Promoting social cohesion and convergence

Economic and social inequalities in Europe in the aftermath of the COVID-19 pandemic

Report
Published
24 January 2023
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Executive summary
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Author(s): 
Bobrovnikova, Ekaterina; Gineikytė-Kanclerė, Vaida; Klimavičiūtė, Luka; Rahm, Ellen; Schito, Marco; Skardžiūtė, Gabija; Sándor, Eszter

Key findings

  • The first year of the COVID-19 crisis saw the fall in income inequality continue, confirming a levelling of inequality in the EU. However, those seeking work and people with low and medium education levels were most likely to experience a drop in income during the pandemic, highlighting that although income inequality overall may not have increased during COVID-19, it will be critical for policymakers to monitor this closely in the current cost-of-living crisis.
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  • The first year of the COVID-19 crisis saw the fall in income inequality continue, confirming a levelling of inequality in the EU. However, those seeking work and people with low and medium education levels were most likely to experience a drop in income during the pandemic, highlighting that although income inequality overall may not have increased during COVID-19, it will be critical for policymakers to monitor this closely in the current cost-of-living crisis.
  • Health and income inequality are closely linked, with people in the lowest income quintile almost three times as likely to have a disability as people in the top 20%. During the pandemic, inequality in access to health services by income also increased: in 2020, the risk of having an unmet medical need for people in the lowest income quintile was 5.4 times higher than those in the top 20%, highlighting how policies focusing on reducing income inequalities can also reduce health inequalities.
  • Findings reveal that working from home during the pandemic may have created inequalities between low- and high-income groups, where temporary workers, young people and those in precarious employment emerged as more vulnerable to crises. To ensure this does not continue in the increasingly flexible world of work post-COVID, it will be crucial for policymakers to tackle precarious work and increase the transparency and predictability of working conditions.
  • During the pandemic, having adequate equipment to carry out online learning was more important than income, highlighting the importance of tackling the digital divide and access to technology for all over the long term. Parents and students living in rural areas, not needing to commute during this period, were also more likely to be satisfied with the quality of online schooling or education than those living in cities.
  • The ability to work from home created inequalities between low- and high-income groups, accentuating gender inequality in childcare and housework. In 2020, single mothers were most likely to reduce their working hours due to the closure of schools and childcare facilities – if women continue to work more hours of unpaid care than men, this may potentially widen the gender wage gap during recovery.
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Abstract

The COVID-19 pandemic had varying impacts on social groups, depending on existing disadvantages, and it was widely believed that it triggered a rise in inequalities across different areas of life. Using indicators from the EU’s Multidimensional Inequality Monitoring Framework (MIMF), this report Read more

The COVID-19 pandemic had varying impacts on social groups, depending on existing disadvantages, and it was widely believed that it triggered a rise in inequalities across different areas of life. Using indicators from the EU’s Multidimensional Inequality Monitoring Framework (MIMF), this report shows how inequality in the spheres of income, health, employment and education changed between 2010 and 2020. It also examines the main drivers of this change during the pandemic and explores the relationships between government policies in several domains and inequality.

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Formats and languages

  • Report

    Number of pages: 
    102
    Reference no.: 
    EF22002
    ISBN: 
    978-92-897-2309-1
    Catalogue no.: 
    TJ-07-23-019-EN-N
    DOI: 
    10.2806/439913
    Permalink: 
    eurofound.link/ef22002
    Catalogue info

    Economic and social inequalities in Europe in the aftermath of the COVID-19 pandemic

    Author(s): 
    Bobrovnikova, Ekaterina; Gineikytė-Kanclerė, Vaida; Klimavičiūtė, Luka; Rahm, Ellen; Schito, Marco; Skardžiūtė, Gabija; Sándor, Eszter
    Topics: 
    Social policies; Social inclusion; Pay and income; Promoting social cohesion and convergence; Working conditions; Work-life balance; Gender equality; COVID-19; Disability and chronic disease; Living conditions; Inequality

    Formats

    Cite this publication: 

    Eurofound (2023), Economic and social inequalities in Europe in the aftermath of the COVID-19 pandemic, Publications Office of the European Union, Luxembourg.

  • Executive summary

    Reference no.: 
    EF22002EN1
    Catalogue info

    Economic and social inequalities in Europe in the aftermath of the COVID-19 pandemic

    Author(s): 
    Eurofound

    Available for download in 1 language

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  • Working papers

    Related working papers

  • Tables and graphs

    The report contains the following lists of tables and figures.

    List of tables

    Table 1: Indicators selected for the income inequality analysis
    Table 2: OLS regression model exploring the relationship between government spending and inequality in making ends meet according to education level
    Table 3: Panel OLS regression exploring general drivers of income inequality (1995–2020), EU27
    Table 4: OLS regression model exploring drivers of income inequality between rural and urban households
    Table 5: OLS regression model exploring income inequality by individual characteristics
    Table 6: Logistic regressions on income inequality by individual characteristics
    Table 7: Indicators selected for the health inequality analysis
    Table 8: OLS regression model exploring the relationship between government expenditure and inequality in chronic disease
    Table 9: Multilevel logit regression model on worsening health between 2019 and 2020
    Table 10: Multilevel logit regression models on worsening health and mental health between 2019 and 2020
    Table 11: Indicators selected for the employment inequality analysis
    Table 12: OLS regression model exploring the relationship between government expenditure and inequality in opportunity in having a white-collar job
    Table 13: OLS regression model exploring the relationship between gender inequality in occupations, childcare and paid leave at country level
    Table 14: OLS regression model exploring the relationship between gender inequality in being employed, childcare and paid leave at country level
    Table 15: Random effects within–between model showing the relationship between gender inequality in employment, over time and between countries
    Table 16: Multilevel linear regression model on the number of hours worked in 2019 and 2020
    Table 17: Multilevel linear regression model on the change in the number of hours worked between 2018 and 2019 and between 2019 and 2020
    Table 18: Indicators selected for inequality in education analysis
    Table 19: OLS regression model exploring the relationship between government spending and inequality in PISA scores
    Table 20: Determinants of respondents’ satisfaction with the quality of their children’s online schooling (multilevel ordered logit model)

    List of figures

    Figure 1: Dimensions of life of the EU MIMF
    Figure 2: Intersectional approach to effects of COVID-19 on inequality
    Figure 3: Macro-, meso- and micro-level factors in income inequality during the COVID-19 pandemic
    Figure 4: Heatmap showing the results of income inequality indicators by country, 2018–2019, EU27 and the UK
    Figure 5: Income quintile share ratio (S80/S20) for equivalised disposable income, EU27
    Figure 6: Gini coefficient of equivalised disposable income, EU27, Bulgaria, Greece and Poland
    Figure 7: Odds ratio of a household having problems making ends meet (with versus without a tertiary education, 2018) against spending on education (2015, % of GDP), EU27 and the UK
    Figure 8: Odds ratio of a household having problems making ends meet (with versus without a tertiary education, 2018) against spending on social protection (2015, % of GDP), EU27 and the UK
    Figure 9: Scatterplot of government spending on social protection (% of GDP at time t–1) relative to the Gini index of disposable income at time t (1995–2020), EU27
    Figure 10: Odds ratio of households having problems making ends meet (rural versus urban, 2018) against public investments in agricultural R&D (2015, % of GDP), EU27 and the UK
    Figure 11: Households that reported that their income decreased in 2020 compared with the previous year by country (%), selected Member States
    Figure 12: Households containing people aged 50+ that received financial support from the government due to the pandemic by country (%), selected European countries
    Figure 13: Recipients of pandemic-related government support by country, EU27 (%)
    Figure 14: Macro-, meso- and micro-level factors in health inequality during the COVID-19 pandemic
    Figure 15: Heatmap presenting the results of health inequality indicators, 2018–2019, EU27 and the UK
    Figure 16: Map of odds ratios of people reporting unmet medical care needs (women versus men, adjusted), 2018
    Figure 17: Heatmap of odds ratio of feeling depressed for different social groups, 2018–2019, EU27 and the UK
    Figure 18: Risk ratios of having a severe long-standing limitation in usual activities (disability) due to a health problem for various social groups (2010–2020), EU27
    Figure 19: Risk ratios of having an unmet medical need due to high cost, distance to travel or waiting lists for various social groups (2010–2020), EU27
    Figure 20: Government spending on education in 2002 (% of GDP) relative to ex ante inequality of opportunity in having two or more chronic diseases in 2019 (aged 50+), EU27
    Figure 21: Macro-, meso- and micro-level factors in inequality in working life outcomes during the COVID-19 pandemic
    Figure 22: Heatmap showing results of working life inequality indicators, 2018–2019, EU27 and the UK
    Figure 23: Risk ratios of gender inequality in various dimensions of working life (2002–2020), EU27
    Figure 24: Risk ratios of unemployment rates among various social groups (2002–2020), EU27
    Figure 25: Risk ratios of employment rates among various social groups (2002–2020), EU27
    Figure 26: Odds ratio of women being in employment versus men (2019) against the share of children under three years of age in formal childcare (2019, %), EU27
    Figure 27: Average number of weekly hours worked in 2020 by country and contract type, selected EU Member States
    Figure 28: Proportion of women who held second or third jobs by household type, 2020 (%)
    Figure 29: Macro-, meso- and micro-level factors in inequality in education and learning during the COVID-19 pandemic
    Figure 30: Heatmap showing results of education inequality indicators, 2018–2019, EU27 and the UK
    Figure 31: Difference in tertiary education attainment as a whole in 55- to 74-year-olds and those with parents with a lower than tertiary education (2021)
    Figure 32: Trends regarding inequality in education between women and men (2002–2020), EU27
    Figure 33: Risk and odds ratios of NEET rates between various social groups (2004–2020), EU27
    Figure 34: Government spending on education (2013, % of GDP) against P90/P10 PISA scores in mathematics (2018), EU27 and the UK
    Figure 35: Parents’ satisfaction with the quality of online schooling for their children, EU27 (%)
    Figure 36: Parents’ satisfaction with the quality of their children’s online schooling depending on whether they worked from home or not during the pandemic, EU27 (%)

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Research carried out prior to the UK’s withdrawal from the European Union on 31 January 2020, and published subsequently, may include data relating to the 28 EU Member States. Following this date, research only takes into account the 27 EU Member States (EU28 minus the UK), unless specified otherwise.

Part of the series

  • COVID-19

    Eurofound’s work on COVID-19 examines the far-reaching socioeconomic implications of the pandemic across Europe as they continue to impact living and working conditions. A key element of the research is the e-survey, launched in April 2020, with five rounds completed at different stages during 2020, 2021 and 2022. This is complemented by the inclusion of research into the ongoing effects of the pandemic in much of Eurofound’s other areas of work.

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