mortgage or rent (OECD, n.d.[67]) (OECD, 2021[68]) (refer to Chapter 2 for more information about housing affordability). Low-income households are also more likely to live in poor-quality dwellings. They may not be able to afford regular maintenance or improvements, while at the same time facing barriers to move to better-quality housing. On average, households in the bottom income quintile show a higher share of overcrowding than those in the middle- or top-income quintiles (15.5%, 10.0% and 5.8% respectively) (Figure 5.28) (OECD, n.d.[67]) (OECD, 2021[68]). In addition, within the low-income population, children are more likely to live in overcrowded housing than other age groups (OECD, 2021[68]). In the United Kingdom, over 20% of children from households in the bottom income tertile live in overcrowded conditions, compared to less than 5% of children from households in the top income tertile (Judge and Rahman, 2020[69]).17

Young people have been facing significant difficulties in accessing affordable and quality housing in recent years. In particular, low-income youth face even bigger challenges than their higher-income peers in securing good-quality housing, often because they are not able to rely on their family resources for support (OECD, 2021[68]). For instance, in the United Kingdom, 6% of people aged 16-24 live in a damp home, compared to 2% of people aged 65 or over (Judge and Rahman, 2020[69]). The COVID-19 pandemic is likely to exacerbate these challenges, given the disproportionate impact of the crisis on young people’s jobs and incomes. Indeed, in September-October 2020, in 25 OECD countries 53.4% of young people (aged 18 to 29) reported that they were concerned about not being able to find/maintain adequate housing in the next year or two, compared to 44.1% of the total population (Figure 5.29).

People belonging to ethnic minority groups in the United Kingdom are more likely to live in poor-quality housing. On average, households belonging to ethnic minority groups are larger than white British households, and therefore more likely to live in overcrowded conditions (12% of people from ethnic minority groups live in households of five people or more, compared to 5% of people from white groups) (Haque, Becares and Treloar, 2020[70]).18 In particular, one-quarter of people under age 15 belonging to ethnic minority groups live in overcrowded housing, compared to fewer than 10% of white people (Judge and Rahman, 2020[69]). Furthermore, the proportion of households with no garden is a lot higher among ethnic minorities, as Black people in England are four times as likely as white British people to have no outdoor space at home (37% compared to 10%) (ONS, 2020[71]).19

The pandemic risks pushing more people into homelessness. Indeed, in Europe, the United States, Canada, and New Zealand, homelessness is more common among the vulnerable population groups that were hit the hardest by the crisis. In Europe, a significant number of countries report a strong and sometimes increasing presence of young people between 15 and 29 years old among the homeless population (Baptista and Marlier, 2019[72]). In addition, the European homeless population tends to have lower education levels – mostly primary and secondary – and there is evidence of an association between homelessness, unemployment and very low incomes (Baptista and Marlier, 2019[72]). In the United States, data from 2019 indicate that Black people make up more than 40% of the homeless population. Similarly, American Indians/Alaska Natives, Native Hawaiians and Pacific Islanders and people who identify as two or more racial groups make up a disproportionate share of the homeless population. Hispanic/Latino people constitute a share of the homeless population approximately equal to the general population, while white and Asian people are significantly under-represented (National Alliance to End Homelessness, 2020[73]).20 In Canada, young people aged 13-24 make up about 20% of those experiencing homelessness, and Indigenous people (including First Nations, Métis and Inuit peoples) are over-represented among those experiencing homelessness in urban centers (Gaetz et al., 2013[74]). People from LGBTQ+ communities are also more likely to be homeless or housing insecure. In Canada, 27% of people identifying as LGBTQ2+ reported experiencing some type of homelessness in their lifetime (Prokopenko and Kevins, 2020[44]). In the United States, 25% of LGBTQ people surveyed in July-August 2020 reported that their home has serious heating or cooling problems, mold problems, pest problems, problems with unsafe drinking water, or other serious environmental problems, compared to 10% of non-LGBTQ people (Movement Advancement Project, 2020[46]). Lastly, in New Zealand, data from 2018 indicate that severe housing deprivation particularly affects ethnic minorities and the youth: Māori and Pacific people are respectively four and six times more likely to be severely housing deprived than people of European descent, and people under 25 make up 48.3% of the total housing deprived population (Amore, 2021[75]).21

COVID-19 has also exacerbated the impact of the digital divide in housing, as households without Internet access have greater difficultly in teleworking or participating in distance learning. Across OECD regions, there is a clear urban-rural divide in access to high-speed broadband. On average in 26 OECD countries, 63.6% of households in rural areas have access to high-speed broadband, compared to 87% of all households. Digital divides also exist between income and racial/ethnic groups. In the United Kingdom, only 51% of households earning GBP 6 000-10 000 a year had Internet access at home in 2014, compared to 99% of households with an income of over GBP 40 000 (ONS, 2019[76]). In Canada, 97.9% of households in the top income quartile had Internet access at home in 2012, while 54.9% of households in the bottom quartile had such access (Statistics Canada, 2017[77]). In 2021, in the United States, roughly six-in-ten adults living in households earning USD 100 000 or more a year (63%) reported having home broadband services, a smartphone, a desktop or laptop computer and a tablet, compared to 23% of those living in lower-income households (earning less than USD 30 000 a year) (Figure 5.30, Panel A) (Vogels, 2021[78]). In addition, 80% of white adults reported having a broadband connection at home, while smaller shares of Black and Hispanic/Latino adults said the same – 71% and 65% respectively. White adults in the United States are also more likely to own a computer than Black or Hispanic/Latino adults (80%, 69% and 67% respectively) (Figure 5.30, Panel B) (Atske and Perrin, 2021[79]).22 Access to the Internet and electronic devices can severely impact educational outcomes for vulnerable children. Across the OECD, children under the age of 15 from the bottom economic social and cultural status quartile were least likely to have a computer and access to the Internet at home in 2018 (76.9% versus 97.1% for children in the top quartile).23 Similarly, 76.9% of children whose parents have less than a secondary education and 86.6% of immigrant students had access to a computer and to the Internet at home, compared to 91.6% of children whose parents have at least a tertiary degree and 90.2% of non-immigrant students (OECD, n.d.[80]).


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← 1. Employment income includes wages and self-employment income. Quintiles are based on people’s ranking in terms of their equivalised disposable income.

← 2. The OECD Risks that Matter (RTM) survey is a cross-national survey examining people’s perceptions of the social and economic risks they face and how well they think their government addresses those risks. The survey was conducted for the first time in two waves in 2018. The 2020 survey, conducted in September-October 2020, draws on a representative sample of over 25 000 people aged 18 to 64 in the 25 OECD countries that agreed to participate: Austria, Belgium, Canada, Chile, Denmark, Estonia, Finland, France, Germany, Greece, Ireland, Israel, Italy, Korea, Lithuania, Mexico, the Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Switzerland, Turkey and the United States.

← 3. Consistent with OECD practice (e.g. in the Migration Outlook), this report uses the words “migrants”, “immigrants” and “foreign-born” synonymously. Unless mentioned otherwise, these include all persons born abroad, regardless of their migration category, legal status or nationality. Likewise, unless mentioned otherwise, native-born includes all persons born in the country, regardless of the country of birth of their parents.

← 4. The main changes involved by the new regulation are: persons on parental leave, and who are either receiving job-related income or benefits, or whose parental leave is expected to last three months or less, are counted as employed; persons raising agricultural products for own-consumption are excluded from employment; seasonal workers outside the season are classified as employed if they still regularly perform tasks and duties for the job or business during the off-season; and people with a job or business who were temporarily not at work during the reference week of the survey but with strong attachment to their job are still considered as employed. In the particular context of the COVID-19 crisis and of the measures applied to combat it, national specificities exist in the assessment of the job attachment; not employed people are considered to be searching for a job only if they use an active search method. The new regulation also achieved further harmonisation in the implementation of questions and modernisation of the nation surveys.

← 5. For example, people stating their ethnicity as “Mixed”, “Indian”, “Pakistani”, “Bangladeshi”, “Chinese”, “Black/African/Caribbean” or “Other”.

← 6. The term "visible minority" is used here because it is the official demographic category defined by the Canadian Employment Equity Act and is used by Statistics Canada in their surveys. The Employment Equity Act defines visible minorities as "persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour". The visible minority population consists mainly of the following groups: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese. The question of appropriate terminology is currently being reviewed in Canada, in the context of a task force on modernising the Employment Equity Act (Department of Finance Canada, 2021[81]).

← 7. LGBTQ2+ is the official acronym used by the Government of Canada across its programmes and policies. At Statistics Canada, the LGBTQ2+ acronym is used in order to reflect the broad scope of gender and sexual identities that exist in society. Respondents were included in the LGBTQ2+ population on the basis of self-reported sexual orientation (lesbian, gay, bisexual or another minority sexual identity such as asexual, pansexual or queer) or gender identity (transgender, including respondents with non-binary identities like genderqueer, gender fluid or agender).

← 8. The term LGBTQI2S indicates Lesbian, Gay, Bisexual, Transgender, Queer (or Questioning), Intersex, and Two-Spirit.

← 9. Findings of an Innovative Research Group (INNOVATIVE) online poll conducted from 24 to 29 March, 2020. Each survey is administered to a series of randomly selected samples from the panel. Additional respondents were recruited from online advertisements on Facebook and Instagram. The sample has been weighted by age, gender, region and sexual orientation using Statistics Canada’s 2016 Census data and the 2016 General Social Survey to reflect the actual demographic composition of the Canadian and LGBTQI2S populations, resulting in an overall representative national sample size of 2 000 Canadians and representative national LGBTQI2S sample size of 300.

← 10. This report’s findings are based on a polling series called The Impact of Coronavirus on Households, conducted by NPR, the Robert Wood Johnson Foundation and the Harvard T.H. Chan School of Public Health (NPR/RWJF/Harvard). As reported by Harvard, “Interviews were conducted online and via telephone (cellphone and landline), July 1-August 3, 2020, among a nationally representative, probability-based sample of 3 454 adults age 18 or older in the US”. The poll included a question allowing respondents to identify as LGBTQ. The figures compare respondents who identified as LGBQ and/or transgender to those who identified as both heterosexual and cisgender (i.e., “non-LGBTQ”). Of the total sample, 353 identified as LGBTQ. Findings from the series, as well as additional methodological information, are available at www.hsph.harvard.edu/horp/npr-harvard.

← 11. The parent or another adult in the family used the 2-item Hunger Vital Sign screening questionnaire to report household food security status during the COVID-19 pandemic. It is a 2-question screening tool, suitable for clinical or community outreach use, that identifies families with young children as being at risk for food insecurity if they answer that either or both of the following two statements is “often true” or “sometimes true” (vs. “never true”): “Within the past 12 months we worried whether our food would run out before we got money to buy more”; “Within the past 12 months the food we bought just didn’t last and we didn’t have money to get more.”

← 12. An electronic survey was distributed in April 2020 to 16 435 families in 4 geographic areas, and 1 048 responded. The survey asked families enrolled in a co-ordinated school-based nutrition programme about their social needs, COVID-19–related concerns, food insecurity, and diet-related behaviours during the pandemic. Three variables (food insecurity, frequency of eating out, and frequency of shopping for produce) in the responses were compared on similar items in data collected from 3 880 families in the same 4 locations in fall 2019. The Autumn 2019 survey and the April 2020 survey used similar questions for the 3 variables.

← 13. Pew Research Center conducted this study to understand Americans’ assessments of their personal financial situation during the coronavirus outbreak. For this analysis, Pew surveyed 13 200 US adults in August 2020. Everyone who took part in the survey is a member of Pew Research Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all US adults have a chance of selection. The survey is weighted to be representative of the United States adult population by gender, race, ethnicity, partisan affiliation, education and other categories.

← 14. The term "visible minority" is used here because it is the official demographic category defined by the Canadian Employment Equity Act and is used by Statistics Canada in their surveys. The Employment Equity Act defines visible minorities as "persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour". The visible minority population consists mainly of the following groups: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese. The question of appropriate terminology is currently being reviewed in Canada, in the context of a task force on modernising the Employment Equity Act (Department of Finance Canada, 2021[81]).

← 15. The term "visible minority" is used here because it is the official demographic category defined by the Canadian Employment Equity Act and is used by Statistics Canada in their surveys. The Employment Equity Act defines visible minorities as "persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour". The visible minority population consists mainly of the following groups: South Asian, Chinese, Black, Filipino, Latin American, Arab, Southeast Asian, West Asian, Korean and Japanese. The question of appropriate terminology is currently being reviewed in Canada, in the context of a task force on modernising the Employment Equity Act (Department of Finance Canada, 2021[81]).

← 16. The figure is from a YouGov survey of 4 116 adults. Fieldwork was undertaken between 11 and 15 June 2020. The survey was carried out online. The figures have been weighted and are representative of all Great Britain adults (aged 18+). This percentage was applied to the latest ONS mid-year estimate for the total number of adults in Great Britain.

← 17. These figures are based on author calculations from the English Housing Survey. This is a continuous national survey commissioned by the Ministry of Housing, Communities and Local Government (MHCLG). It collects information about people’s housing circumstances and the condition and energy efficiency of housing in England. Each year a sample of addresses is drawn at random from a list of private addresses held by the Royal Mail. 

← 18. In the summer of 2020, the polling company ICM administered a survey on behalf of Runnymede Trust to 2 585 adults (aged 18+) in Great Britain. The survey covered people’s experiences of the coronavirus pandemic and lockdown and explored the impact of COVID-19 on physical and mental health, work, finances, relationships, childcare and schooling, as well as the understanding of the government’s COVID-19 social and economic measures. A total of 750 people in the sample belonged to an ethnic minority, including Chinese, Indian, Pakistani, Bangladeshi, Black Caribbean and Black African ethnic groups.

← 19. ONS used a combination of data sources to look into how many people have access to a garden and how far they are from the nearest park. ONS used Natural England’s Monitor for Engagement in the Natural Environment (MENE) survey to examine differences by personal characteristics (such as ethnicity, age and socio-economic group). The MENE survey covers England only. Fieldwork started in March 2009 with around 800 respondents interviewed every week across England using an in-home interview format. Every year at least 45 000 interviews are undertaken.

← 20. Data are from the Annual Homeless Assessment Report to Congress, Part 1, 2020.

← 21. Severe housing deprivation is synonymous with homelessness. It refers to people living in severely inadequate housing due to a lack of access to minimally adequate housing. This means not being able to access a private dwelling to rent or own that has all basic amenities. Housing that lacks at least two of the three core dimensions of housing adequacy – habitability, security of tenure, and privacy and control – is deemed severely inadequate.

← 22. The Pew Research Centre surveyed 1 502 US adults from 25 January to 8 February 2021 by mobile phone and landline. The survey was conducted by interviewers under the direction of Abt Associates, and is weighted to be representative of the United States adult population by gender, race, ethnicity, education and other categories. 

← 23. The PISA index of economic, social and cultural status (ESCS) is a composite measure used to estimate a student’s socio-economic background. The index is derived from several variables related to students’ family background: parents’ education, parents’ occupations, a number of home possessions that can be taken as proxies for material wealth, and the number of books and other educational resources available in the home. The index itself is a composite score derived from these indicators via Principal Component Analysis (PCA). Here, however, students are divided into quartiles according to their position in the distribution of ESCS scores in their country or economy.

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