Tackling the Gender Pay Gap: Valuation and Distribution of Paid Work and Unpaid Care Work - EIGE Report - Hoofdinhoud

Council of the European Union

Brussels, 16 October 2020 (OR. en)

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SOC 514 EMPL 379 GENDER 106 ANTIDISCRIM 95

NOTE

From: General Secretariat of the Council

To: Delegations

Subject: Tackling the Gender Pay Gap: Valuation and Distribution of Paid Work and Unpaid Care Work

• - 

  EIGE Report

Delegations will find attached a report entitled "Gender equalities in care and consequences on the

labour market" prepared by the European Institute for Gender Equality (EIGE) at the request of the

German Presidency.

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Foreword

The COVID-19 pandemic has highlighted the importance of both paid and unpaid care work for the wellfunctioning of society and the economy. During the pandemic, the burden of work for carers exploded - whether for lone parents taking care of their children at home or nurses treating patients in hospitals.

Care workers were applauded and described as ‘essential workers’. Yet they are among the most disadvantaged and underpaid professions in the EU. This undervaluing of care work is closely linked to the idea that caring is a women’s responsibility within the household and that it’s done for free.

This assumption needs to change, and fast. One of the major factors contributing to the gender pay gap is the large burden of unpaid care work that so many women take on at home. Care responsibilities are holding back women’s job prospects and influencing the choices they make in their professional lives, which is not the case for most men. More women work part-time, in temporary and low-paid jobs, and are underrepresented in big firms and at management level.

While the consequences from the pandemic are still unfolding, it’s clear that the distribution of care work, whether it be paid or unpaid is one of today’s most significant challenges for gender equality – one that needs to be put at the centre of Covid-19 response strategies.

The funding of care systems needs to be a priority when it comes to Covid-19 recovery measures. We need to support our care systems by investing more into them. The working conditions and pay of carers, who are mostly women, also need to be improved. Higher investments would lead to new jobs in care and related professions, such as medical technology, cleaning and hospitality services. Better working conditions in care could also attract more men to the profession, helping to address the shortage in carers.

If we want a more gender-equal society, we need a two-fold approach that tackles the uneven sharing of care work. Firstly, we need changes at the household level, where the sharing of care tasks between women and men becomes the norm and secondly, we need accessible and affordable professional care services that can help tackle the rising care needs expected in the EU, as the population ages.

This report is part of EIGE’s work to monitor the EU’s progress towards its gender equality commitments under the Beijing Platform for Action (BPfA). It was prepared at the request of the German Presidency of the Council of the EU. We are confident that this report, its findings and recommendations provide concrete evidence why care needs to be at the centre of EU policy-making, if we want to keep moving forward with gender equality.

Carlien Scheele EIGE Director

Acknowledgements

This report was developed by the research & statistics team of the European Institute for Gender Equality (EIGE): Blandine Mollard, Jakub Caisl, Davide Barbieri, Dr Marre Karu, Giulia Lanfredi, Vytautas Peciukonis, Maria Belen Pilares, Dr Jolanta Reingardė and Dr Lina Salanauskaitė. The report is based on a study prepared by the research team of IRS: Flavia Pesce, Manuela Samek Lodovici, Nicoletta Torchio (IRS) and Vera Lovazzi, GESIS and IRS. Other contributors involved from IRS: Elena Ferrari, Emma Paladino, Nicola Orlando, Daniela Loi and Serena Drufuca. The research efforts that went into this report were coordinated by Blandine Mollard with the support of Giulia Lanfredi (EIGE), together with Flavia Pesce (IRS). Many thanks to other colleagues at EIGE for their valuable contributions and comments throughout the report development such as Helena Morais Maceira. The administrative and communications support from colleagues at EIGE was also very much appreciated. The following individuals are thanked for their role in reviewing the report and making other important research contributions: Isabella Biletta, Senior Research Manager, and Jorge Cabrita, Research Manager, Working Life Unit, and Hans Dubois, Research Manager, Social Policies Unit, Eurofound as well as Prof. E. Vera Troeger, President of the European Political Science Association, Chair of Comparative Political Science, University of Hamburg.

The report greatly benefited from expert advice received from participants in EIGE’s expert consultation meeting held on 20th and 21st of April 2020, from the German Federal Ministry for Family Affairs, Senior Citizens, Women and Youth, and the European Commission, in particular the Gender Equality Unit at the DG JUST and the High Level Group on Gender Mainstreaming.

Contents

Foreword ...................................................................................................................................................................................................... 7

Acknowledgements ................................................................................................................................................................................... 8

Contents ....................................................................................................................................................................................................... 9

List of figures ............................................................................................................................................................................................. 10

Executive Summary ................................................................................................................................................................................. 13

Introduction ............................................................................................................................................................................................... 17

Chapter 1: Women’s work is undervalued, both at work and at home .................................................................................... 18

1.1 Care is a gendered issue ............................................................................................................................................................. 18

1.2 Gender inequalities in pay ......................................................................................................................................................... 22

1.3 Linkages between gender care gaps and gender pay gaps ........................................................................................... 25

Chapter 2: Are policies promoting greater equality? ................................................................................................................... 29

2.1 Policies promoting a fairer distribution of care within households ........................................................................ 30

2.2 Policies supporting external solutions to care needs ................................................................................................. 36

Chapter 3: From equal sharing of care to use of external services: where do families stand? ......................................... 40

3.1 Is equal sharing of care a lived reality for families in the EU? ......................................................................................... 40

3.2 How much of their care needs do families externalise and what are the effects?.................................................... 46

3.3 Do external care services support more equal sharing of care work? ......................................................................... 52

Chapter 4: What are the consequences of externalisation? ....................................................................................................... 56

4.1 The paid care sector: significant employment yet perpetrating inequalities .............................................................. 56

4.2 The impact of the COVID-19 pandemic on the care sector ............................................................................................ 60

Conclusions ............................................................................................................................................................................................... 63

Policy recommendations ...................................................................................................................................................................... 65

Annex ......................................................................................................................................................................................................... 69

• a. 

  What is care work? ........................................................................................................................................................................ 69

• b. 

  Unpaid care work: additional descriptive statistics ................................................................................................................70

• c. 

  Gender pay gap ..............................................................................................................................................................................72 d. Cross-country correlation analysis: gender gaps in pay and care ...................................................................................73

• e. 

  Multivariate regression analysis and decomposition techniques ......................................................................................73

• f. 

  Focus group discussion ................................................................................................................................................................. 80

• g. 

  The International Social Survey Programme (ISSP) ............................................................................................................. 80

• h. 

  The paid care sector ..................................................................................................................................................................... 82

Appendix: Policy boxes ......................................................................................................................................................................... 88

Bibliography ............................................................................................................................................................................................. 92

List of figures

Figure 1: Participation rate of employed women and men in unpaid care work, as a percentage of total employed, (%, 15+, EU-28, 2015) .............................................................................................................................................................................. 19

Figure 2: Mean time spent in daily unpaid care activities by employed women and men, (15+, hours per day, EU- 28, 2015) ..................................................................................................................................................................................................... 19

Figure 3: Mean time spent daily on total unpaid care work by employed women and men, by country (15+,hours per day, EU-28, 2015) ............................................................................................................................................................................ 20

Figure 4: Participation rate of employed women and men in unpaid care work, as a percentage of total employed by country (%, 15+, EU-28, 2015) ....................................................................................................................................................... 20

Figure 5: Women and men working part-time as percentage of the total employment, by country (%, 15+, EU-28, 2019) ........................................................................................................................................................................................................... 22

Figure 6: Gender gaps in the unadjusted gross hourly pay and in overall earnings (%, 15+, by country, EU-28, 2014) ..................................................................................................................................................................................................................... 23

Figure 7: Unadjusted gender pay gap in the EU, by job characteristics (%, 15+, EU-28, 2014) ....................................... 25

Figure 8: Correlation between unadjusted gender pay gap and gender gap in time spent in direct care among employees (15+, EU-28, 2014, 2015) .................................................................................................................................................. 26

Figure 9: Estimated effect of direct care on women’s and men’s gross hourly income in the EU (%, 16+, EU-28,

2016) ............................................................................................................................................................................................................27

Figure 10: Decomposition of the explained gender pay gap (%, 16+, EU-28, 2016) ........................................................... 28

Figure 11: The four major gender pay gap determinants across the Member States (16+, EU-28, 2016) ..................... 29

Figure 12: Total length of statutory mandatory and voluntary paternity leave in the EU (number of days, EU-28,

2019) ........................................................................................................................................................................................................... 33

Figure 13: Total length of paid and unpaid parental leave in the EU (number of weeks, EU-28 2019) .......................... 34

Figure 14: Cross-country comparison of ineligibility rates among the employed and gender gaps in unpaid care

(EU-28, 2015-2017) ................................................................................................................................................................................. 36

Figure 15: Typologies of the gendered division of care among cohabiting couples (%, 18+, EU-28, 2012) .................. 41

Figure 16: Typologies of gendered division of care among cohabitating couples, by household employment patterns (%, 18+, EU-28, 2012) ............................................................................................................................................................ 42 Figure 17: Typologies of gendered division of care among cohabitating couples, by attitudes to gender equality (%, 18+, EU-28, 2012) .................................................................................................................................................................................... 43

Figure 18: Share of employed women and men carrying out daily care activities (%, 15+, EU-28, 2000-2015) .......... 44

Figure 19: Gender gaps in time dedicated to direct care per day among the employed population (hours per day, 15+, EU-28, 2005-2015) ......................................................................................................................................................................... 44

Figure 20: Gender gaps in time dedicated to housework (cleaning and cooking) per day, among the employed population (hours per day, 15+, EU-28, 2005-2015) ..................................................................................................................... 45

Figure 21: Share of children enrolled in formal care, by age (%, EU-28, 2018) ..................................................................... 46

Figure 22: Share of children under three in formal care, by number of hours per week (%, EU-28, 2018) .................. 46

Figure 23: Gender gap in the use of professional childcare services among employed people with childcare responsibilities (18-64, % points, EU-28, 2018) ............................................................................................................................... 48

Figure 24: Effects of childcare responsibilities on employment of women and men (25-49, %, EU-28, 2018) ............ 49

Figure 25: Coverage rates of long-term care recipients by type of care, as a percentage of population potentially in need of care (%, 15+, EU-28, 2016) ................................................................................................................................................... 49

Figure 26: Share of employed population or population with previous work experience who experienced at least one month of work interruption due to care responsibilities for relatives with health issues (%, 18-64, EU-28, 2018) ...................................................................................................................................................................................................................... 51

Figure 27: Share of employed population or population with previous work experience who experienced a decrease in working time of at least one month due to care responsibilities for relatives with health issues (%, 18-

64, EU-28, 2018) ....................................................................................................................................................................................... 51

Annex figures

Annex figure 1: Participation rates in unpaid care work as a percentage of population (18+, EU-28, 2016) .................70

Annex figure 2: Employment rate by sex (20-64, EU-28, 2019) ..................................................................................................70

Annex figure 3: Women who are inactive due to care responsibilities, as a percentage of total population (15-64, EU-28, 2019) .............................................................................................................................................................................................. 71

Annex figure 4: Frequency of care activities of employed women and men (15+, EU-28, 2000-2015) .......................... 71

Annex figure 5: Selected care occupations: distribution by personal characteristics and income deciles (%, 15+, EU- 28, 2018) .................................................................................................................................................................................................... 83

Annex figure 6: Share of part-time work and main reason for choosing it, in selected care occupations and total economy (%, 15+, EU-28, 2018) .......................................................................................................................................................... 84

Annex figure 7: Share of temporary work and main reason for choosing it, in selected care occupations and total economy (%, 15+, EU-28, 2018) .......................................................................................................................................................... 85

Annex figure 8: Share of workers on atypical hours in selected care occupations and total economy (15+, EU-28, 2018) ............................................................................................................................................................................................................87

Annex figure 9: Working conditions in selected care occupations and total economy (15+, EU-28, 2018) ................. 88

List of tables

Table 1: Definition of care work used in the report ....................................................................................................................... 69

Table 2: Measures of gender pay gap used in the report ...........................................................................................................72

Table 3: Cross-country correlations between inequalities in pay and gender care gaps among employees

(Pearson’s r), EU-28 .................................................................................................................................................................................73

Table 4: Observed characteristics from the EU-SILC 2016 used in the regression analysis ................................................75

Table 5: Wage regressions: coefficients of proxy variables for unpaid care work, EU-SILC 2016 ..................................... 77

Table 6: Decomposition of the observed gender pay gap among employees (16+), EU-SILC 2016 ..............................79

Table 7: ISSP sample sizes by wave, country and sex of the respondent ............................................................................... 82

Country codes Abbreviations

BE Belgium BPfA Beijing Platform for Action BG Bulgaria ECDC European Centre for Disease Prevention CZ Czechia and Control DK Denmark ECEC Early Childhood Education and Care DE Germany EEG European Expert Group EE Estonia EFSI European Federation for Services to IE Ireland Individuals EL Greece EHIS European Health Interview Survey ES Spain EQLS European Quality of Life Survey FR France ERDF European Regional Development Fund HR Croatia EU-LFS European Labour Force Survey IT Italy EU-SILC European Union Statistics on Income and CY Cyprus Living Conditions LV Latvia EWCS European Working Conditions Survey LT Lithuania EWL European Women’s Lobby LU Luxembourg FRA European Union Agency for Fundamental HU Hungary Rights MT Malta FWA Flexible work arrangements NL Netherlands GHG Greenhouse gas emissions AT Austria HETUS Harmonised European Time Use Surveys PL Poland ICT Information and communications PT Portugal technology RO Romania ILO International Labour Organization SI Slovenia ISSP International Social Survey Programme SK Slovakia LTC Long-term care FI Finland MISSOC Mutual Information System on Social SE Sweden Protection UK United Kingdom OADR Old-Age Dependency Ratio EU 28 EU Member States (2013-2020) OECD Organisation for Economic Co-operation NO Norway and Development IS Iceland PHS Personal and household services PPE Personal Protective Equipment SES Structure of Earnings Survey SHARE Survey on Health Ageing and retirement in Europe STEM Science, Technology Engineering and Mathematics TUC Trade Union Congress WBG Women’s Budget Group WHO World Health Organization

Executive Summary

Gender inequalities in unpaid care are acknowledged to be the ‘missing link’ ( 1 ) in the analysis of gender gaps in labour market participation, quality of employment and, particularly, pay. Care work includes all activities and occupations that directly and indirectly involve care processes and entail ‘the provision of personal services to meet those basic physical and mental needs that allow a person to function at a socially determined acceptable level of capability, comfort and safety’ (Himmelweit, 2007, p. 581). Progress in gender equality in the distribution of unpaid care mirrors progress achieved in the EU on gender equality at large: steady but fragile and far too slow. Over time, the gender gap in time spent on care has narrowed, decreasing by one hour a day since 2005. However, the movement towards a model where women and men share earning and caring roles, often referred to as ‘dual earner/dual carer model’, is incomplete, as women have moved strongly to the labour market while men have not entered the home sphere in equal measure. The dual earner/dual carer model also implies that care from parents should be complemented by high-quality childcare and long-term care services provided by well-qualified and well-compensated non parental caregivers (Wright, Gornick, & Meyers, 2009), which is not a reality across the EU.

Inequalities originate in the household

Data shows that certain characteristics increase the likelihood of dividing care equally among women and men, such as a dual earning model and gender egalitarian values. Nevertheless, it also shows that most cohabiting couples in the EU follow a pattern where women are the main caregivers in the household and only about one

2

third of families share care activities equally ( ). Despite progress, ‘care’ is still considered a woman’s responsibility in the family and this conviction persists even when women enter the labour market ( 3 ). According to the latest available data, employed women spend on average 90 minutes more than employed men on housework and direct care activities every day. These inequalities vary according to family circumstances, with women living in couples with children spending more than double the daily time on care work compared to those living in couples without children (5.3 hours per day compared to 2.4 hours). Job characteristics also matter in the analysis of unpaid care, with evidence that women in temporary jobs or with no formal contract spend twice as long engaged in unpaid care every day than women employed in permanent jobs.

Gender inequalities in care have far-reaching effects

Women’s disproportional burden of unpaid care work affects and hinders their participation in the labour market in several ways. Care responsibilities keep some 7.7 million women out of the labour market, compared to just 450,000 men ( 4 ). Among women who are employed, 60 % report experiencing some change in employment as a

1 (Ferrant, Pesando, & Nowacka, 2014)

2 EIGE elaboration of ISSP 2012 data, more details can be found in Figure 15.

3 According to data from Eurobarometer, in 2017, 73% of respondents think that women spend more time than men on housework and caring duties. 22% think it is equal(European Commission, 2017b).

result of childcare responsibilities, compared to 17 % of employed men. Only 3 % of men have reduced their working hours due to childcare responsibilities, something that 18 % of employed women have done ( 5 ).

Difficulties in reconciling work and private responsabilities and the cultural norm assigning care to women influence choices women make in their professional lives. For instance, women make up 72 % of workers in the education sector and 89 % of domestic workers, compared to 46 % of workers in total employment. In terms of job prospects, career breaks due to caring often constrain women to part-time, irregular, temporary and low-paid jobs, as they are assumed to provide greater flexibility than standard jobs and allow women to juggle their paid work and unpaid care. 29 % of part-time employed women cite care duties as their main reason for working parttime ( 6 ). Characteristics of women’s employment produced by unpaid care responsibilities – sectoral segregation, high part-time employment, underrepresentation in big firms and in supervisory positions (vertical segregation) - determine a notable part of the gender pay gap. Currently in the EU, women’s average gross hourly earnings are 16 % lower than those of men (

7 ).

Promoting a fairer distribution of unpaid care within households would thus support efforts to reduce the gender pay gap and other gender inequalities in pay. In turn, tackling both vertical and horizontal segregation is essential to reduce the gender pay gap and promote gender equality generally. Women continue to be underrepresented in decision-making positions at all levels, even in female-dominated sectors and occupations, such as education and healthcare. The EU Gender Equality Strategy 2020-2025 encourages Member States to adopt the 2012 proposal for a Directive on improving the gender balance on corporate boards, which aims for a minimum of 40 % of non-executive members of the underrepresented sex on company boards (European Commission, 2020c). Binding pay transparency measures are also needed to tackle the asymmetry of pay information between employees and employers. From this perspective, the forthcoming Directive on pay transparency represents a much awaited development (European Commission, 2020c).

Scarce data availability on unpaid care makes it difficult to study direct consequences on the labour market

Unpaid care and earnings interact in multiple and complex ways, with limited data making the causal link difficult to investigate fully. A multivariate regression analysis ( 8 ) shows that having young children (0-6 years old) in the household is positively associated with men’s income - compared to not having young children – while no significant association appears with women’s income. The use of childcare services shows a positive association with both women’s and men’s income, with a greater impact on women’s. Women with children under 12 using

5 EIGE calculations based on Eurostat, EU-LFS ad hoc module on reconciliation between work and family life, lfso_18ceffed. More details can be found in Figure 24.

6 Compared to only 6 % of men. Eurostat (lfsa_eppga; lfsa_epgar).

7 Latest available data refers to 2018. Source: Eurostat [sdg_05_20].

8 EU-SILC 2016 cross-sectional microdata is used to explore the linkages between gender inequalities in unpaid care work and gender

inequalities in pay (for employees aged 16+). The analysis closely followed the methodological approach used by Boll, Leppin, Rossen, and Wolf (2016). Near cash income was used as a measure of ‘pay’. It includes wages and salaries paid by the main and any secondary or casual jobs, as well as supplementary payments, commissions and bonus payments. The gender pay gap then is measured as the logarithm of gross hourly income. Unusually, this work included in the model specification some variables capturing the participation of women and men in unpaid care work, especially in relation to childcare tasks (see Table 4 in the Annex). The main limitation of the model is that it does not include some aspects (e.g. career breaks) that could strongly impact the results. For more details on the regression analysis, see Annex (section e).

childcare services at least 14 hours a week ( 9 ) are estimated to earn +4.8 % more on an hourly basis, compared to women that do not outsource childcare. The estimated difference for men is +2.6 %. All other things being equal, therefore, a higher use of childcare services seems to be associated with lower gender inequalities in pay. The direction of the causal relationship needs to be carefully explored in future research, however, as the above analysis shows a robust link between inequalities in unpaid care and pay but it is unclear whether inequalities in care cause pay gaps or vice versa.

Around two-thirds of the gender pay gap in the EU remains unexplained – this is partly due to lack of data on certain worker characteristics and partly due to discrimination in the labour market that goes beyond individual characteristics. It is likely that some consequences of unpaid care work which are not captured by available data (e.g. career breaks) account for a large share of the unexplained pay gap, for this reason the result of this analysis need to be interpreted with caution. Future research to better explore this at EU level will need high-quality datasets that link data on pay and unpaid care work. Making such datasets available requires combining available EU datasets used to measure unpaid care work (time use surveys, the European Working Conditions Survey (EWCS)) with those used to measure the pay gap. It also requires improved collection of EU-level data on unpaid care work, for example by carrying out EU time use surveys more frequently and extending their coverage of Member States, or by improving collection of data on certain consequences of unpaid care, such as career breaks.

External care services are essential but do not supersede efforts toward equal sharing

Policy initiatives at both EU and Member State level generally address care inequalities in two ways. The first consists of initiatives to promote more equal sharing of unpaid care tasks within the household (e.g. nontransferable parental leave). The second – known as ‘externalisation’ – supports the partial or total transfer of unpaid care activities from the household to other people and/or paid services. This externalisation is particularly important in the context of the rising care needs expected in the EU in the coming decades, especiallly related to long-term care 10 .

In 2019, the adoption of the Work-Life Balance (WLB) Directive for parents and carers showed strong political will to facilitate better distribution of care and household work between women and men. Among the provisions are new or harmonised labour market rights, such as the right to flexible working arrangements for workers with care responsibilities, carer’s leave, parental leave and increased job protection (European Parliament & Council of the European Union, 2019). While the Directive represents a step in the right direction, some aspects of its implementation are left to Member States to define, which could lead to substantial divergence in access to the benefits enshrined in the Directive and significant differences in take-up, especially among men. These aspects include rules defining eligibility to parental leave. At the moment, no Member State in the EU-28 offers universal access to parental leave - EIGE estimates that 10 % of women and 12 % of men in employment in the EU are not

9 The median value of the distribution of hours of childcare externalisation is about 14 for those households with at least one child up to 12 years old and which externalise at least one hour per week. The hours of externalisation are calculated as the average hours of all children in the household using childcare services (centre-based services; day care centre; professional childminder; relatives).

10 Public expenditure on long-term care is expected to increase strongly over the next few decades. Due to population ageing, public spending on long term are in the EU under existing national policies is projected to increase from 1.6% of GDP on average in 2016 to 2.7% in 2070 (European Commission, 2019b).

eligible for parental leave (EIGE, 2020e). Analysis shows that countries with higher eligibility for parental leave – for both women and men - also tend to have smaller gender gaps in unpaid care. This could indicate that uptake of parental leave can promote fairer sharing of care. Similarly, compensation for paternity and parental leave is key to stimulating uptake among fathers, with some academics arguing that compensation at 100 % income level is the most conducive incentive to take-up this leave.

The WLB Directive includes non-legislative aspects, such as investment in infrastructure for care, particularly longterm care (LTC). EIGE’s evidence shows that a minimal fraction of EU funds is used for that purpose (EIGE, 2020a). The extent of financing for active ageing programmes is similarly limited (EIGE, 2020a).

The effects of policy provisions such as flexible working arrangements (FWA), statutory leave policies, service provision and cash/tax towards a fairer division of unpaid care depend on how they are designed (eligibility criteria, duration, costs and level of income support, availability and quality, etc.), how they can be combined, and the presence of supportive gender norms in a given society. For example, despite greater access to FWAs, men’s uptake of those entitlements is hindered by gender norms that attribute efforts to reconcile home and work life to women. Research shows that men often use FWAs to increase their engagement in paid work, while women resort to FWAs to better meet their family responsibilities. This demonstrates that policy coherence and communication is essential to promoting positive outcomes.

Making the case for a transformative policy-making approach

Despite some progress, public policies supporting equal sharing of care are characterised by two limiting aspects. Firstly, they are limited to people already in employment, leaving behind those families that experience the most acute tensions between care responsibilities and paid work. Secondly, and most importantly, they focus on supporting women’s employment but lack the transformative goal likely to significantly affect gender relations and the ways families share care over time.

These two policy limitations translate into persistent gaps in coverage for care services, gaps that women fill with unpaid work. More specifically, no targets for long term care service provision have been adopted at EU level. In addition, in terms of provision of early childhood care and education services, the Barcelona targets adopted in 2002 would benefit from being revisited in order to set more ambitious goals for enrolment of children under three years of age and to include qualitative elements of service provision (quality, accessibility, affordability). As a result, gaps in coverage persist and cost is too often a barrier to accessing care services for children, older people and people with disabilities.

Outsourcing the burden of unpaid care is not enough if not accompanied by a structural revaluation of care work

Focus group discussions show that the use of external care services often stems from women pushing back against the disproportionate burden of unpaid care expectations, as a way to reclaim some leisure time and reduce tensions within the family. However, this itself creates another form of unpaid and unshared care work linked to organising care, such as planning, budgeting, scheduling of care and household tasks. The notion of care being a women’s responsibility goes therefore unchallenged, with care simply transferred to other women outside the household. This becomes apparent with the establishment of ‘global care chains’: chains of interdependency (and power relations) between those women - often native-born - who can afford to give up on their share of unpaid care labour by relying on external services, and other women – often foreign-born and from a migrant background – who work in the paid care sector and experience low pay, dire and precarious working conditions.

Care work is devalued in both the household and the labour market. Skills related to these jobs tend to be undervalued and less formalised (EACEA, 2019); there are low investments in the care sector, care jobs are poorly remunerated and have few career prospects. These are direct consequences of the longstanding perception that care had no economic value, and was not considered ‘work’. The externalisation approach needs to be complemented by a structural revaluation of care work, in both society and the economy (i.e. more investment in care infrastructure, better regulation to support care workers). In the absence of a transformative policy-making approach, outsourcing the burden of unpaid care might ease inequalities between women and men within the same household, but it reproduces inequalities between those households who are able to externalise care tasks and those who are not.

COVID-19 exacerbated the fragility of the paid care sector, highlighted the need for greater public investment

The COVID-19 pandemic is exposing the fragility of de-prioritised and de-funded care infrastructures ( 11 ), revealing the consequences of these critical political choices on society as a whole, as well as on the economy. Care, healthcare and long-term care workers, most of them, women, have been disproportionately affected by the virus, and the lockdown measures enforced across the EU aggravated the strain on households that are reliant on external care services. The global pandemic seems to have catalysed a revaluation of care work at societal level by sparking conversations on the essential role of care, both paid and unpaid.

Higher investments would help to solve care gaps and create new jobs in the care and related sectors (e.g. people producing medical equipment, cleaners, delivery drivers, hospitality workers). The COVID-19 pandemic has shown that care jobs are essential for the functioning of society and the economy, and this momentum must now be harnessed to prioritise care on the EU political agenda in the longer term. Developing a European strategy on social care and social protection could guide the implementation of the European Pillar of Social Rights and complement the WLB Directive for parents and carers. To meet the caring needs of an ageing population, it would be useful to establish a framework to regulate minimum levels of care for older people, similar to the Barcelona targets set by the European Council in 2002 to regulate the provision of formal childcare.

Introduction

2020 marks the 25 th anniversary of the Beijing Platform for Action (BPfA), the leading roadmap for gender equality

in all spheres of public and private life. All EU Member States have adopted the Platform and committed to its implementation. More recently, Member States adopted the 2030 Agenda for Sustainable Development and its Sustainable Development Goals (SDGs), including SDG5 on gender equality.

11 The post Euro crisis years were characterised by a widespread contraction in social investments due to budgetary trade-offs and austerity measures adopted to prioritise fiscal consolidation (Bouget, Frazer, Marlier, Sabato, & Vanhercke, 2015; Natali & Vanhercke, 2015; Ronchi, 2018). This had a notable detrimental impact on care infrastructures in several EU countries (European Public Service Union, 2019; Quaglio, Karapiperis, Van Woensel, Arnold, & McDaid, 2013).

Many of the challenges identified in the BPfA in 1995 remain relevant today, including the gender pay gap and women’s disproportionate burden of unpaid care. In the context of EIGE’s mandate to monitor progress in achieving the objectives of the Platform in the EU, this report focuses on BPfA Area F, ‘Women and the economy’, and explores the ways in which gender inequalities in pay are linked to gender inequalities in care in Europe. The analysis aims to contribute to important policy discussions on the gender pay gap and gender care gap – two priority areas of the EU Gender Equality Strategy 2020-2025.

This analysis is innovative in that it considers inequalities in pay and care together, as the two are inextricably intertwined. Care is one of the most important dimensions of gender equality but is often ‘invisible’ because it has been long associated with the domestic sphere and was thus deemed inherently separate from paid labour. However, the COVID-19 pandemic has placed care inequalities at the centre of the public debate and cast new light on national care systems. During the pandemic, care workers were described as ‘essential workers’, while being among the most disadvantaged and underpaid professions in the labour market. This originates directly from the cultural and economic devaluation of care work, which is closely associated with the assumption that ‘care’ is a woman’s responsibility within the household and the expectation that it would be provided free of charge.

Relying on external care services is a reality for a growing number of individuals, due to looming demographic changes such as the ageing population, increased life expectancy, lower birth rate and, particularly, smaller household size. In fact, the average household composition dropped from 2.4 people in 2010 to 2.3 in 2019, and currently about one-third of households are formed by just one person - a 19 % increase since 2010 (European Commission, 2020a) . In the coming years, a large share of the population will rely solely on care services rather than on family members’ support. With care an inevitable priority on the EU political agenda, inequalities in this area need to be addressed in a transformative way.

The report consists of four chapters. The first illustrates the extent of gender inequalities in care and in pay in the EU and the linkages between the two. The second chapter reviews the two main policy approaches to tackling these inequalities, which address the so-called ‘equal sharing of care’ (among women and men within the household) and ‘care externalisation’ (outsourcing care tasks to external providers). The third chapter focuses mainly on ‘externalisation’ as the predominantly adopted solution in the EU and illustrates the historical evolution of intra-household care arrangements, as well as families’ reasons for outsourcing care tasks to external service providers. The fourth chapter analyses the implications of externalisation, including care workers’ dire employment conditions and the role of COVID-19 in exposing the fragilities of the underfunded care sector. Finally, the report provides a range of policy recommendations to achieve greater equality in the areas of unpaid care and paid employment, at both Member State and EU level.

Chapter 1: Women’s work is undervalued, both at work and at home

One of the strongest hierarchical dualisms is the conventional economic distinction between ‘productive’ and ‘unproductive’ work (Beneria, 1999; Waring, 1989, 2003). This is reinforced by the neoclassical model of labour supply, where time spent outside of paid labour is assumed to be spent ‘at leisure’ (Thomson, 2009). This results in the work done by men being widely acknowledged, with most men considered economically ‘productive’, while women who are engaged in full-time household care are commonly viewed as ‘not working’ and ‘unproductive’. Feminist economists were the first to argue for the economic importance of non-market activities, such as childcare, elderly care and domestic work (Himmelweit, 1995; Power, 2004; Razavi, 2009). ‘Social reproduction’, the renewal and care of human life (and thus of human labour power) across generations is at the centre of the feminist understanding of the economy and is viewed as equally important as the industrial production of goods and services (Ferguson, 2018). Feminist economists theorised the concept of ‘care work’ ( 12 ) by overcoming the traditional distinction between the spheres of ‘care’ and ‘work’ that were previously considered separate and mutually exclusive.

The neoclassical devaluation of care translates into the labour market, where paid care is stereotypically considered a ‘woman’s job’ (Sarti & Scrinzi, 2010) and is underpaid compared to traditionally male-dominated sectors. The concentration of women in low-paid sectors and occupations - a phenomenon referred to as gender segregation - is primarily due to the disproportionate burden of care that falls on their shoulders, and contributes to maintaining the gender pay gap in labour markets.

1.1 Care is a gendered issue

1.1.1 Care at home is mostly borne by women

Care work includes all activities and occupations that directly and indirectly involve care processes and entail ‘the provision of personal services to meet those basic physical and mental needs that allow a person to function at a socially determined acceptable level of capability, comfort and safety’ (Himmelweit, 2007, p. 581). Looking at the entire EU population ( 13 ), it is clear that almost all women in the EU (92 %) are regular carers (i.e. provide unpaid care work for at least several days a week) and 81 % are daily carers (compared to 68 % and 48 % of men, respectively). In spite of the strong increase in female participation in the labour market in recent decades, gender roles persist in the home even in dual-earning households, where women continue to assume the main role in providing direct care and routine housework (ILO, 2018; Kan, Sullivan, & Gershuny, 2011) (see section 3.1.1.1). Academics have debated the key factors behind the persistence of the gender care gap, typically stressing the resistance to change in gender culture and gendered social norms.

Gender care gaps persist among the employed population

On average in the EU-28, almost all employed women (94 %) are involved in unpaid care work at least several

times a week, compared to 70 % of employed men ( Figure 1 ). Housework tasks are the most unequally shared,

with 93 % of women and 53 % of men regularly undertaking such work.

Figure 1: Participation rate of employed women and men in unpaid care work, as a percentage of total employed, (%, 15+, EU-28, 2015)

12 See definition of care work in the Annex (Table 1).

13 See Annex figure 1

Source: EIGE elaboration of EWCS 2015.

Note: Declared participation in unpaid care activities daily or at least several times a week based on EWCS (Q95. ‘In general, how often are you involved in any of the following activities outside work?’). Results do not consider records with unavailable information (don’t know/refusal/not applicable).

Of those involved in unpaid care on a daily basis, the time spent by employed women (3.9 hours per day ( 14 )) is

one and a half times higher than the time spent by men (2.6 hours per day) ( Figure 2 ). The amount of time spent

by employed people on care increases markedly with the presence of children or grandchildren in the household. On average in the EU-28, employed women spend 3.3 hours per day engaged in childcare, while employed men spend 2.7 hours.

Figure 2: Mean time spent in daily unpaid care activities by employed women and men, (15+, hours per day, EU-28, 2015)

Source: EIGE elaboration of EWCS 2015.

Note: For each category of unpaid care work, mean time spent is calculated on those employed who declare their participation in the activity every day, based on EWCS (Q96: ‘On average, how many hours per day do you spend on the activity?’). Results do not consider records with unavailable information (don’t know/refusal/not applicable).

Figure 3 illustrates that the mean time dedicated to unpaid care tasks varies between Member States. The greatest gender inequalities are present in Greece, Cyprus and Austria. By contrast, Denmark, Slovakia and Finland have the most balanced engagement of women and men in care.

14 EWCS data provides information on time spent only by those declaring their participation in unpaid care every day.

Figure 3: Mean time spent daily on total unpaid care work by employed women and men, by country (15+,hours per day, EU- 28, 2015)

Source: EIGE calculations based on EWCS 2015.

Note: Low data reliability for men in EL, CY, PL, SK.

Women generally participate in care on a daily basis, while men are usually involved several times a week. Although the Member States show substantial differences, women’s total involvement (the sum of daily and weekly participation rates) is higher than men’s in every Member State. The biggest gender gaps are found in Greece,

Cyprus and Poland. By contrast, Denmark, Slovenia and Sweden have the smallest inequalities ( Figure 4 ).

Figure 4: Participation rate of employed women and men in unpaid care work, as a percentage of total employed by country (%, 15+, EU-28, 2015)

Source: EIGE elaboration of EWCS 2015.

Note: Low reliability for men in EL, CY, PL, SK.

1.1.2 Inequalities vary across groups of employees according to personal and job characteristics

Gender gaps not only differ between countries but also between different groups of workers according to their personal and job characteristics ( 15 ). The presence of children in the household and marital status are powerful indicators of the extent to which intra-household dynamics affect the division of unpaid care. For example, women living in couples with children spend more than double the daily time on care work compared to those living in couples without children (5.3 hours per day compared to 2.4 hours) ( 16 ). The central role of childrearing is reflected in the distribution of unpaid care work among different age groups. Among the employed engaged in care every day, the daily time spent on unpaid care is higher in the childbearing age group 25–49, especially for women, resulting in a higher gender care gap than among the other age categories.

Gender gaps in care decline with age, with an average of three hours per day spent by employed women and 2.5 hours by employed men in the age group 50–64. People in this group are especially involved in caring for their grandchildren amid caring for adults (partner and parents) ( 17 ). Indeed, most elderly care provision continues to be delivered informally within families ( 18 ) (Bittman & Folbre, 2004; EIGE, 2020d; Henz, 2009, 2010; Luppi & Nazio, 2019; Saraceno, 2008), and it remains highly gendered: women are more likely both to provide and receive care. More daughters than sons become their parents’ primary caregivers and daughters are more likely to take up more intensive caring activities (Horowitz, 1985; Luppi & Nazio, 2019; Spitze & Logan, 1990; Tennstedt, McKinlay, & Sullivan, 1989).

Time spent on unpaid care work by employed women and related gender gaps differ according to job characteristics, with the burden of unpaid care work being higher for women in non-standard and low-paid jobs. Time spent on unpaid care is highest among women in the second quintile and then decreases as income increases. For employed men, the time devoted to unpaid care work does not change much in relation to their level of earnings. The gender care gap is thus highest among workers in the second quintile and declines for higher income earners.

This pattern is likely to be related to the availability and affordability of care services. EIGE (2019a, p. 91) shows that the use of formal childcare increases with household income, going from 28 % in families in the poorest quartile to 45 % for families in the highest quartile. This reflects two effects. On the one hand, availability of childcare allows parents to participate more in the labour market, which directly leads to higher income. On the other hand, and especially in countries with higher childcare costs, affordability of services is closely dependent on household income levels. For instance, affordability and lack of care services are reported among the main reasons for difficulty in accessing formal LTC ( 19 ) services for people with low income, low education levels, and those

15 Due to the limited number of observations at country level in the EWCS, this analysis is possible only at EU level.

16 EWCS 2015.

17 ibid.

18 Eurofound (2020b) estimates that 44 million, or 12% of the adult population, are frequent informal long-term care giver, i.e. people aged 18 or over who care for one or more disabled or infirm family member, neighbour or friend, of any age, more than twice a week.

19 LTC (long-term care) refers to ‘A range of services and assistance for people who, as a result of mental and/or physical frailty and/or disability over an extended period of time, depend on help with daily living activities and/or are in need of some permanent nursing care’ (European Commission, 2014a, p. 11). These services can be provided in institutions (institutional LTC) or at the home of the recipient (homebased LTC). Household-related care encompasses services that support the dependent person in carrying out activities of daily life (bathing, clothing, eating, shopping, cooking, etc.) or support the informal carer in carrying out these tasks.

belonging to ethnic minorities or having a migrant background (EIGE, 2019b; Spasova et al., 2018). EWCS data shows that women in temporary jobs or with no formal contract spend twice the amount of time in unpaid care every day than women employed in permanent jobs.

The relationship between high gender care gaps and precarious job conditions is twofold. Women in low-paid and precarious jobs spend more time in unpaid care because they lack the economic resources to rely on external services. Yet, women employed in irregular and temporary jobs are often prevented from accessing more stable jobs due to their disproportionate caring responsibilities. Despite their precariousness, irregular and temporary jobs are often the only ones flexible enough to accommodate caring duties (ILO, 2018). It is evident that the enduring burden of unpaid care systematically disadvantages women in the labour market and perpetuates gender inequalities (Chopra, 2015). As the following section illustrates, this is one of the root causes of gender inequalities in pay.

1.2 Gender inequalities in pay

1.2.1 Women resort to part-time employment to reconcile paid labour and care responsibilities

Women across Europe often shift from full-time to part-time employment when they become mothers, as a workfamily life reconciliation strategy (Gregory & Connolly, 2008). This does have a detrimental effect on their earnings, as part-time jobs are heavily polarised into low-paid occupations and sectors (Manning & Petrongolo, 2005). Evidence shows that many women working in low-paid part-time jobs are qualified for and have previously held higher level and better paid jobs, which they opted out of in order to reorganise their working lives around the increased burden of unpaid care (Gregory & Connolly, 2008).

In 2019, 32 % of women were engaged in part- time work in the EU, compared to only 10 % of men ( 20 ). Differences between countries are striking, range from 76 % of women working part-time in the Netherlands to 2 % in Bulgaria (Figure 5). Women working part-time dedicate an hour more to daily care than women employed full-time, while no similar difference is observed for men ( 21 ).

In the EU 29 % of part-time employed women indicated that unpaid care itself was their main reason for working part-time, compared to only 6 % of men citing the same cause ( 22 ). The over-representation of women in parttime jobs has detrimental effects on both the gender earnings’ gap and the pension gap. This is not only because part-time employment reduces actual earnings and future pensions, but also because the hourly pay for part-time work is often lower than for full-time work (Eurostat, 2019), a disparity known as the ‘part-time penalty’ ( 23 ) (Manning & Petrongolo, 2005).

Figure 5: Women and men working part-time as percentage of the total employment, by country (%, 15+, EU-28, 2019)

20 Part-time employment rate is part of the BPfA framework, among indicators to monitor Area F ‘Women and the Economy’(EIGE, 2020b). 21 EWCS data.

22 Eurostat (lfsa_eppga; lfsa_epgar).

23 According to Eurostat [earn_ses14_hftpt], in 2014, the gross hourly pay for part-time workers in the EU-28 was, on average, EUR 13.97, compared to EUR 15.63 for full-time workers.

Source: Eurostat, 2019 [lfsa_eppga].

1.2.2 Gender gaps in pay and earnings in the EU

Gender inequalities in pay can be measured with several indicators, depending on the definition of pay and the available disaggregation by personal and household conditions, type of job and occupation (EIGE, 2019b). This report focuses primarily on the ‘unadjusted gender pay gap’, defined as the difference between the average gross hourly earnings of women and men expressed as a percentage of average gross hourly earnings of men (Eurostat, 2020b). In 2017, the gender pay gap in the EU amounted to 16 %, i.e. women’s average gross hourly earnings were 16 % lower than those of men (Eurostat, 2020a).

The gender gap in overall earnings, however, is much higher, reaching almost 40 % in 2014 ( 24 ) (Eurostat, 2020a). This indicator provides a more comprehensive picture of gender differences in economic conditions because it accounts for the impact of employment rates and working time on the average earnings of all women of working age (whether employed or not) compared to men ( 25 ). The gender gap in overall earnings is higher due to women’s lower employment rates and their working fewer hours compared to men (EIGE, 2019b) ( 26 ). According to Eurostat (2020a) estimates, at the EU level, almost two-thirds (63 %) of the overall gender earnings’ gap was determined by the gender gap in working hours (accounting for 32 % of the gap in overall earnings), and the gender gap in employment (accounting for 30 %). Gender gaps in overall earnings are higher than in hourly earnings in all countries, ranging from 19 % in Latvia to 48 % in the Netherlands ( Figure 6 ).

Figure 6: Gender gaps in the unadjusted gross hourly pay and in overall earnings (%, 15+, by country, EU-28, 2014)

24 Latest data available.

25 The gender overall earnings gap is a synthetic indicator. It takes three combined factors: (1) average hourly earnings, (2) monthly average of the number of hours paid (before any adjustment for part-time work), and (3) employment rate, and measures their impact on the average earnings of all women of working age - whether employed or not employed - compared to men.

26 Eurostat calculates that in 2014 in the EU, women were paid for 14 % fewer hours, on average, than men per month.

Source: Eurostat online database (earn_gr_gpgr2; teqges01).

Note: The latest data available for gender overall earnings gap date back to 2014. The figure presents data on the unadjusted gender pay gap for the same year, in order to allow a direct comparison.

The wide variation between countries of gender gaps in overall earnings reflects gender differences in hourly wages, hours worked and employment rates. In countries with small differences between the gender pay gap and overall earnings (e.g. LV, LT, FI), the gender gap in hourly pay is the main cause of gender gaps in overall earnings. These countries register high full-time employment rates among women, although women are predominantly segregated in lower paid jobs and sectors (Rubery & Koukiadaki, 2016). In countries with greater differences between the two indicators, these are largely due to high gender gaps in working time and/or in employment rates.

The low unadjusted gender pay gap registered in some countries (e.g. EL, HR, IT, MT, PL, RO) reflects a ‘positive selection’ effect, as these countries have among the lowest female employment rates in the EU (see Annex figure 2). The few women in formal employment in these countries usually have better work conditions (higher education, better paid jobs, long-term contracts) than those countries with higher employment rates of women, therefore the unadjusted gender pay gap is narrower. The gender pay gap in overall earnings is instead much higher, as it accounts for the low female employment rate. In fact, Malta, Italy, Romania, Poland and Croatia have, respectively, the first, second, fifth, sixth and seventh highest share of inactive women due to care responsibilities in the EU (see Annex figure 3). Finally, the ‘part-time penalty’ explains the high gender gaps in overall earnings in countries with high part-time employment among women, such as Belgium, Germany, the Netherlands and Austria ( 27 ).

Pay inequalities originate primarily from women’s segregation in the labour market

In addition to women’s lower participation in the labour market – chiefly due to the burden of unpaid care - they also experience discrimination when entering the labour market. This discrimination manifests along two axes:

Vertical segregation: women are systematically concentrated at the bottom of the organisational hierarchy, therefore earn lower wages. The gender pay gaps are especially high among highly educated women relegated to subordinate positions and who struggle to obtain career advancement (a phenomenon

27 Part-time arrangements for women differ substantially between countries. In the Netherlands, 74 % of employed women work part-time and the gender hours gap stands at 28 %, meaning that female employees are paid on average 28 % fewer hours per month than men. Austria and Germany also register a high incidence of part-time work among women (47.6 % and 46.7 %, respectively).

known as the ‘glass ceiling’) (Boll et al., 2016; Christofides, Polycarpou, & Vrachimis, 2013). For example, in the education and healthcare sectors, women are underrepresented at management level despite making up the majority of the workforce (EIGE, 2019b; ILO, 2017a). Vertical segregation is higher in these sectors

than in the overall economy (Eurostat, 2020a).

Horizontal segregation: women are concentrated in certain low-paid sectors. It reflects the traditional division of roles in the domestic sphere, transferred into the job market. As explored in the first section of this chapter, care is stereotypically regarded as ‘women’s work’ and within most EU households the burden of unpaid care falls on women’s shoulders. Due to this cultural expectation, women tend to work in ‘traditionally feminine’ occupations, such as childcare, caring for older people, teaching and nursing (see section 4.1 for further details). These jobs are paid significantly less than sectors dominated by men (e.g. IT, finance), for both cultural reasons (‘care’ has traditionally been regarded as an ‘unproductive’ unpaid activity and remains economically undervalued) and economic reasons (lack of investment in care

infrastructure).

The unadjusted gender pay gap is highest in the financial and insurance sector (35 %) and in manufacturing (31 %), while it is considerably lower in mining and quarrying (1 %) and in transportation and storage (7 %) (Figure 7). Among occupations, the greatest inequalities in pay are registered among craft and trade-related workers (38 %) and managers (29 %), while the lowest are in services and sales occupations (5 %) and in clerical support occupations (10 %), which are predominantly female.

Figure 7: Unadjusted gender pay gap in the EU, by job characteristics (%, 15+, EU-28, 2014)

Source: EIGE calculation based on SES 2014 [earn_ses14_15].

Note: The gender pay gap is computed as the percentage difference between women’s and men’s gross hourly wages over men’s gross hourly wages. SES data refers to employees working in enterprises with 10+ employees, therefore excluding many smaller private home care providers and child care providers. Thus, due to sample selection, SES underestimates the unadjusted gender pay gap in ‘Human health and social work activities’, at least for the (large) long-term care component of these NACE categories.

Previous research by EIGE (2019b) looked at some sub-categories of the occupations presented in Figure 7. It

28

found relatively low gaps in the women-dominated personal care work occupation ( ) (less than 5 %), but also drivers and mobile plant operators ( 29 ) (less than 5 %). This is because the two axes of discrimination often overlap: women are concentrated in certain low-paid jobs (service and care industry), while other high-paying sectors are dominated by men. The few women who enter those sectors are stuck at the bottom of the hierarchy and thus earn significantly less than their male colleagues.

1.3 Linkages between gender care gaps and gender pay gaps

As illustrated in sections 1.1 and 1.2, the uneven sharing of care among women and men is the root cause of inequalities in pay. This section provides further statistical evidence of this link.

1.3.1 Higher gender care gaps among the employed are associated with higher gender inequalities in pay

Evidence shows that countries with a low gender gap in time spent by employees in direct care (care for children, grandchildren, older people, people with disabilities) also tend to have a lower unadjusted gender pay gap (e.g. BE, HR, IT, LU, MT, PL, RO) (Figure 8) ( 30 ). In countries such as Czechia or Austria, with high gender inequalities in time spent in care activities instead, the unadjusted gender pay gap is also high. Slovakia is the only country with a negative gender gap in direct care.

Figure 8: Correlation between unadjusted gender pay gap and gender gap in time spent in direct care among employees

(15+, EU-28, 2014, 2015)

Source: EIGE elaboration of Eurostat online database ([earn_gr_gpgr2]; [earn_ses14_16]) and EWCS 2015 microdata.

28 A sub-group of the broader ‘Service and sales’ occupation.

29 A sub-group of the broader ‘Plant and machine operators and assemblers’.

30 Results show a moderate cross-country correlation (Pearson’s r = 0.36) between inequalities in the daily time dedicated to caring for

children, grandchildren, elderly people and people with disabilities by employees (EWCS, 2015) and the unadjusted gender pay gap (SES, 2014). For further details see Annex (section d). These findings should be interpreted with caution, as the correlation analysis does not investigate causal links between the two variables.

Note: Pearson’s r = 0.36. Unadjusted gender pay gap: difference between average gross hourly earnings of female and male employees as a percentage of male gross earnings (SES 2014). Gender care gaps are calculated for employees as the difference between the mean time spent every day on unpaid care by women and men involved in everyday care, as a percentage of the mean time spent by employed men (EWCS 2015).

Previous EIGE research shows that families’ net monthly earnings are strongly affected by the sharing of care responsibilities. The gap between women’s and men’s earnings is higher among couples with children compared to couples and single people without children (EIGE, 2019b). This is consistent with the body of literature arguing that having children is associated with a ‘motherhood penalty’ and a ‘fatherhood premium’ in earnings, reflecting increasing inequalities in care (i.e. women’s higher involvement in unpaid care and men’s increased participation in the labour market) (Kellokumpu, 2007; Lundberg & Rose, 2000; Meurs, Pailhé, & Ponthieux, 2010; Trappe & Rosenfeld, 2000). The lowest gender gap in net monthly earnings is observed among the youngest generations without children, and thus with fewer caring responsibilities (EIGE, 2019b).

1.3.2 Care-related responsibilities have a notable impact on pay inequalities

A multivariate regression analysis ( 31 ) ( Figure 9 ) shows that having young children (0-6 years old) in the household is positively associated with men’s income, compared to not having young children, while no significant association appears with women’s income. Unpaid care work affects women’s and men’s pay differently, possibly reflecting career breaks, employer discrimination or other factors not directly captured in the analysis. On the other hand, caring for adults is negatively associated with women’s income. Women providing home-based LTC for more than 20 hours a week ( 32 ) earn 2.9 % less on an hourly basis than those with similar personal and job-related characteristics but who do not provide home care.

The use of childcare services shows a positive association with both women’s and men’s income, with a greater impact on women’s. Women with children under 12 using childcare services at least 14 hours a week ( 33 ) are estimated to earn +4.8 % more on an hourly basis, compared to women that do not outsource childcare. The estimated difference for men is +2.6 %.

Figure 9: Estimated effect of direct care on women’s and men’s gross hourly income in the EU (%, 16+, EU-28, 2016)

31 EU-SILC 2016 cross-sectional microdata is used to explore the linkages between gender inequalities in unpaid care work and gender

inequalities in pay (for employees aged 16+). The analysis closely followed the methodological approach used by Boll et al. (2016). Near cash income was used as a measure of ‘pay’. It includes wages and salaries paid by the main and any secondary or casual jobs, as well as supplementary payments, commissions and bonus payments. The gender pay gap is measured as the logarithm of gross hourly income. Unusually, this work considers in the model specification some variables capturing the participation of women and men in unpaid care work, especially in relation to childcare tasks (see Table 4 in the Annex). The main limitation of the model, however, is that it does not include some aspects (e.g. career breaks) that could strongly impact the results. For more details on the regression analysis see Annex (section e).

32 Home care aims to make it possible for people to remain at home rather than use residential LTC. Home care may include healthcare and/or life assistance.

33 The median value of the distribution of hours of childcare externalisation is about 14 for those households with at least one child up to 12 years old and which externalise at least one hour per week. The hours of externalisation are calculated as the average hours of all children in the household using childcare services (centre-based services; day care centre; professional childminder; relatives).

Source: EIGE calculation on EU-SILC 2016.

Note: *differences in coefficients are statistically significant at p<0.05 with respect to having children and childcare. Selected coefficient of gender wage regressions, controlling for: age; country of birth; health status; education level; married; if married (spouse’s income; employment status; education level); temporary work; part-time work; occupation; sector; supervisory position; firm size; country.

These results should be interpreted with caution, however, as they only reflect the impact of the variables included in the model (see Annex, section e ) and suffer from the limitations of the dataset. More specifically, data availability means that the model does not include other key factors that could significantly affect the results of the analysis, such as career interruption and working life duration. While the analysis often looks at inequalities in care in terms of their effects on inequalities in pay, the causality may well be (at least to some degree) in the opposite direction, e.g. higher income can enable a higher use of childcare services, or lower income can lead to higher participation in unpaid adult care. Caution should be used in determining causal relationships – although the analysis points to a robust link between inequalities in unpaid care and pay, it is difficult to say whether inequalities in care cause pay gaps or the reverse.

1.3.3 Horizontal segregation and part-time work are the main determinants of the gender pay gap

Aggregate cross-country estimation ( 34 ) shows a 16 % gender pay gap among employees in the EU. The Oxaca Binder decomposition was applied to investigate the personal and job characteristics captured by the regression that underpin the gender pay gap, and to what extent. This technique is part of the BPfA indicators’ framework and is used to monitor gender pay gap under Area F ‘Women and the Economy’ (EIGE, 2020b). Analysis shows that women earn 6.5 % less than men due to their characteristics in the labour market, which are less remunerative (6.5 % out of 16 % is termed the ‘explained’ gender pay gap). Figure 10 lists these characteristics, including the direction of their effect on the gender pay gap. When a characteristic is attributed a positive coefficient, on average the difference between female and male workers is in favour of men. Conversely, a negative coefficient refers to features that are in favour of women.

The remaining 9 % (out of 16 %) of the gender pay gap is attributed to both unobserved workers’ characteristics not captured by the model and to discrimination (the ‘unexplained’ part). For instance, if the explained part of the gap shows that women work more often in lower paid occupations than men, the unexplained part reflects that

34 Based on EU-SILC 2016 cross-sectional microdata.

women earn less than men in the same occupation, either due to discrimination or some other variables not captured by the model. Unobserved characteristics might be negotiating skills, institutional setting and work experience (i.e. duration of working life).

Figure 10: Decomposition of the explained gender pay gap (%, 16+, EU-28, 2016)

Source: EIGE calculations on EU-SILC 2016.

At EU level, the explained part of the gender pay gap (6.5 %) is driven by four explanatory factors ( 35 ): employment sector (4 %), part-time work (2.5), firm size (1.5 %) and supervisory position (0.9 %). Employment sector refers to the horizontal segregation by gender across sectors and explains a major proportion of the gender gap in almost all Member States analysed (i.e. women are overrepresented in sectors with average lower wages, such as education). It appears among the four main determinants of the gender pay gap in 25 Member States (Figure 11). In addition, women work more often than men in part-time and temporary jobs, which are associated with lower hourly pay (‘part-time penalty’). These results are consistent with the empirical literature on the decomposition of the gender pay gap in the EU (Boll et al., 2016; European Commission, 2018c).

Firm size is another main determinant of the gender pay gap in 20 Member States and constitutes 1.5 % of the explained gap. This is because women are overrepresented in small firms, implying that the wage bonuses associated with large firms operate in favour of men. Larger companies are also more likely to have better diversity strategies, as well as pay transparency initiatives that benefit employees. Finally, another key determinant is women’s underrepresentation in supervisory positions (+ 0.9 %), also known as vertical segregation, which is a major factor in 16 Member States ( Figure 11 ).

It is no surprise that childcare and adult care are not among the main determinants of the explained gender pay gap (see Figure 10 ). In fact, in the decomposition model, childcare is measured with a proxy variable that records

35 The results presented in Figure 10 only cover individual characteristics. The regression model also included some characteristics of

spouses (income and employment status), but results are highly heterogeneous for women and men (coefficients have different signs), which makes them hard to interpret within the Oaxaca-Blinder decomposition. There is value in keeping them as control variables in the regressions but their interpretation is not included in this report.

the presence of children under 12 years old in the household. It is unlikely that the proportion of women and men living with children under 12 differs significantly, since the majority of households with children are composed of two parents (although lone parents are an important exception). This makes large differences in the pay gap unlikely to be due to different proportions of women and men living with children under 12. Instead, the gender pay gap seems to be influenced by the different pay implications of using childcare for women and men (see section 1.3.2).

Figure 11: The four major gender pay gap determinants across the Member States (16+, EU-28, 2016)

Source: EIGE calculations on EU-SILC 2016.

Note: bars indicate the number of Member States in which these characteristics are among the four main determinants of the gender pay gap.

The analysis shows that the unequal division of care tasks in the household has a direct effect on characteristics underlying gender inequalities in pay. For example, care inequalities affect women’s and men’s income, as they operate by sorting women into low-paid sectors and low-paid jobs, e.g. part-time and temporary jobs.

Chapter 2: Are policies promoting greater equality?

The past four decades have seen a decline in the prominence of the male breadwinner model, in which women were assumed to be available and capable of providing unpaid housework and care to children, older and sick family members while men were primarily occupied with paid work. Combined with the relative decrease of men’s earnings as the main source of family income and pressure from the feminist movement for women’s greater economic independence and access to paid work, this family model gave way to more heterogenous division of paid and unpaid work (Ciccia & Bleijenbergh, 2014, p. 55).This evolution has created pressure for public policies and services to adapt and better cater to the needs of a broader range of family circumstances. Member States have reacted differently, according to a host of factors such as labour market structures, social and political systems, and demographic circumstances. Understanding how social policies affect households’ decisions and behaviours in terms of division of care work between women and men is central to continued progress towards gender equality. Alongside the defamilisation grid of analysis, policy interventions can also support households to develop internal solutions to the tensions between care and paid work, allowing family members to re-evaluate the time dedicated to paid work and distribute care tasks more equally.

Policy interventions can support the provision of ‘money, time off and services’ (Bettio & Plantenga, 2008; Gornick & Meyers, 2004; Lewis, 2006). The following section will first analyse policy options for promoting equal sharing of care by supporting families’ access to time off from paid work, then analyse policy options in relation to service provision and financial support. Lewis and Giullari (2005) argued that greater equality at home involves not only ‘rebalancing of paid work between men and women, but a complicated rebalancing of unpaid work between the market, state, men and women’ . Where relevant, examples of policies implemented in specific Member States can be found in Appendix: Policy boxes.

2.1 Policies promoting a fairer distribution of care within households

Public action can affect gender norms in several ways, including through education, media and institutional mechanisms. However, family policy is the main avenue for government to affect gender relations most visibly. Two such policy tools are used by governments to influence sharing of unpaid care within families: statutory leave policies for working parents and other workers with care responsibilities, and (to a lesser extent) FWAs. Although limited by targeting solely people in employment, they are nevertheless important levers in promoting fairer distribution of care within families, due to their potentially transformative effects on women’s and men’s life courses, parenting practices, and gender relations.

2.1.1 Flexible working arrangements

Flexible working arrangements constitute an important element of work-life balance. They include flexitime (flexible start and end times), job-sharing, telecommuting/working from home and part-time work (Russell, O'Connell, & McGinnity, 2009; Winder, 2009), as well as “…time banking or working time accounts and annualised hours” (Eurofound, 2013, p. 13). They can mitigate the negative impact of care responsibilities on employment, notably among women (Chung & Van der Horst, 2018), allowing them to remain in human capital-intensive jobs in times of high family demand.

The WLB Directive calls on governments to grant access to flexible working arrangements to all workers with care responsibilities and parents of children up to eight years old. This is seen as a way to ease tensions inherent in combining paid work with caring responsibilities all through the life course. In line with the European Pillar of Social Rights, it aims to promote women’s participation in the labour market and men’s greater engagement in caring ( 36 ).

As seen in section 1.21, part-time work is used far more by women than by men, especially to meet family responsibilities. As EIGE (2019a) highlights, men tend to have greater flexibility in setting their working times than women due to them being more likely to work in the private sector and in managerial positions. Data from EWCS

36 One of the policy measures included in the WLB Directive refers to ‘encouraging a gender-balanced use of family-related leave and flexible working arrangements’.

show that flexibility is far from being the norm, with over half of workers in the EU (57 % of women and 54 % of men) having working time arrangements set by employers with no possibility for change.

Research undertaken in 27 EU Member States showed that workers in female-dominated sectors, such as education or care work, were half as likely to access flexitime than workers in male-dominated or gender equal sectors (Chung, 2018). Despite this greater access, the uptake of FWAs by men is hindered by gender norms attributing reconciliation efforts to women (Laundon & Williams, 2018). If the expectations for men to be involved fathers have increased within the family, research suggests that the workplace still views fathers as - largely - ‘invisible and stigmatised’ and their caring responsibilities remain overlooked and silenced (Ewald, Gilbert, & Huppatz, 2020).

Different types of flexible working arrangements have various effects on work-life balance of workers (Winder, 2009). For example, telework can both decrease and increase work-life conflict (Eurofound and International Labour Office, 2017; Russell et al., 2009). Russell et al. (2009) found that part-time work and job sharing reduce work-life conflict, particularly for parents, but usually offer lower wages on average and lead to limited social protection, including pension entitlements and other social benefits (Spasova, Bouget, Ghailani, & Vanhercke, 2017), contributing significantly to the gender pension gap (EIGE, 2015). Research from Germany (Lott & Eulgem, 2019) has found that the use of flexibility at work does not always enhance their contribution to childcare. The authors found that men working flexibly spend less time on childcare than those doing office hours, while home workers spend the same amount of time on childcare as their office-based colleagues. This links to the fact that men use - and are expected to use - flexible working arrangements for performance-enhancing purposes. They often increase their work intensity or working hours and receive additional rewards through income premiums (Lott & Chung, 2016). The increased workload can then aggravate work–family conflicts. In contrast, women often work flexibly to meet increased family responsibilities, which do not lead to any financial rewards (Chung & Van der Lippe, 2018). Thus ‘work flexibility [can] help make job and family more compatible, but it can simultaneously cement the classic role divisions between women and men, or even make them stronger’ argues Lott (in (Broom, 2019).

The COVID-19 pandemic has led to a dramatic – although perhaps temporary - shift to telework for a significant share of the EU working population. Preliminary data shows that among 18-34 year olds, more women than men started teleworking during the pandemic (50 % and 37 %, respectively), which could reflect women taking on a disproportionate share of childcare and education while maintaining their paid work (Eurofound, 2020a).

An additional limitation of the use of FWAs as a gender equality tool lies in the fact that, for women, transitioning from part-time to full-time work is particularly challenging. As shown by EIGE (2019a), despite the pool of men working part-time being considerably smaller, their opportunities for moving to full-time jobs are much higher than those of their female peers. Over the 2017-2018 period, 59 % of men working part-time maintained their status, compared to 76 % of women. Consequently, 26 % of men and only 13 % of women in part-time employment moved into full-time jobs ( 37 ). In addition to national labour market circumstances, research identifies

37 Source: Eurostat [ilc_lvhl30].

parenthood as a major constraint on the ability of part-time workers to move into full-time jobs, especially in countries with limited or unaffordable childcare provision (Gash, 2008; Kelle, Simonson, & Gordo, 2017). Similarly, Dubois (2019) highlights that older workers having reduced their hours to care for an elderly partner or relative often find it difficult to reintegrate full-time employment once their care responsibilities cease or decrease.

2.1.2 Statutory leave policies

Working parents across Member States are entitled to a range of types of leave, the most common being maternity leave, paternity leave, parental leave and leave to care for children who are ill. Additionally, most countries provide carers’ leave for those caring for older people or adults with disabilities. All care-related leave policies allow parents and other carers to provide care at home without losing their jobs or income.

Member States’ leave policies for parents vary considerably in terms of types of leave, entitlements, duration, flexibility and payment (Koslowski, Blum, Dobrotic, Moss, & Macht, 2019) and their effects on work-family conflicts are not always easy to discern (Notten, Grunow, & Verbakel, 2017). The variation means that leave policies create different conditions and opportunities for parents to organise care and paid work, conditions that generate different effects on care patterns. Depending on their design and other sociocultural factors, the leave policies in different countries can either i) promote greater fairness in the division of unpaid care, ii) emphasise parental choice regarding the division of leave between women and men; or iii) emphasise maternal home care (Wall, 2007). For instance, most Eastern European countries began with mother-centred leave systems and have gradually moved towards more gender-equal ones (Dobrotić & Stropnik, 2020).

While maternity leave is mostly understood as a health-and-welfare measure linked to pregnancy, childbirth and the first months of motherhood, the introduction of paternity and parental leaves reflect calls for greater gender equality in the workforce and a more equal share of childcare responsibilities within the household (Salmi & Lammi-Taskula, 2011; Strang & Broeks, 2017). The movement towards the dual earner/dual carer model has been judged to be incomplete, as women have moved strongly into the labour market while men have not invested in the home sphere in equal measure. Gender equality requires familising men to a greater extent (Esping-Andersen, 2009) and it is expected that increasing fathers’ involvement in childcare would advance gender equality in the labour market (Connell, 2003; Morgan, 2009) and support the emergence of a dual earner/dual carer family model, where women and men engage equally in paid work and care (Gornick & Meyers, 2004).

Maternity leave

Maternity leave offers job protection for mothers before and after the birth and maternity leave provisions are established in all EU Member States. It is most often paid at high replacement rates (except IE, SK, UK) and all or part of it is mandatory. The maternity rights set out in the 1992 Pregnant Workers Directive sets the minimum period for maternity leave at 14 weeks, with two weeks’ compulsory leave before and/or after confinement and an adequate allowance subject to national legislation (Council of the European Union, 1992). Duration of maternity leaves range from 14 weeks in Germany to 58 weeks in Bulgaria (European Parliament, 2019; Koslowski et al., 2019).

Moderate duration of leave for women is thought to have a substantial positive effect on their employment outcomes and working hours, whereas very short and very long leaves are associated with reduced female labour market participation (Pettit and Hook, 2005; Genre et al., 2010, Misra et al., 2011; Akgunduz and Plantenga, 2013; Olivetti and Petrongolo, 2017). There is no consensus in the literature on the optimal duration, but less than four months would generally be considered short, from 5-12 months as moderate, 12 months to 2 years as long, and more than two years as very long. Long or very long maternity leaves are considered to contribute to an unbalanced division of care between mothers and fathers during the first year(s) of the child’s life. In some countries, parts of the maternity leave can be transferred to fathers (BG, CZ, ES, HR, UK) without exceptional circumstances (such as serious illness), thus providing opportunities for equalising care (Koslowski et al., 2019). Other countries have opted to move away from traditional maternity leave and developed what is known as the ‘Icelandic model’, characterised by one parental leave scheme with periods designated for ‘mothers only’ and for ‘fathers only’ ( 38 ), creating a situation where mothers and fathers have equal amounts of leave. This trend can be seen in Sweden and Portugal (Koslowski et al., 2019). In Portugal, parental leave is only available to each parent (either 120 days paid at 100 % or 150 days at 80 % of previous income). An extra 30 days are available if parents share the leave period (European Parliament, 2019).

Paternity leave

Paternity leave is typically a short period of leave for the father immediately following childbirth, intended for fathers to support the mother’s recovery from childbirth, care for the newborn and older children, attend to the registration of the birth and other family-related responsibilities (ILO, 2014). While maternity leave policies prescribe a mandatory period of leave across all countries except Latvia and Lithuania (EPRS, 2019), paternity leave policies are usually voluntary. Indeed, only three countries (BE, IT, PT) established a mandatory period ( 39 ) of paternity leave, with three days in Belgium, five in Italy and 15 days in Portugal (

40 ).

Figure 12: Total length of statutory mandatory and voluntary paternity leave in the EU (number of days, EU-28, 2019)

Source: EIGE elaboration of MISSOC 2019.

Note: The line indicates the minimum working days’ leave stated in the WLB Directive adopted by the Council of European Union (2019).

38 The Icelandic model consists of nine months’ parental leave, three months of which are reserved for the mother and three for the father, and three additional months to be divided between the parents as they choose. In terms of recovery from childbirth, the leave makes it mandatory for women to take two weeks’ leave after birth, which can be extended in case of complications (Koslowski et al., 2019).

39 While the respect of mandatory maternal leave is controlled by the State, this is not usually the case for paternity leave, where no sanctions are in place for unused leave.

40 In all three cases, mandatory paternity leave is paid at 100 % of the most recent salary.

Prior to the adoption of the WLB Directive, there were no minimum standards for paternity leave at EU level. The majority of Member States already comply with the requirement of 10 working days set out in the Directive. Eighteen countries have paternity leave of 10 or more working days, while seven have paternity leave shorter than 10 working days (CZ, EL, IT, HU, MT, NL, RO) and three (DE, HR, SK) have no arrangements for statutory paternity leave (Figure 12). In the case of Germany, many fathers use parental leave entitlements similarly to paternity leave (Reimer, Erler, & Blum, 2019).

In the EU, 25 Member States provide paternity leave with income-related benefits, 14 of which have full compensation of previous income. Overall, in 23 Member States, paternity leave is considered well-paid (compensation above 66 % of previous wage). However, a ceiling may be set on the income-related payment of leave (BE, BG, CZ, DK, EE, ES, FR, LT, SI, SE). Information on the uptake of paternity leave is lacking and not comparable across countries (Eurofound, 2019). In countries where information is available, the levels of uptake tend to vary considerably. In Estonia, for example, 53 % of new fathers took paternity leave (2017), 69 % in Finland (2015), 33 % in Bulgaria (2018) and 67 % in Spain (2018) (Koslowski et al., 2019).

A study in Spain showed that increasing the duration of paternity leave with 100 % of wage replacement from two weeks to four/five weeks acted as a political and social legitimisation of the leave, increasing uptake to 80 %, with increases also evident among some groups of fathers previously reluctant to take time off from paid work (selfemployed, workers in temporary or low-skilled occupations) (Jurado-Guerrero & Muñoz-Comet, 2020). The authors highlighted that uptake of paternity leave has been high since the introduction of the provision and remained high during the economic recession (similar to Sweden in the 1990s), which they attributed to its nontransferable dimension and high payment levels (Jurado-Guerrero & Muñoz-Comet, 2020).

Overall, the effect of paternity leave on actual division of care responsibilities within the family may be limited, due to its duration and its design, which places fathers in a supporting (albeit important) role during maternity leave. As such, paternity leave does little to shift the responsibility of care or question the role of mothers as primary caregivers (Lammi-Taskula, 2008; Nyberg & Haataja, 2006).

Parental leave

Parental leave is available to both parents. Although parental leave policies are often designed to be genderneutral and offer benefits to both parents, this form of leave often perpetuates gendered choices and gender inequalities (Morgan, 2009). As parental leave entitlements are often transferable between parents, gender norms frequently influence parents’ choices and result in situations where women take the lion’s share of the leave (Morel, 2007; Morgan, 2009). Although reliable comparable data is scarce, the overall take-up of parental leave by men is estimated to be very low (Blum, Koslowski, Macht, & Moss, 2018; Karu & Tremblay, 2018). If the gendered pattern of care is to be changed and fathers familised, higher take-up of parental leave by men is crucial. Alongside sociocultural factors (gender roles, employer resistance), uptake of parental leave by fathers is associated with the way the leave is designed. Duvander et al. (2019) provide an overview of the aspects of parental leave policies that have contributed to increased uptake by fathers in Nordic countries (DK, FI, SE, NO, IS). The introduction of quotas (a non-transferable element of leave that is lost if not taken by the father) and level of compensation were found to be the most instrumental. The study also pointed to flexibility in how the leave can be taken (for eg. as a parttime entitlement or within a longer timespan) as similarly supportive of uptake of parental leave among fathers.

Systems of parental leave differ significantly between Member States, especially in terms of eligibility, payment, duration, flexibility in usage, age of the child to be cared for, and transferability between parents. As shown in Figure 13, the length of paid parental leave ranges from non-existent to 160 weeks (HU, SK). Eight Member States currently fall short of the minimum of four months (around 17 weeks) set for paid parental leave by the WLB Directive (CZ, IE, EL, ES, CY, MT, NL, UK).

Figure 13: Total length of paid and unpaid parental leave in the EU (number of weeks, EU-28 2019)

Source: EIGE elaboration of Eurofound (2019) and Annual Review 2019 – International Network on Leave Policies and Research.

Note: The line indicates the minimum paid weeks’ parental leave stated in the WLB Directive adopted by the Council of the European Union (2019).

Evidence shows that fathers taking up parental leave can lead to a more equal division of care and household tasks, with both immediate effects (Schober & Zoch, 2019) and longer-term effects (Kotsadam & Finseraas, 2011). Fathers who take-up parental leave become more involved in childcare and there may be immediate effect on sharing childcare and housework, and sharing of care for sick children. Evertsson (2014) emphasises the importance of parental leave, which can affect the gender gap in unpaid care, depending on its length. More specifically, where fathers take longer parental leave, the gender gap in childcare decreases once both parents are back at work (Evertsson, 2014; Evertsson, Boye, & Erman, 2018; Neilson & Stanfors, 2014). In these situations, fathers have more time to experience childcare and become familiar with care needs, while children are accustomed to turning to either parent when in need, thus fostering shared care.

Scholars have warned against overestimating the equality impact of parental leave (Kvande & Brandth, 2017; Leira, 2002; Moss & Deven, 1999). Studies have not found the expected impact in care-related behaviours of fathers who have been on parental leave (Ekberg, Eriksson, & Friebel, 2005; Kluve & Tamm, 2009). Karu (2012) argued that the limited (or no) impact may be partially due to the fact that not all fathers who take up leave become actual or primary carers of their children. From this perspective, flexible parental leave designs, while conducive to greater uptake, also increase the likelihood of parents being on parental leave together which can deter parents from actually sharing childcare and lead to them resorting to a gendered set-up where mothers are the primary carers (Duvander et al., 2019).

In addition to length, compensation is another key dimension of parental leave (Duvander et al., 2019; Duvander & Johansson, 2012). As with other forms of leave, 14 Member States compensate income during parental leave, calculated as a percentage of previous income, where ceilings may apply (CZ, DK, DE, EE, LT, HU, SI, SE). The maximum benefit was capped as low as 34 % (CZ) or 48 % (DK) of national average wage in 2014 (Karu & Tremblay, 2018), so that compensation level of 100 % applies only to those with low incomes. Eight Member States pay a flat rate during parental leave ( 41 ). However, in many countries with well- paid parental leave, the share of fathers using the leave remains low (Karu & Tremblay, 2018).

Ineligibility for parental leave

Parental leave policies are only effective insofar as they are accessible to prospective parents, which makes eligibility rules an essential aspect. EIGE estimates that 10 % of women and 12 % of men in employment are not eligible to parental leave in the EU (EIGE, 2020e). Currently, no Member States in the EU-28 offer universal access to parental leave (EIGE, Forthcoming). Only Croatia, Finland and Sweden stand out as having broad-ranging access rules ( 42 ). In 2017, EIGE (2020e) found that different characteristics could make prospective parents ineligible for parental leave: being a refugee or asylum seeker (19 Member States), insufficient work history (16), self-employed status (10), being in a same-sex couple (11), residency status (11) and citizenship (2). Adoptive parents and lone parents are eligible for parental leave across the EU-28 (EIGE, 2020e).

Ineligibility can inhibit family formation, as potential parents anticipate not benefitting from any leave entitlement. It can also hinder employment of parents (full or part-time) if they have no alternative to parental leave. Countries with lower ineligibility for parental leave for both women and men also tend to have smaller gender gaps in unpaid care (e.g. BE, FR, LV, LT, HU, RO) (Figure 14). Denmark stands out as having a particularly low ineligibility for parental leave and gender care gap, whereas Belgium and France both have a lower gender care gap despite quite high parental leave ineligibility. This could suggest a bigger role of other factors, such as prevalence of residential care. In Member States with overall lower ineligibility rates, women’s ineligibility is higher (DK, FR, LV, LT, HU, PT, UK). In countries, where overall ineligibility rates are higher (e.g. >20), men’s ineligibility rates are higher. In countries, with low overall ineligibility, further attention should be paid to barriers to women’s capacity to use parental leave. In the Member States with higher ineligibility rates, the high ineligibility for all, especially for men, should be on the agenda for discussion and reform, if the unpaid care gap is to be addressed and gender equality is to progress.

Figure 14: Cross-country comparison of ineligibility rates among the employed and gender gaps in unpaid care (EU-28, 2015- 2017)

41 For eligible employed parents in Estonia, for example, parental leave is compensated proportionally (100 %) to the personal average

earnings, calculated based on employment in the previous calendar year, while eligible parents who were not working during the calendar year before the birth receive a flat-rate of EUR 500. Sweden has mixed compensation, partially income-related and partially flat-rate.

42 Here, access to parental leave is restricted for asylum seekers.

Source: EWCS 2015 and EIGE (2021).

Note: Data for DE, HR, PL, SI, SK, FI, SE not presented due to ineligibility rate being null for employed women and men.

2.2 Policies supporting external solutions to care needs

2.2.1 Service provision

Early childhood education and care

Policies promoting the provision of good-quality formal early childhood education and care (ECEC) services are essential to the realisation of gender equality in employment. More specifically, the absence of gaps between the end of leave provision and the start of subsidised, high-quality ECEC are associated with greater women’s participation in the labour market (OECD, 2018). In most Member States (except HR, IT, LT, RO, SK), parents are entitled to statutory ECEC (EIGE, 2019a). However, evidence suggests that despite such entitlement, care services are not always easily available or sufficient, e.g. in Estonia, Germany and Hungary (Blum et al., 2018). Few Member States (DK, DE, MT, SI, FI, SE) have publicly subsidised childcare that begins as paid parental leave ends (EIGE, 2019a). The highest care gaps are found in Austria (36 months) and the Netherlands (33.2 months). This highlights a lack of coordination between two policy areas (Blum et al., 2018).

Analysis of unmet need for childcare services highlights persistent gaps in coverage. About 14 % of households in the EU report unmet needs for formal childcare services, a phenomenon affecting lone mothers disproportionately (EIGE, 2019a). In half of the cases, the main reason for not making (greater) use of formal childcare services is the cost, suggesting that ECEC services are unaffordable for many families ( 43 ).

In 2002, the European Council set objectives for the availability of childcare facilities through two targets: 90 % of children from age three until mandatory school age and 33 % of children under three to be achieved by 2010. More recently, the European Pillar of Social Rights and its New Start initiative emphasised children’s right to affordable, quality educational and childcare services (European Commission, 2017a). The EU also reaffirmed the need for children from marginalised socioeconomic backgrounds to benefit from specific remedial action to

43 According to EU-SILC 2016 data, 50 % of European households with at least one child under 12 and reporting unmet childcare needs identify cost as the main reason for not making greater use of formal childcare services, while 12 % of households cite unavailability of places, 8 % opening hours, 5 % distance, 2 % unsatisfactory quality of services, and 23 % other reasons. Source: Eurostat [ilc_ats04].

further their development and social inclusion. While these high-level commitments have been translated into concrete progress in recent decades, childcare service provision remains very inconsistent between countries (see section 3.2.1), with several falling short of the Barcelona targets, especially for children under three.

While strong political will is essential to the availability of ECEC services, other important dimensions determine the actual use of services: i) Quality of the childcare services in terms of care workers’ qualifications and working conditions, staff-to-child ratio, areas and spaces; ii) Accessibility, including opening hours, territorial coverage, inclusivity of children with health issues/disabilities, availability of connections and transport that does not require parents to sacrifice work commitments; iii) Affordability, in terms of costs for the parents and sustainability of the service within the household economy. Governments can influence all three dimensions through legislation, training to improve care workers’ skills and financial incentives to care providers. These dimensions of childcare services are not monitored at EU level.

In the context of preparing the WLB Directive, the question was raised as to the need to expand the Barcelona targets to include some of the qualitative aspects mentioned above (European Commission, 2015). This revision also features as a priority in the EU Gender Equality Strategy 2020-2025 (European Commission, 2020c). In May 2019, EU education ministers adopted a Council Recommendation on high-quality early childhood education and care systems (European Commission, 2019a). The European Commission’s proposal for a Child Guarantee in 2021 will seek to address some of the most significant barriers preventing children from accessing early childhood education services.

While the WLB Directive refers to ‘making better use of European funds to improve provision of formal care services (childcare, out-of-school care and long-term care)’ and the Gender Equality Strategy and previously the Strategic Framework for Gender Equality encouraged Member States to use EU funds to improve the provision of care services, EIGE’s evidence shows that only a minimal fraction of EU funds are used for that purpose ( 44 ). Between 2014 and 2020, approximately 1.25 billion (0.6 % of the total ERDF budget) was planned for ‘investment in childcare infrastructure’ (EIGE, 2020a). EIGE also found a lack of policy coherence and consistent action on highlevel objectives in the way the funds operate, with insufficient numbers of programmes that integrate EU and national WLB policy objectives (

45 ). Even in the context of marginalisation of care services’ interventions, there is a disproportionate focus on childcare, at the cost of other forms of care services and measures to meet the needs of carers (EIGE, 2020a).

Long-term care

Ageing is becoming a demographic reality in the EU. The old age dependency ratio (OADR) – the number of people aged 65 and over per 100 people of working age (15–64) – has increased by 5 percentage points (p.p.) in 10 years, reaching 30.5 in 2018. It is expected to reach 50 by 2050 ( 46 ). One in four people in the EU is affected by a

44 EIGE conducted a gender assessment of ESI Funds programmes in 11 Member States. EIGE also conducted four country case studies (CZ, DE, EE, ES) to get a more in-depth understanding of the use of the ESF and the ERDF to promote WLB in the EU.

45 EIGE conducted a gender assessment of ESI Funds programmes in 11 Member States. EIGE also conducted four country case studies (CZ, DE, EE, ES) to get a more in-depth understanding of the use of the ESF and the ERDF to promote WLB in the EU.

46 Provisional data, Eurostat [tps00198] and [tps00200] extracted on 10 February 2020.

long-term disability, women (27 %) more often than men (22 %) ( 47 ), and about 5 % of families in the EU are affected by disabilities in their children ( 48 ). EU institutions and Member States are under pressure to find sustainable and affordable models to meet this ever-increasing demand for LTC services (EIGE, 2020d).

Active and healthy ageing ( 49 ), deinstitutionalisation and prioritisation of formal home-based LTC are policy priorities for EU institutions and across the EU (EEG, 2012, 2014; EIGE, 2020d). The European Disability Strategy 2010-2020 encourages the transition from institutional to formal home-based services and, in 2017, two-thirds of EU Member States had either adopted a dedicated strategy on deinstitutionalisation or included measures for deinstitutionalisation in a broader disability strategy (FRA, 2018).

If the European Pillar of Social Rights has reaffirmed everyone’s right to accessible, good-quality and affordable formal LTC services – particularly home care and community-based services − the need to develop LTC service provision has yet to lead to the adoption of any EU-wide targets similar to the Barcelona objectives for ECEC. In its Gender Equality Strategy 2020-2025, the European Commission announced that it will launch a consultation on a Green Paper on Ageing, with a focus on LTC, pensions and active ageing (European Commission, 2020c).

Statistical data on unmet need for LTC highlights insufficient coverage of formal LTC services. In the EU, about 29 % of households reported unmet need for professional home care services in 2016, with large differences between countries (from 12 % in Sweden to 86 % in Portugal) (EIGE, 2019a). In most cases, their needs for home care services are not met due to cost (49 %) and unavailability of services (15 %) ( 50 ). LTC in the EU relies heavily on informal care, with evidence showing that the number of informal carers (mostly women) is twice as high as numbers of formal caregivers (European Commission, 2014a).

Policy approaches to LTC often fail to reflect gender concerns. One reason is that LTC cuts across different policy areas, such as social protection and inclusion, or healthcare. Gender mainstreaming across different areas of EU policy, including the implementation of Europe 2020 and the European Semester, is fragmented and lacks a systematic approach. Even where gender equality objectives are included, a cross-cutting gender mainstreaming approach is often insufficient. For instance, while the European Pillar of Social Rights includes a gender-specific principle, it lacks a gender dimension across some of its key principles, such as LTC (EIGE, 2020d). The crosscutting dimension of LTC also inhibits the monitoring of public financing of LTC, with budget allocations fragmented and different government authorities responsible for different strands. This creates substantial difficulties in ascertaining exact figures for spending LTC, or numbers of care recipients receiving LTC services and benefits (European Commission, 2018a). An analysis of the use of EU funds to support WLB found that financing for active ageing programmes, and therefore likely to support autonomous living versus residential living, was

47 Eurostat, Health variables of EU-SILC, 2017, (hlth_silc_06).

48 5 % of families with children had a child or children with disabilities, i.e. some or severe longstanding limitation(s) in usual activities due to health problems, Eurostat, ilc_hch13.

49 The European Commission considers active ageing to be ‘helping people stay in charge of their own lives for as long as possible as they age and, where possible, to contribute to the economy and society’. In 2011, the Commission launched the European Innovation Partnership in Active and Healthy Ageing, which promotes greater autonomy and participation in paid employment of older persons as a way to decrease demand for LTC.

50 EIGE calculation based on Eurostat [ilc_ats15].

limited (EIGE (2020a). For example, an assessment of ESF and ERDF funding for WLB in Czechia, Germany, Estonia and Spain found no evidence of funding for active ageing programmes (EIGE, 2020a).

2.2.1 Cash and tax benefits

Childcare-related cash and tax benefits

Cash benefits are financial resources transferred directly to parents or paid in the form of vouchers (see Box 2 in Appendix: Policy boxes) to contribute to their childcare costs. Direct cash transfers to families are often argued to provide the key advantages of allowing parents to choose their preferred care solution and encouraging childcare providers to meet the needs of parents. It can also encourage competition in the supply of childcare by facilitating public and private actors to compete (see Box 3 in Appendix: Policy boxes).

In addition to cash benefits, several forms of tax benefits and tax credits are offered to families to lighten the costs of childcare. Such tax benefits include tax reductions on evidence of the use of a registered childcare provider, and several forms of tax credits for working parents. Tax benefits differ from cash benefits in the impact that fiscal policy may have on families’ work-related decisions (Immervoll & Barber, 2006; Thévenon, 2011), depending on the policy’s target population and country legislation. From a gender perspective, the unit of taxation – and consequently the beneficiary of the tax reduction – represents a key determinant for the preferable earning profile within the household ( 51 ), influencing the family’s care decisions or needs. Tax benefits can have two different effects on the choices of parents in respect of employment and thus indirectly on the need to externalise childcare. Firstly, family-based taxation systems may create adverse incentives for the second earner (most commonly a woman) to participate in the paid labour market. By contrast, individual taxation can support both parents to enter the labour market and thus may contribute to the formalisation and externalisation of care needs (OECD, 2007). During the past three decades, several countries in the EU have moved towards individual taxation out of a related concern for gender equality. In addition, the tax benefits or tax allowances reducing the costs of using a formal childcare provider represent an incentive for parents to externalise care tasks. The amount of tax benefits related to childcare costs and household net earnings determines whether it is convenient to externalise the care tasks (Immervoll & Barber, 2006).

LTC-related cash and tax benefits

When it comes to LTC for older people or people with disabilities, cash benefits can be divided into three main categories: i) direct payments to older people needing care: ii) personal budgets and consumer-directed employment of care assistants; iii) income support payments to informal care givers (Simonazzi, 2012). While the latter is not related to the externalisation of care tasks, the first two can be used to externalise care needs, perhaps even facilitating ‘informal caregivers’ becoming ‘formal caregivers’ with a regular employment contract (see Box 2.7). Some academics (Le Bihan & Martin, 2012) argue that in the context of cost containment and difficulty in developing public support, the burden of care provision is placed on family members, primarily women. Public measures have become ways to support families in their caring roles, introducing forms of semi-formal care. They can be considered as a form of externalisation, as they recognise the monetary value of unpaid care work provided by people – usually women – within the household, introducing new forms of paid work, defined as

51 Generally speaking, the single-earner model or the dual-earner model (OECD, Family Database).

‘informal care employment’ (Geissler & Pfau-Effinger, 2005). Most schemes providing cash benefits are funded from general taxation, with some Member States using a mix of contributions and taxes. Certain cash benefits are embedded in existing benefit schemes for people with severe disabilities ( 52 ). Others are newly established to address the challenges of an ageing society and rising demands for social and LTC services ( 53 ) (Spasova et al., 2018). Eligibility and the amount of cash benefits usually depend on one or a combination of criteria, including: i) degree of care dependency, ii) level of income, and iii) age of the care-dependent person (Spasova et al., 2018).

Housework-related cash and tax benefits

In addition to personal care, household care (a broad range of activities that contribute to family and individual well-being at home, such as cleaning, home repairs, gardening, etc.) can be provided by a person external to the family. This externalisation is usually carried out according to two different employment models of service provision: i) a direct employment model in which private individuals or households (who became the ‘employer’) directly recruit workers to perform domestic tasks in their home, and ii) employment in service provider organisations, in which workers are employed by an organisation (private or public, for profit or non-profit) that sells those services to households. Different public policy tools have been implemented, primarily to support households to reduce costs (e.g. tax incentives and/or deductions) and, especially when the direct employment model is prevalent, encourage formal employment (and discourage undeclared work), through the use of vouchers or similar tools.

Tax incentives and tax deduction systems were initially introduced in Nordic countries. Finland introduced a tax deduction system for home-based services (within the taxpayer’s own household and also for housework services performed within older relatives’ homes) as early as 1997, with Sweden following suit in 2007 (see Boxes 13 and 14 in Appendix: Policy boxes). Vouchers are a means of payment between in-kind provision of services and cash benefits and can be used in different sectors of activity. Although usually used for direct care services, their application to household services has grown in recent years, following successful experiences in some European countries (see Box 2.14). Vouchers have advantages for both the demand and supply side. They are intended to allow user choice between different types of providers (public or private) or simply a single employee (i.e. a domestic worker) and different types of services or activities. A second advantage is the simplification of the administrative procedures involved in employing someone to outsource housework tasks and to incentivise declared labour.

Packages of measures have greater combined effects than single policies

From a gender perspective, the effects of FWAs, statutory leave policies, service provision and cash/tax benefits on the division of unpaid care depend on how they are designed (eligibility criteria, duration, costs, level of income support, availability and quality, etc.), and how they are combined within specific gender norms (Moss, 2019). Research shows the inclusion of gender equality concerns in social policy is central to promoting a dual earner / dual carer model. More specifically, when it comes to promoting men’s greater engagement in childcare, essential aspects include the non-transferability of leave entitlements and high level income replacement levels (Duvander et al., 2019; Jurado-Guerrero & Muñoz-Comet, 2020). Gender mainstreaming and gender budgeting principles are

52 EE, EL, HR, HU, MK, RO, SK, FI, RS, UK.

53 BE, CZ, DE, ES, FR, CY, LU, MT, NL, AT, FI.

needed at every stage of the policy design and implementation process to ensure coherence and articulation of various policies.

Chapter 3: From equal sharing of care to use of external services: where do families stand?

This chapter looks at two aspects of gender equality in unpaid care work. Firstly, it looks at the trends in gender gaps in the frequency and intensity of informal care work and focuses on the strategies adopted by families to solve the issues of care ‘internally’. To this end, it proposes an analysis of the gendered division of care commonly found in the EU. Secondly, it describes the level of ‘externalisation’ of care work understood as the partial or total transfer of unpaid care activities from the household to paid people and/or services.

3.1 Is equal sharing of care a lived reality for families in the EU?

As the main unit of socialisation of children, the family is an important arena for challenging traditional gender roles and establishing more equal patterns for future generations (Becker, 1981; Farré & Vella, 2013). The arrangements established by couples to carry out the daily activities necessary for the functioning of the household are particularly relevant for gender equality. The literature often refers to these arrangements as the ‘gender contract’ ( 54 ) (McDowell, 2017; Pfau-Effinger, 1994) and refers, for example, to the way partners contribute to the household’s income, participate in the care of children and vulnerable family members, carry out daily household tasks, and whether some of these tasks are externalised. This section seeks to highlight the ways that cohabiting heterosexual couples in the EU organise their everyday care tasks and reviews how gender gaps in unpaid care have progressed in the past 15 years.

3.1.1 Only one-third of families share care equally

Data from the International Social Survey Programme (ISSP) (

55 ) provides information on household arrangements in respect of unpaid care work for 21 Member States. By combining answers related to direct care and household care carried out regularly by the respondent and their partner, four types of household arrangements emerge ( 56 ):

• - 

  Equal sharing of care activities (‘equal sharing’); - The woman is carrying out most care activities (‘woman as main caregiver’); - The man is carrying out most care activities (‘man as main caregiver’); - Most care activities are carried out by a third person (‘externalisation’).

Figure 15 presents the distribution of these four typologies in the 21 Member States for which ISSP had data in 2012. The prevailing gendered division of care tasks across the EU is based on women being the main caregiver in the household. This is the leading pattern in all countries, albeit to different degrees, from 68 % of respondents in

54 The (European Commission, 1998b) defines a gender contract as a ‘set of implicit and explicit rules governing gender relations, and which allocate different work, value, responsibilities and obligations to women and men, and are maintained on three levels: cultural superstructure (the norms and values of society); institutions (family welfare, education and employment systems, etc.); and socialisation processes, notably in the family’.

55 Recurring module ‘Family and Changing Gender Roles’ (ISSP Research Group, 2016).

56 ISSP does not collect information on the sex of the respondent’s partner. Due to this data limitation, the analysis assumes that all respondents are in a heterosexual relationship.

Czechia and Slovakia to 48 % in Sweden. Households where the man is the main caregiver was indicated by 18 % of respondents in Austria, while elsewhere it ranges from 4 % in Slovakia to 10 % in Sweden. Respondents who externalised most care activities represented less than 3 % of respondents. This low share points to the fact that for most adults, the use of external services, if supportive, cannot be expected to cover all household care tasks.

Figure 15: Typologies of the gendered division of care among cohabiting couples (%, 18+, EU-28, 2012)

Source: EIGE elaboration of ISSP 2012 data.

Note: Typologies identified on the basis of the combination of respondent’s sex and the answers to the question ‘In your household, who does the following things ...? - Doing the laundry; care for sick family members; shops for groceries’. Percentages based on respondents cohabiting with their partner (married/long-term relationship). Due to data limitations, all respondents were assumed to be in a heterosexual relationship.

Among the factors that influence equal sharing are employment patterns and individual gender values. Figure 16 illustrates the ways in which employment patterns interact with the distribution of care. Equal sharing of care activities is least prevalent in households where the man is the only one involved in paid work. Conversely, equal sharing of care is more commonly found among couples where the woman is the only or the main breadwinner. However, women are the main caregivers in one-in-two households.

Figure 16: Typologies of gendered division of care among cohabitating couples, by household employment patterns (%, 18+, EU-28, 2012)

Source: EIGE elaboration of ISSP 2012 data.

Notes: Household employment patterns built by combining the respondent’s sex and the answers given to the following questions: ‘Are you currently working for pay, did you work for pay in the past, or have you never been in paid work?’; ‘How many hours, on average, do you usually work for pay in a normal week, including overtime?’; ‘Is your spouse/ partner currently working for pay, did he/she work for pay in the past, or has he/ she never been in paid work?’, ‘How many hours, on average, does your spouse/ partner usually work for pay in a normal week, including overtime?’. Those working more than 37 hours a week are considered full-time workers.

As shown in Figure 17 , attitudes to gender equality affect the division of unpaid care. Respondents expressing traditional attitudes towards gender roles are the least likely to share care activities equally. Conversely, the biggest share is among respondents who support egalitarian gender roles. Regardless of individual values and attitudes, the typology in which women are the main caregivers dominates. This supports research findings suggesting that gender egalitarian principles do not necessarily lead to actual equality in dividing paid and unpaid labour, and that values and behaviours are not always aligned (Dernberger & Pepin, 2020).

Figure 17: Typologies of gendered division of care among cohabitating couples, by attitudes to gender equality (%, 18+, EU- 28, 2012)

Source: EIGE elaboration of ISSP 2012 data.

Note: See Annex (section g) for information on computation of the gender ideologies used in this figure.

3.1.2 Gender gaps in care are narrowing slowly

Between 2000 and 2015, the share of employed women and men engaged daily in childcare and household care declined slightly (Figure 18). This trend is analysed in literature (Bianchi, Milkie, Sayer, & Robinson, 2000; Craig & Mullan, 2011; Geist & Cohen, 2011), with the decline attributed to several factors such as the increased labour force participation of both women and men, increased time pressures, and a fertility drop, leading to smaller families.

Despite this overall decrease, women are still carrying out most daily care activities. The share of employed men carrying out childcare tasks on a daily basis decreased from 40 % in 2000 to 25 % in 2015, while employed women who carry out childcare tasks on a daily basis decreased from 56 % in 2000 to 41 % in 2015. Since 2000, only a small share of employed men (around 5 %) and women (around 10 %) are engaged daily in the care of older members of the family and those with disabilities. However, these results need to be interpreted with caution. While Figure 18 highlights the share of employed women and men active in unpaid care, no information is available on the employment status of their partner. When both partners work full time, economic resources may give access to more varied options to alleviate care needs, including residential or home-based elderly care, thus explaining the decrease in engagement with care. Women belonging to the ‘sandwich generation’ (still in employment and dealing with care needs related to elderly parents and grandchildren) are particularly exposed to the unequal division of care (Burke & Calvano, 2017; Evans et al., 2019; Tur-Sinai, Silverstein, & Lewin-Epstein, 2018). The intensive care demand can decrease their labour force participation (Da Roit, Hoogenboom, & Weicht, 2015) and their situation would not be captured by this data.

Figure 18: Share of employed women and men carrying out daily care activities (%, 15+, EU-28, 2000-2015)

Source: EIGE elaboration of EWCS 2000-2015.

Note: Weighted data. Based on valid cases of EWCS 2000, 2005, 2010, 2015. Trend question: ‘In general, how often are you involved in any of the following activities outside work?’ - Caring for and educating your children, grandchildren; Cooking and housework; Caring for older members of the family and those with disabilities.

Since 2005, the gender gap in time spent on care has continuously narrowed. In 2015, employed women spent 1.3 hours a day more than men on care activities (childcare, LTC, housework) compared to 2.3 hours in 2005.

When looking at direct care (childcare and LTC), some important country differences emerge (Figure 19). Akin to the EU average, the gap narrowed continuously from 2005 to 2015 in one-quarter of Member States. In the second group of Member States, the gap has declined since 2005 but progress has been rather uneven. In the third group, the gap remained unchanged or widened. In Czechia and Estonia, the gap notably widened compared to 2005. In Croatia, Latvia, Lithuania and Sweden, the gap widened slightly or did not change since 2005.

Figure 19: Gender gaps in time dedicated to direct care per day among the employed population (hours per day, 15+, EU-28, 2005-2015)

Source: EIGE elaboration of EWCS 2005-2015.

Note: Weighted data. Based on valid cases of EWCS 2000, 2005, 2010, 2015. Trend question: ‘How many hours per day are you involved in any of the following activities outside work?’ - Caring for and educating your children, grandchildren; Caring for older members of the family and those with disabilities.

The gender gap in time spent on housework overall is similar to the gender gap in direct care (childcare and LTC) (comparing Figure 19 and Figure 20). In 2015, employed women spent on average 42 minutes more than men on housework every day and 42 minutes more on childcare and LTC. In line with direct care, the gender gap in household care has continuously reduced since 2005. Country heterogeneity is lower for household care than for direct care, with gender gaps ranging from -0.5 hours in Slovakia to 1 hour in Malta (Figure 20). This continuous narrowing of the gender gap in household care was observed in 11 Member States, with the largest changes from 2005 to 2015 taking place in Malta and Hungary. No gender gap was actually observed in Hungary in 2015. The narrowing of the gap was uneven across another 11 Member States. In four countries (BE, EE, FR, UK), no significant changes have been observed, yet Czechia and Slovakia show the reverse of the gender gap, compared to the situation in 2005 and 2010.

Figure 20: Gender gaps in time dedicated to housework (cleaning and cooking) per day, among the employed population (hours per day, 15+, EU-28, 2005-2015)

Source: EIGE elaboration of EWCS 2005-2015.

Note: Weighted data. Based on valid cases of EWCS 2000, 2005, 2010, 2015. Trend question: ‘How many hours per day are you involved in any of the following activities outside work?’ - Cooking and housework.

The COVID-19 pandemic has resulted in a dramatic turn to teleworking for non-essential workers in most Member States. Research carried out in the UK during the lockdown showed that while women were still spending more time on childcare than men, the gender gap in childcare was smaller than before the pandemic. It highlighted that the division of childcare had grown more equal in households where men were either teleworking or had lost their jobs (Sevilla & Smith, 2020). Analysis of the UK Office for National Statistics survey of 1 300 families across Great Britain compared with the 2014–15 UK Time Use Survey showed that, on average, men increased their unpaid care by 22 minutes per day, while women’s decreased by 20 minutes. As a result, the daily gender gap in time spent decreased from 110 minutes to 67 minutes. This change is attributed to men spending more time at home, as commuting and travel activities are suspended (Office of National Statistics, 2020). Despite this increase in men’s contributions to childcare, women are still shouldering the additional care activities resulting from school and day care closures (Norman, 2020). In Belgium, data collected through time diaries shows that both working men and women have experienced increased time pressures ( 57 ) during the lockdown compared to data of 2013 but time pressures increased most particularly for parents and especially women with children (Mullens & Verbeylen, 2020). Results further showed that time dedicated to childcare and domestic work increased in similar ways for women and men (13 minutes more for women and 18 minutes for men). During the lockdown, women still dedicated about 30 minutes more than men every weekday to childcare and domestic work. Men enjoy an hour more of free time than women ( 58 ). Compared to previous time use surveys, the gender gap in domestic work and childcare has remained similar to 2013 levels (about 30 minutes per weekday to the detriment of women) (Bacq, 2020). In France, a survey undertaken during the strictest phase of the lockdown showed that one-in-three women stopped work to focus on childcare and housework, compared to one-in-four men (Lambert et al., 2020).

3.2 How much of their care needs do families externalise and what are the effects?

3.2.1 Use of ECEC services

The use of childcare services for children under compulsory school age has increased in the EU over the past decade (EACEA, 2019). Between 2010 and 2018, the enrolment rate of children under three increased by 5 p.p. and children aged between three and compulsory school age increased by 9 p.p. In 2018, 35 % of children under three and 86 % of children from three to mandatory school age attended formal childcare services in the EU-28 ( 59 ). However, important differences in enrolment rates persist between Member States, especially for children under three years of age. While most Member States have achieved the Barcelona target of 90 % of children between three and compulsory school age attending formal childcare services, several continue to fall short of the Barcelona target of 33 % of children under three years (Figure 21).

Figure 21: Share of children enrolled in formal care, by age (%, EU-28, 2018)

57 Subjective measure based on a 8 item scale.

58 6h28 for men compared to 5h26 for women for weekdays.

59 EIGE calculations based on Eurostat [ilc_caindformal]; [ilc_caindother]. For the second Barcelona target focusing on the enrolment of

children between the age of three and compulsory school age, data is not fully comparable between countries, as this age varies between Member States.

Source: Eurostat [ilc_caindformal] extracted on 3 January 2020.

Note: Share of children in formal care as a percentage of the population of the same age group. Formal care includes education at preschool or equivalent, childcare at centre-based services, day care centres, pre-school. Provisional data: IE; UK.

The enrolment rate by number of hours of childcare attendance per week is a particularly important indicator in the analysis of the externalisation of childcare activities. Reflecting the commitment made by EU countries in 2002, this indicator is part of the monitoring framework of the BPfA. Most Member States have an enrolment rate of children in formal care that is higher for full-time services than for part-time childcare services (Figure 22).

Figure 22: Share of children under three in formal care, by number of hours per week (%, EU-28, 2018)

Source: Eurostat [ilc_caindformal ].

Note: Share of children in formal care as a percentage of the population of the same age group. Formal childcare includes education at preschool or equivalent, childcare at centre-based services, day care centres, pre-school. Provisional data: IE; UK.

In some countries (DK, LU, PT, SI), more than 40 % of children under three attend formal care for more than 30 hours per week, falling to less than 10 % in full-time childcare in others (UK, NL). These differences reflect the age of legal entitlement and opening hours of childcare services (e.g. DK, SE guarantee a place in full-time childcare for children under the age of one), their cost (e.g. high costs in UK) and the working hours of women with children (e.g. high rate of women’s part-time employment in NL).

In 2016, 14 % of households in the EU reported an unmet need for childcare services ( 60 ). Affordability was the leading cause (50 %), followed by a lack of available places (12 %), opening hours (8 %) and distance (5 %). Unsurprisingly, reliance on informal ECEC services (including grandparents and other relatives, friends or neighbours) was higher among low-income families, with 61 % of families in the poorest quartile dependent on family or friends, compared to 50 % of families in the richest quartile. The use of formal childcare as the main type of childcare also increased with income, from 28 % in families in the poorest quartile to 45 % for families in the wealthiest quartile ( 61 ).

Analysis of EU-SILC data found that mothers’ education levels were an important predictor of the use of formal ECEC services in all EU countries. Children born to women with a high education level were much more likely to attend formal childcare than children born to women with a low education level. In the UK, for example, this was up to six times more likely (Bradshaw, Skinner, & Van Lancker, 2015). These analyses highlight that entrenched socioeconomic inequities affect women’s ability to access and benefit from services designed to promote WLB, and underline the need for an intersectional analysis on service usage to ensure access for families most in need.

Affordable and high-quality childcare services are fundamental to women’s ability to juggle childcare and participation in the labour market (Arpino et al., 2012; OECD, 2017). Empirical research shows that childcare availability appears to have a greater impact than cost on mothers’ labour supply, and the impact of childcare availability and costs are stronger among more disadvantaged backgrounds (i.e. lower income and less skilled) (Del Boca, 2015). The OECD (2016) found that in EU countries ( 62 ), children under three are far more likely to be enrolled in formal childcare services when their mother works, largely because parents’ employment increases the demand for non-parental care. This is reflected in the fact that in most EU countries, the use of professional childcare services is higher among employed women than among employed men (Figure 23). On average in the EU, women’s use of childcare services is 5 p.p. higher than men’s in comparable circumstances (employed, using childcare services for some or all of their children). This gender difference reaches 12 p.p. in Hungary, highlighting that employed women with childcare responsibilities tend to rely on childcare services more than men do.

Figure 23: Gender gap in the use of professional childcare services among employed people with childcare responsibilities (18- 64, % points, EU-28, 2018)

60 EU-SILC [ilc_caindformal].

61 EIGE calculations based on European Quality of Life Survey (EQLS) 2016. Main type of childcare used for youngest child among respondents with at least one child < 12 in household in EU-28. Formal childcare refers to formally contracted childcare and/or childcare facilities.

62 Except for Sweden, where all children older than one year are entitled to a place in ECEC regardless of parental employment status, and childcare fees are low and thus affordable for all parents.

Source: EIGE calculations based on EU Labour Force Survey ad hoc module on reconciliation of work and family life [lfso_18cusels] extracted on 12 February 2020.

Note: The gender gap in use of professional care services is calculated as the difference in p.p. between the share of employed women using professional childcare services and the share of employed men using professional childcare services. Figures are calculated for the population using professional care services for all or for some children over the population 18-64 that only takes care of children under 15. ‘No response’ is not considered.

Women’s over-reliance on childcare services is further reflected in Eurostat data showing that, in 2018, one-inthree women (in employment or with previous employment) reported a work interruption of at least six months for childcare reasons (33 %) compared with a little over 1 % of men (Eurostat, 2019). The lowest share of women’s work interruptions for childcare reasons were seen in Malta (13 %), followed by Spain and Portugal (14 % each), while the highest shares were reported in Estonia (68 %), Bulgaria (67 %) and Czechia (66 %). The share of men who reported a career break for childcare reasons was 4 % or less in all Member States except Sweden (13 %).

Grandparents’ support in childcare: another gendered form of unpaid care

In countries where public provision of childcare services and opportunities to work part-time are both limited, families tend to rely more on informal care by grandparents (Janta, 2014). Data shows that grandparents are the main childcare providers in one-half to two-thirds of households with children in seven Member States in the south of Europe ( 63 ) (Eurofound, 2017). Grandmothers are more likely than grandfathers to be engaged in childcare, particularly when it comes to full-time childcare (Glaser et al., 2013; Igel & Szydlik, 2011; Jappens & Van Bavel, 2012). Among grandparents, 35 % of women and 29 % of men report providing care and/or education services to their grandchildren at least once or twice a week (Eurofound, 2017). There is evidence that childcare reduces the working hours of grandmothers less attached to the labour market (i.e. already working fewer hours), with possible consequences for incomes and exposure to the risk of poverty in old age (EIGE, 2019a; Rupert & Zanella, 2018).

Similarly, the effects of childcare responsibilities on employment vary substantially by gender (Error! Not a valid bookmark self-reference.), with 40 % of women in employment reporting at least one change in employment due to childcare responsibilities, compared to 17 % of men in similar circumstances. About 18 % of employed women in the EU reported a reduction in working hours, a situation experienced by only 3 % of employed men.

63 BG, EL, HR, IT, CY, MT, RO.

Figure 24: Effects of childcare responsibilities on employment of women and men (25-49, %, EU-28, 2018)

Source: EIGE calculations based on Eurostat, EU-LFS ad hoc module on reconciliation between work and family life [lfso_18ceffed].

Notes: ’No responses’ were not included.

3.2.2 Use of LTC services:

Despite independent living being a political priority (see section 2.2), a significant number of older people in the EU reside in healthcare or LTC institutions. According to 2011 census data, the share of older people in the EU aged 65–84 years living in institutions was 1.7 %, with the share reaching 12.6 % among those aged 85+ ( 64 ) (Eurostat, 2017).

Recent OECD data shows that the share of older people over 65 in LTC institutions other than hospitals is above 4 % in seven Member States (DE, EE ,FR, LT,LU, FI, SE) and below 2 % in three countries (LV, PL, PT) ( 65 ). For all countries for which data is available, women make up the majority of institutional LTC residents, ranging from 56 % in Latvia to 75 % in Czechia ( 66 ). The high numbers of people living in institutions is partly linked to the dearth of community-based services and support, making home-based care difficult to access (EIGE, 2019a, 2020d; Spasova et al., 2018).

In the EU-28, the coverage rate of LTC services (the ratio between recipients of institutional and home care services and the population of in need of care) is estimated at 35 % (Figure 25) (European Commission, 2018), with considerable variation between countries. Coverage rates vary from above 60 % in Belgium, Malta and the Netherlands to below 10 % in Poland and Portugal. Coverage rates tend to be higher for home care services than for institutional care in most Member States (with the exception of CZ, DE, IT, CY, LT, HU, PT, RO).

Figure 25: Coverage rates of long-term care recipients by type of care, as a percentage of population potentially in need of care (%, 15+, EU-28, 2016)

64 Excluding Ireland and Finland, for which no information is available.

65 OECD-Stat 2018, LTC recipients in institutions - Long-term care resources and utilisation: Long-term care recipients. https://stats.oecd.org/index.aspx?queryid=30143# . Data available for 14 Member States. Data extracted on 9 July 2020.

66 OECD-Stat 2018, LTC recipients in institutions - Long-term care resources and utilisation: Long-term care recipients. https://stats.oecd.org/index.aspx?queryid=30143#. Data available for 13 Member States. Data extracted on 9 July 2020.

Source: EIGE elaboration on European Commission (2018a).

Note: Coverage estimated as ratio between recipients and population potentially needing LTC. Recipient data presented is provided by Member States. Population of potentially dependent is based on 2011-2015 average of EU-SILC data on ‘self-perceived longstanding limitation in activities because of health problems for at least the last 6 months.’ The coverage for institutional care for LU is likely to be underestimated due to incomplete data.

*EU-28 countries unweighted average.

Gender is a key dimension of the analysis of LTC services, including barriers to access, as women make up the majority of both care recipients and providers. Research also shows that gender intersects with other axes of marginalisation, affecting which groups access formal LTC services. People with low income, people with low education (where women are overrepresented), migrants and ethnic minority women have greater difficulty in accessing formal LTC services (Crepaldi, Samek Lodovici, & Corsi, 2010) . A study by Privalko, Maître, Watson, and Grotti (2019) based on 11 EU countries 67 , found that lone parent households and households with a person with a disability are 2.6 times more likely to have unmet home care needs than households with a person aged 65 or over.

In 2016, in most EU countries, over half of care recipients needed to pay for the formal home-based LTC services they used (EIGE, 2020d). In several EU Member States, public subsidised formal LTC is reserved for citizens who do not have family support (e.g. BG, EL, LV, PL, UK) (Spasova et al., 2018). Public expenditure on LTC services shows considerable variation in EU countries, with Nordic and Scandinavian countries (BE, NL, AT, FI, SE) showing the highest expenditure (above 3 % of GDP in 2015) (European Commission, 2018d). Financial barriers may be experienced more frequently by women, due to sharp income disparities between older women and men ( 68 ) and the feminisation of poverty in older age ( 69 ) (EIGE, 2019a, pp. 38-39)). Unmet needs for formal LTC services have far-reaching effects: they increase the risk that care recipients and carers will experience social exclusion and poverty (King & Pickard, 2013; Srakar, Hrast, Hlebec, & Majcen, 2015), they can lead to negative health outcomes and poor quality of life for those in need of care, and extensive engagement in informal care by family members or friends (EIGE, 2020d). On average in the EU, women represent 62 % of all people providing informal LTC to older people or people with disabilities (EIGE, 2019a). In many Member States, unavailability and/or high costs for formal LTC services (either home-based or in institutions) have resulted in an increasing role of domestic workers, often migrant women, in the provision of LTC at home (Spasova et al., 2018).

67 AT, BE, DK, EL, ES, FI, FR, IE, IT, SE, UK. Study based on EU-SILC 2016.

68 In the EU-28, men aged 65 and over earned 38 % more than women of the same age group (EU-SILC, 2017).

69 In the EU-28, 19 % of women aged 75 and over were at risk of poverty, compared to 13 % of men of the same age group (EU-SILC, 2017).

Privalko et al. (2019) shows that in the countries analysed, the employment gap between women and men (18–64) is significantly smaller (4 p.p.) when needs for home care are met, compared to those with unmet needs (12 p.p.).

At country level, the provision of home care services is linked to women’s career prospects: in Member States where households show high levels of unmet needs for care services, women show lower scores in career prospects ( 70 ). Provision of informal LTC is a significant element for WLB of family carers and gender equality.

According to Eurostat 2018 data, more than 10 million employed people (of whom six million were women) in the EU-28 had care responsibilities for incapacitated relatives aged 15 years and older - 6 % of women and 4 % of men in employment ( 71 ). 10 % of women and 4 % of men with care responsibilities for relatives with health issues experienced a work interruption of at least one month to care for them (Figure 26). Work interruptions are more common than decreases in working time (

Figure 27 ), as almost all countries have adopted legislation on access to leave for carers. However, legal arrangements vary considerably in duration, eligibility, benefit level and entitlement to social security rights (Bouget, Spasova, & Vanhercke, 2016). Apart from some exceptions (IT, NL, RO), in all EU countries for which data is available, work interruptions and decreases in working time are more prevalent among women than men.

Figure 26: Share of employed population or population with previous work experience who experienced at least one month of work interruption due to care responsibilities for relatives with health issues (%, 18-64, EU-28, 2018)

Figure 27: Share of employed population or population with previous work experience who experienced a decrease in working time of at least one month due to care responsibilities for relatives with health issues (%, 18-64, EU-28, 2018)

Source: Eurostat [lfso_18redsted].

70 The Career Prospects Index is a composite indicator used in the domain of work of the Gender Equality Index. It was developed by Eurofound and combines indicators on employment status, type of contract, prospects for career advancement as perceived by the worker, perceived likelihood of losing one’s job and experience of downsizing in the organisation.

71 EIGE calculations based on the EU-LFS ad hoc module on reconciliation between work and family life of Eurostat [lfso_18cresls]. Data includes people who have care responsibilities for incapacitated relatives only and people who have care responsibilities for both incapacitated relatives and own/partner's children. The population with care responsibilities for incapacitated relatives are defined as people who look after or provide help to the partner or relatives (15+) in need of care because they are sick, older, or have disabilities. This includes the relatives of the spouse/cohabiting partner, irrespective of whether or not they live in the same household.

Note: The share is calculated on the population that at some time had care responsibilities for relatives aged 15 and over with health issues (i.e. excluding those stating that they never had care responsibilities). Not available because of unreliable data: HR, (CY, LV for men); Low data reliability for men for: EE, HR, CY, LV, (SI, MT for reduction of working time only); for women for: HR, SI, (CY, MT for reduction of working time only).

3.2.3 Use of housework services

As seen in section 3.1.2, household care is one of the activities in which gender gaps are most stark. The use of external services for housework (cooking, cleaning, ironing, gardening, caring for pets, etc.) has increased in recent decades, largely due to women’s increased participation in the labour market. Externalising part of housework and household chores is a way for employed women to improve WLB (De Ruijter, Treas, & Cohen, 2005; Raz‐Yurovich, 2014; Van der Lippe, Tijdens, & De Ruijter, 2004)

Several studies have assessed the relationship between externalisation of housework and women’s labour market participation. By purchasing services, highly skilled women with the highest opportunity costs in terms of labour market participation can increase their engagement in paid work and reduce the time spent on housework (Barone & Mocetti, 2011; Forlani, Lodigiani, & Mendolicchio, 2015; Raz-Yurovich & Marx, 2019; Raz‐Yurovich, 2014). At the same time, the strong rise in women’s migration resulting from transnational economic inequalities is seen as a crucial factor contributing to increased externalisation of housework (Morel, 2015; Raz-Yurovich & Marx, 2019). As women increasingly took up paid work and men did not increase their share of the domestic work accordingly, there was an urgent need for a third person (usually an immigrant woman or a woman from a lower socioeconomic background) to do that kind of work. The presence of ‘affordable’ migrant domestic workers enabled professional women to maintain their position in the labour market, providing the illusion of gender equality within the relationship of the employing couple (see section 4.1.1). The effect however, is to shift gender inequalities from that relationship into global care chains (Morel & Carbonnier, 2015).

The magnitude of externalisation of household care services is difficult to assess in the absence of official statistics at EU level, primarily due to the variety of national definitions of personal and household services, the different employment models of service provision ( 72 )(Farvaque, 2013). Estimations are further complicated by the high share of undeclared work ( 73 )(Eurofound, 2020b). Estimates of the size of the sector are usually made from the number of employees in specific economic divisions or occupations, although these do not account for undeclared work. As seen in chapter 1, undeclared work in the provision of housework, and more generally among domestic workers, can be very high in some countries. According to a special Eurobarometer on undeclared work in the EU (European Commission, 2014b), home cleaning services are the third most common area of undeclared work ( 74 ), with 15 % of respondents reporting having used undeclared services for home cleaning. On the supply side, 13 % of Europeans who carried out undeclared work referred to cleaning services. Carrying out undeclared work in cleaning services is more prevalent among women (25 %) than men (5 %), and among people with low education

72 Farvaque (2013) identifies two main employment models of service provision in use in the EU: i) the ‘direct employment model’ (dominating in southern countries), where workers are directly recruited by private households to perform domestic tasks in their home; ii) the ‘employment in service provider organisations’ (dominating in northern countries and Belgium) where workers are employed by an organisation selling those services to households.

73 The European Commission defines undeclared work as ‘paid activities that are lawful as regards their nature but not declared to the

public authorities as may be required by the specific regulations of Member States’ (European Commission, 1998a).

74 29 % of respondents reporting having used undeclared services for repairs or renovations and 22 % for car repairs.

(31 %). Recently, several EU countries have introduced measures to make housework services more affordable, such as tax credits and vouchers (Morel & Carbonnier, 2015), and to deter the use of undeclared work (Farvaque, 2013).

3.3 Do external care services support more equal sharing of care work?

In order to deepen understanding and shed light on the prevalence of care externalisation by households in the EU, qualitative data was collected through a set of focus group discussions in 11 Member States ( 75 ). Participants were invited to discuss their family arrangements for allocating different care activities (care for children, LTC for older relatives or people with disabilities and other chronic conditions, housework), their decision-making process for resorting to external help, and the possible effects of externalisation in balancing the burden of unpaid care. More details on the focus group discussions including the list of countries, criteria and approaches to recruiting participants and interviewing guide can be found in the Annex (section f).

3.3.1 Men often perceive their families as more equal than they are

While statistical data presented previously shows that gender inequalities in unpaid care work at EU level are still pervasive, most focus group participants stated that care and housework activities were shared quite equally

76

between women and men in their household, with no strict gender division of care responsibilities ( ). Only in two countries (IE, PT) did participants acknowledge their traditional gendered division of household labour, with women shouldering most of the unpaid care. In these cases, men were considered to be solely focused on paid work: ‘My husband is starting to learn how to open the washing machine; men were formatted to their work, they leave the house to go to work, and that is their work; everything else does not exist’ (women, PT).

However, even among participants reporting that care is equally shared in terms of time spent, when analysing the type of household tasks described by participants, a gendered distribution of labour is visible. Women perform the heaviest and most traditional tasks inside the home (laundry, cleaning), while men carry out more practical tasks inside and outside the home (small home maintenance projects, gardening): ’I do the gardening and my wife washes the clothes …’ (man, DK). Care related to children seems to be mainly dealt with by women. For example, several male respondents said they do not do laundry for the family but, rather, do it for themselves, if at all. In some cases, perceptions about who does what and more specifically about the time allocated to these tasks also differs between women and men. Most women feel that they carry the brunt of household chores, while their male partners feel it is more equally balanced, and those diverging perceptions leading to tensions. ‘My husband and I regularly fight about who does most, he feels it is equally balanced and I feel I do most. It is his task to vacuum clean and he has now bought a robot vacuum cleaner. He considers turning that robot on as his duty, but that is not an equal division of household tasks’ (woman, NL).

75 A pilot focus group in HR, plus 10 others covering DE, DK, EE, IE, FR, NL, PT, RO, SK, FI. More details on the number and characteristics of

focus group participants can be found in Annex f. Focus group discussion.

76 This finding is at odd with data from Eurobarometer showing that in 2017, 73% of respondents considered that women spent more time than men on housework and caring duties. 22% considered the time spent to be equal between women and men .

Many participants agreed that they were first exposed to a gendered division of responsibilities in their families of origin, pointing to very early socialisation. Participants referred to their mothers not only as caregivers to their children but also to their husbands: ‘But even going back to when I was a child, my mum stayed home and my dad worked, my mum did everything then as well’ (woman, IE). Traditional gender roles within the family are also at play among young people. One student testifies: ‘I live together with other female and male students. We made a roster for cleaning but very often the boys try not to do their job and hope we don’t notice. Also, there was one boy whose mother visited once a week to tidy and clean his room. We were so shocked about this that we told the mother to stop because otherwise he will never learn to take care for himself and will come to expect other women in his life to do that for him’ (man, NL). As sole care providers, lone mothers observed that discussions around sharing do not apply to them. ‘It is up to me to be the father, to be the mother, to be everything; I have no support’ (woman, PT). This is also true in other situations, such as following a separation - even when there is shared custody of the children, lone mothers experience unequal contributions to parenting ‘Our child had difficulties and he was diagnosed with autism when he was three. Even before the divorce I was the only one to perform the care and domestic activities. My husband was travelling for long periods of time; he was rarely at home’ (woman, RO).

Similar to the statistical data described in sections 3.2.1 and 3.2.2, the impact of care responsibilities on employment is felt more by women. Several female participants describe their experiences: ‘I was working in the technical management of construction works [as a civil engineer] for 15 years […] in different locations […] with long working hours […] At some point in time I became very stressed, with everything on my shoulders, the therapies and all, because my husband was not very available for that, his work was not flexible at all […]. So I decided I had to work closer to home. So I did [as a self-employed real estate consultant], I manage my working schedule, I make my own appointments, etc.’ (woman, PT). ‘[When her mother got dementia] I thought, well, I have to find some other thing to do; it is no longer possible for me to work for an employer […]. More often I was absent from work or showed up late […]. I then started to work as a cleaner, doing some hours, in order to be able to meet the expenses one always has’ (woman, PT).

3.3.2 Externalised care as a strategy to lighten women’s load, sometimes unwillingly

Participants were asked to reflect on decision-making around externalisation, specifically when, how and by whom the decision to externalise was made and the main elements taken into account in that decision. In many cases, participants reported that the decision to externalise was made by consensus. In other cases, the decision to use paid care was made by a woman or resulted from a family event affecting a woman, particularly return to work after parental leave: ‘ ... the older child there was the reason why I wanted to go back to work on a part-time basis and I wanted to have time, there was space for it, so it was my need to have paid care...’ (woman, SK) or the arrival of another child: ‘we use a private nursery school mainly because we had a second child, because the older one wanted to play with her and pull her, so we wanted the younger child to have a calm place ...’ (woman, SK).

The majority of focus group participants stressed that the decision to externalise was approached differently, depending on the type of care activities to be externalised. In the case of housework, it was mainly to achieve a certain level of freedom. In these cases, the decision to externalise indirect care work was to give more free time to the family. Sometimes this shift was disapproved of: ‘So in terms of all of the housework, I externalise it by bringing somebody in. It was disapproved of greatly in my family because “Oh you’re only working part-time, you’re at home, why can’t you do it?”’ (woman, IE).

Gender norms make it easier for men to receive care than women. However, an important difference is noted between women and men senior participants. While one man gladly accepted external help once his wife passed away, an older woman expressed feeling very conflicted about having to get external help: ‘After my wife died I realised how much I had underestimated the amount of work it takes to keep a household running. I also had to do lots of things I had never done before like buying clothes or cooking meals. Very quickly, I started looking for a cleaner. She’s been coming for six years now, and I could not cope without her’ (man, NL). ‘When I heard both my knees needed surgery I tried to rearrange everything in my house so I could cope after my return from the hospital without any external help. It was very important for me to be able to do everything alone. I only had a physiotherapist for a couple of weeks but was very keen on doing everything as quickly as possible on my own again. For me this is very important. It is a matter of independence. Giving up my independence would be terrible for me so as I grow older I try to arrange my life in such a way that I can keep going on my own for as long as possible’ (woman, NL).

In case of older relatives who are no longer independent, the decision of family members to externalise care stems from their desire to stay employed and an awareness that health limitations require professional care. However, in these particular cases, the decision to externalise is felt by female participants as a failure to care for their loved ones ‘The decision to send our mother to a geriatric hospital during the last month was almost imposed on us by doctors who said, “it will be too much of a burden for you”, but retrospectively, I regret it’ (woman, FR). The decision to place family members in institutional care appears to be a last resort when informal and home care proves insufficient. ‘You must apply for a home care package and four years ago I said oh no, no, we’re managing. I’m an osteopath, I know how to make her walk, we’ll get everything working. And then a year later when her frailty began to dramatically increase and she had had two falls and fractured her spine, it was a case of okay, we need some help and I negotiated 17 hours a week, so every morning, every evening [of externalised care for her mother]’ (woman, IE). ‘We had two people who took care of my mother-in-law and only then did we put her in an institution’ (woman, HR).

3.3.3 The ‘mental load’ of organising externalised care is borne by women

Generally, the externalisation of housework was considered to bring positive effects, giving extra time to families. Some participants pointed out that externalising indirect care not only saves them time but can also avoid conflict about gender roles. ‘When we decided to move in with each other, I immediately negotiated with my boyfriend that we would get a cleaner. Otherwise, I would refuse to move in, because I knew it would become problematic. He’s rather different than I am when it comes to household care and I knew we would end up having conflicts about this. To avoid this, I decided it would be better to take an external cleaner right from the start, so all was settled right from the start’ (woman, NL).

Several participants in the focus groups agreed that the responsibility for identifying, selecting and organising externalised services is, in general, shared between family members. However, deeper discussion revealed that the coordination of external care services appears strongly gendered, with men admitting that the mental load of organising care (planning, budgeting, scheduling of care and household tasks) is mostly borne by women. ‘I have to agree, my partner has a much higher mental load of organising care. I was raised traditionally male [...], there was nothing I could have learned it from. I am very grateful for a partner who reflects these things and I try to accept and embrace it and to act accordingly, e.g. by organising the doctor’s appointment and so on’ (man, DE). Women themselves acknowledge the disproportionate burden of organising care falling on them: ‘We have a big mental load problem that arises from the fact that I took six years of parental leave [....]. And to get out of these structures is incredibly difficult, after a routine for six years. There are things he does not know because he has never had to know them’ (woman, DE). ‘It seems that organisation of housework routine, care work, use of external services is a decision made by a woman’ (woman, EE). In general, women’s skills and efficiency are given by women and men alike as reasons for this allocation of responsibilities.

Chapter 4: What are the consequences of externalisation?

Externalisation seems to be the predominant approach adopted to reduce inequalities in care and in pay in the EU. It has the potential to alleviate women’s burden of unpaid care work, allow their greater participation in the labour market and thus narrow the gender pay gap. On the other hand, however, outsourcing care work produces new inequalities. In particular, it establishes new hierarchies between those women (mostly native-born) who can afford to outsource care work and those (often foreign-born and from a migrant background) who work in the care industry, with low wages, precarious jobs and dire employment conditions. The fragility of the care sector, characterised by low investments and a low-paid insecure workforce, became immediately apparent during COVID-19. The global pandemic took a great toll not only on care workers themselves but on society (and the economy) as a whole, and highlighted the importance of considering care work and care infrastructures as a priority in the EU political agenda.

4.1 The paid care sector: significant employment yet perpetrating inequalities

4.1.1 Women constitute the majority of the care workforce and experience poor working conditions

In 2018, the total care workforce amounted to 21 % of total employment, corresponding to almost 49 million workers, more than 37 million of whom were women (76 %) ( 77 ). These figures are likely underestimated, as some care occupations experience a large share of undeclared employment ( 78 ). According to the European Employment Policy Observatory (2016) , the ‘personal and household services’ (PHS) sector, which includes carerelated services and household support ( 79 ), is the third most commonly identified sector for undeclared work, after the construction sector and hotels, restaurant and catering. (EFSI, 2018) found that in some EU countries ( 80 ) the share of undeclared services can be as high as 70 % of all transactions.

Care is a gendered issue, even when it is paid The care workforce is strongly female dominated: the share of women (of the total workforce) ranges from 72 % in the education sector to 89 % in domestic work, compared to 46 % in total employment ( 81 ). A number of jobs in the care sector are still commonly considered ‘women only’, such as pre-primary education, nursing or midwifery, secretarial and personal care work, domestic and related help (EIGE, 2017; European Commission, 2018b). Women are overrepresented in lower qualified occupations, such as childcare workers and teachers’ aides (93 %), personal care workers in health services (86 %), and domestic cleaners and helpers (95 %). Recent data from Eurofound (2020b) shows that the LTC sectors alone counts 6.3 million workers, 81% of which are women.

Care work involves tasks that women have traditionally performed without pay in the domestic sphere, and for this reason the skills it requires are systematically undervalued and overlooked, in society as well as in the labour market (ILO, 2016, 2017b) (see chapter 1). The devaluation of tasks and skills stereotypically associated with women is further exacerbated by the fact that wages often decline where the female workforce increases (ILO, 2017b; Levanon, England, & Allison, 2009; Tijdens, De Vries, & Steinmetz, 2013). In addition to cultural norms, the low economic recognition of care work can be attributed to its high part-time rate, as well as to cutbacks in public spending. The lack of investment in the care industry translates into lower fees paid to private providers, thereby contributing to low wages and poor working conditions (ILO, 2018).

This section describes the features of the workforce in three selected core care occupations (see section h of the Annex for explanation of this selection and classification), and the working conditions they face. The analysis is based on EU-LFS 2018 microdata and does not include Bulgaria, Malta, Portugal or Slovenia, due to data unavailability. Figures are presented in the Annex (section h).

77 Eurostat [lfsa_egan2] and EIGE calculation based on EU-LFS microdata 78 The European Commission (1998a, p. 4) defines undeclared work as ‘paid activities that are lawful as regards their nature but not declared to the public authorities as may be required by the specific regulations of Member States’.

79 The PHS brings together activities carried out mainly in users’ homes relating to personal assistance services (early childhood, childcare, dependence, disability, invalidity, etc.) and to services of daily living (cleaning, ironing, gardening, small DIY, maintenance, remedial classes, etc.)’ (EFSI, 2018).

80 Particularly in countries where no PHS supporting policies are implemented for household-related services, where undeclared services represent around 70 % of all transactions. In countries where supporting measures are implemented (e.g. price reduction for users, cost reduction for providers, increase of the quality of services), that figure falls to around 30 %.

81 EIGE calculations based on Eurostat data [lfsa_egan22d] for year 2018.

• a. 

  Childcare workers and teachers’ aides: a profession mainly for native-born women

Childcare workers and teachers’ aides, who represent over 2.6 million workers in the 24 Member States included in the analysis, are predominantly women (93 %), born in the country of residence (86 %), and with an intermediate level of education (56 %).

Data shows that childcare workers and teachers’ aides have relatively low monthly pay compared to the total economy: about 60 % are among the 30 % lowest paid workers. This is partly due to the high part-time rate: 41 % of workers (compared to 21 % in total employment), 40 % of whom chose this solution due to their care responsibilities ( 82 ).

Teachers, childcare workers and teachers’ aides often suffer from psychosocial distress due to deep emotional involvement and heavy workloads associated with low staff–child ratios (Converso, Viotti, Sottimano, Cascio, & Guidetti, 2015). Heavy workloads and stress may have a negative effect not only on their work satisfaction but also on children’s well-being. In the EU countries analysed, on average, 23 % of childcare workers and teachers’ aides were engaged in informal or formal education and training in the four weeks prior to being interviewed, which is only slightly higher than the average registered across all the occupations (19 %).

• b. 

  Personal care workers in health services: a female profession with low pay and lack of recognition for both nativeborn and, increasingly, migrant women

Healthcare assistants and home-based personal care workers number over 5 million in the 24 EU countries considered, with almost 9 out of 10 being women. Foreign-born women and men account for 23 % of workers. Given their work tasks, they have a lower level of educational attainment than in the health sector overall. However, both under and overqualification are often observed among personal care workers in health services (ILO, 2018) . Colombo, Llena-Nozal, Mercier, and Tjadens (2011) argued that several workers are underqualified: they have little formal training and, in many cases, do not have the required qualifications to do the job. Data shows that 22 % of personal care workers in health services in the EU have below secondary level education ( 83 ). At the same time, overqualification is also common, particularly among skilled migrant workers (i.e. nurses) who cannot validate their certification and are subject to unfair recruitment practices (Colombo et al., 2011).

Non-standard forms of employment, such as temporary or part-time jobs, are quite common among care workers in health services. Almost one in five have a temporary job and 4 in 10 have a part-time job ( 84 ). Workers in nonstandard forms of employment are more exposed to job insecurity, gaps in access to social protection, higher levels of health and safety risk, and lower pay (ILO, 2018). Women and men working as healthcare assistants and home-based care workers receive lower wages compared to the health sector or the economy as a whole. In the EU, more than 50 % of personal care workers in health services are among the 30 % lowest paid workers ( 85 ). Eurofound (2020b) highlights that LTC workers’ wages receive often falls below national average and with pay being on average lower in the private sector than in the public.

82 EIGE calculations based on EU-LFS 2018 microdata. Figures are presented in the Annex (section h).

83 ibid.

84 EIGE calculations based on EU-LFS 2018 microdata. Figures are presented in the Annex (section h).

85 ibid.

Working conditions are complicated by the high prevalence of atypical working hours, with shift work, night work and weekend work being common practice in this sector (43 %, 50 % and 43 % prevalence, respectively). These working time arrangements have an impact on workers’ safety, health and motivation, as well as on the quality of care (ILO, 2017b, 2018) . Healthcare workers are considered at high risk of stress and burnout syndrome due to the heavy physical and mental strain of their job (Elshaer, Moustafa, Aiad, & Ramadan, 2018; Embriaco, Papazian, Kentish-Barnes, Pochard, & Azoulay, 2007), and patient outcome indicators - such as morbidity and mortality - are closely associated with staffing levels, staffing stability and health workers’ education levels (Aiken et al., 2012; Aiken et al., 2014; Griffiths et al., 2019; Needleman et al., 2011). Care workers in the healthcare sector are also more likely to experience violence and harassment (13 %) than the overall workforce (2 %) ( 86 ).

• c. 

  Domestic cleaners and helpers directly employed by households: high prevalence of migrant labour

Domestic workers, as providers of personal and household services in private homes, are considered part of the care workforce. Their work may include tasks like cleaning the house, cooking, washing and ironing clothes, taking care of children, older people or members of a family with disabilities or other chronic conditions, gardening, guarding the house, driving for the family, and even taking care of household pets (ILO, 2018). In the EU, domestic workers are mostly women (95 %), mainly working part-time (69 %), with relatively low skills (56 %) and often from

87

a migrant background (55 %) ( ).

In many countries (e.g. DE, IT, PT) they are employed as live-in caregivers for older people, although lacking the required training and professional expertise (Farvaque, 2015; ILO, 2017b, 2018) . Domestic workers employed as caregivers often suffer from psychological distress and health-related consequences of high physical and mental strain, heavy workloads and precarious job conditions (Carretero, Garcés, Ródenas, & Sanjosé, 2009; Farvaque, 2015; Marcelli et al., 2016) . The negative effects of heavy workloads can be exacerbated by the age of care workers: among domestic cleaners and helpers directly employed by households, almost one in two women is over 50 years old. Several studies highlight the unfavourable and precarious working conditions of these workers, with jobs characterised by low hourly wages, high flexibility requirements, atypical working hours, lack of job security and a high prevalence of irregular employment (EFSI, 2015, 2018; European Commission, 2018b; ILO, 2018, 2019).

Almost 20 % of domestic cleaners and helpers are in temporary jobs (compared to 13 % for the total economy), mostly (88 %) because they could not find permanent work. As a consequence, the share of those looking for another job is three times higher than the average share in the total economy (13 % versus 4 %). Domestic cleaners and helpers directly employed by households are often trapped in a low-wage situation (Farvaque, 2015), and more than 8 out of 10 are among the 20 % lowest paid workers ( 88 ).

Global care chains and the phenomenon of denationalisation

86 EIGE’s calculations based on EWCS 2015 microdata on the question: ‘And over the past 12 months, during the course of your work have you been subjected to any of the following?’ a. physical violence; b. sexual harassment; c. bullying/harassment.

87 EIGE calculations based on EU-LFS 2018 microdata. Figures are presented in the Annex (section h).

88 EIGE calculations based on EU-LFS 2018 microdata. Figures are presented in the Annex (section h).

The high prevalence of foreign-born women in some care professions is connected to the phenomenon of denationalisation, i.e. the transfer of care tasks to women outside the family group, who are mostly foreign-born. This phenomenon draws primarily on the connection established between the welfare state, the feminisation of migration and the global care chains (Romero, 2012) . Global care chains are transnational networks ‘comprised of households which transfer their caregiving tasks from one to another on the basis of power axes, such as gender, ethnicity, social class, and place of origin’ (Pérez Orozco, 2009, p. 4) . In practical terms, externalisation creates new hierarchies and power relations between those households who are able to outsource their share of care work, and those who provide such paid services (mostly foreign-born women with a migrant background), working lowpaid and precarious jobs in the under-funded care industry.

According to Pérez Orozco (2009), the global care chains are a consequence of the current ‘care crisis’ in Europe (and North America). In these countries, women’s participation in the labour market is increasing, leading to their lower engagement in unpaid care within the household (see section 3.1.2). Combined with demographic changes (ageing societies, increasing life expectancy, smaller household composition (European Commission, 2020a)) this prompted a situation where growing care needs were no longer satisfied by women’s unpaid work. They created a new demand for paid care services, a gap that was largely filled by migrant labour (Pérez Orozco, 2009) . According to the ILO (2018), this arrangement is the result of ‘a set of labour market, migration and care policies (or the lack thereof), which shape the choices available to households. When confronted with unaffordable alternatives, families may find it more tempting to resort to the cheapest and easiest solutions on the market, especially when there is a lack of publicly subsidised services’ (ILO, 2018, p. 192).

4.1.2 Women’s overrepresentation in the care industry reflects and reinforces gender stereotypes

The growth of the paid care sector simultaneously encouraged women’s participation in the labour market and reinforced their identification with caring roles in society and their concentration into low-paid and precarious jobs. According to Hanlon (2012, p. 30) ‘Care is socially constructed as feminine within both the private and public sphere because women comprise the majority of society’s carers and because caring is defined as feminine. Despite the fact that caring is sometimes idealised and valorised in itself, to be a carer is to be materially and symbolically subordinated’

The cultural construction of men’s spaces and women’s spaces

The majority of initiatives and debates on horizontal segregation in education and in the labour market revolve around the issue of women’s underrepresentation in science, technology, engineering and mathematics (STEM) disciplines, while men’s underrepresentation in the care sector is rarely addressed (Kaufman, 2020). Block, Croft, and Schmader (2018) analysed the asymmetry in support for changing gender roles and found that initiatives to correct the gender imbalance in male-dominated spaces receive greater support compared to similar measures targeting female-dominated sectors, both in terms of social action and budget allocation. This is primarily due to the widespread social perception that men’s underrepresentation in care is due to internal factors (i.e. lack of motivation and ability), while women’s underrepresentation in STEM is due to external factors (i.e. discrimination, stereotyping). (Block et al., 2018). In addition, Croft, Schmader, and Block (2015) argue that female-dominated sectors are stereotypically considered lower in status (and, as discussed in chapter 1, in economic value), therefore deserve less attention.

This hierarchical dualism contraposing men’s and women’s spaces comes down to gender stereotypes. Men’s underrepresentation in social care jobs mirrors their lower involvement in care work within the home (Fagan & Norman, 2013), revealing a continuum of gender expectations that permeates all of society, from the domestic sphere to labour markets. Simpson (2004) and Drudy (2008) argue that care jobs are commonly deemed to entail tacit nurturing skills and emotional labour that women are believed to possess naturally, as the primary caregivers in the traditional gender-segregated family. The few men in these occupations therefore experience negative bias and prejudice at societal level (i.e. their masculinity is perceived as non-normative), which can have repercussions in their professional and private lives (Fagan & Norman, 2013).

Practical implications of gender stereotypes

Men’s underrepresentation in the care sector has a direct impact on its social and economic recognition (ILO, 2017a; Tijdens et al., 2013). In addition, the lack of male role models among childcare workers has negative consequences on children’s education, as it reinforces obsolete gender stereotypes (i.e. care is a ‘woman’s job’) (Fagan & Norman, 2013). As Block et al. (2018) argue, seeing a greater proportion of male role models might enhance men's own internalisation of caring values and encourage more interest in female-dominated fields. Such cultural change is crucial to overcome horizontal segregation and achieve gender equality in both care and pay.

This cultural shift is not easy to achieve because men’s underrepresentation in care is both cause and consequence of the dire working conditions of this sector (low pay, limited job security, lack of benefits and training opportunities, restricted career progression). In fact, paid work is central to the construction of a socially valued male identity, and breadwinning is understood as the main way in which men are expected to provide care (Hanlon, 2012). Care-related jobs are therefore not appealing to men because they do not guarantee the same level of security and remuneration as other male-dominated sectors - a feature that would undermine their breadwinning role in the family.

At the same time, men are overrepresented in supervisory positions in female-dominated sectors. Vertical segregation in healthcare is much higher than in the rest of the economy and the few men employed in this sector are concentrated at the top of the hierarchy (EIGE, 2019b). Williams (1992) coined the expression ‘glass escalator’ (in contrast to the ‘glass ceiling’ that women experience – see section 1.2.2) to represent the fact that, especially when they enter female-dominated spaces, men are expected to move quickly into authority positions, on a fasttrack to which women apparently have no access.

4.2 The impact of the COVID-19 pandemic on the care sector

4.2.1 Toll on healthcare workers

Harmonised data on the number of healthcare workers victims of COVID-19 in the EU is not available yet. However, the WHO (2020b) shared some initial figures according to which - at a global level - the virus has disproportionately affected this category of workers. A recent publication illustrates that “while health workers represent less than 3% of the population in the large majority of countries, and less than 2% in almost all low-and middle-income countries, around 14% of COVID-19 cases reported to WHO are among health workers. In some countries, the proportion can be as high as 35%.”(WHO, 2020b). These preliminary figures should be interpreted with caution, as they come with the caveat that data availability and quality is still limited ( 89 ). The full extent to which health workers have been affected by infection will not be visible for several months. Furthermore, data on other types of care workers, including personal care workers, domestic workers and teacher’s aides is not yet available.

In addition to the physical hazard, the pandemic has also placed extraordinary levels of psychological stress on health workers. They are for example exposed to high-demand settings for long hours, coping with the unprecedented mortality rate of their patients, living in constant fear of disease exposure while separated from their family and facing social stigmatization (Krystal & McNeil, 2020). Recent studies on the mental health of health care professionals found that during the pandemic they were more likely to develop symptoms of psychological distress, such as compulsive attention to COVID-19-related news, insomnia, healthcare work–related anxiety, guilt, avoidance of returning to the workplace, irritability, intrusive thoughts, nightmares and depression (Ayanian, 2020; Krystal & McNeil, 2020; Pappa et al., 2020; Spoorthy, Pratapa, & Mahant, 2020). The WHO (2020a) also recorded an alarming rise in reports of verbal harassment, discrimination and physical violence among health workers in the midst of COVID-19.

Pressure on the care sector is expected to increase in the coming decades

The COVID-19 pandemic has exposed and aggravated some of the structural shortcomings of the care sector. The strain was heavy not only for healthcare but also for LTC systems, as the virus is particularly deadly for people over 60 years of age (Lloyd-Sherlock, Ebrahim, Geffen, & McKee, 2020). The pressure on the care sector is bound to increase in the coming decades, due to the demographic changes ahead of Europe (European Commission, 2020a). According to OECD (2020) estimates, the proportion of the population over 80 years old is projected to double by 2050. The old-age-dependency ratio is also set to increase, resulting in only two people of working age for every person over 65 years by 2050.

These demographic changes are compelling signs that care systems need robust investment aimed at improving availability and accessibility of services, as well as attracting more workforce (European Commission, 2020a). According to the OECD/EU (2018), there are already indications of labour shortages in the health and LTC sector, with growing concern about nurses, in particular. Among other factors, rising demand is expected to be driven also by the retirement of the current ‘baby boom’ generation of nurses. Yet attracting new workers to the profession remains a challenge, mainly due to poor working conditions (i.e. heavy workloads and low pay) (OECD, 2020). Many countries have addressed these concerns by employing a high share of migrant and foreign-born workers (OECD, 2016). However, COVID-19 exposed the precariousness of this situation for EU care systems, as thousands of migrant care professionals (mostly women) returned to their home countries ahead of border closures. This exodus served to highlight the exploitative mechanisms of European countries relying on the work of low-paid migrant women (mostly from Eastern Europe), who are often deprived of proper work status and decent working conditions (Zacharenko, 2020).

Women are overrepresented among frontline workers

89 For example it is not possible yet to establish whether health workers were infected in the work place or in community settings.

The vast majority of healthcare workers ( 90 ) and personal care workers in health services ( 91 ) in the EU are women, at 76 % and 86 %, respectively. Women have thus been on the frontline of the COVID-19 pandemic, bearing even heavier workloads and risking themselves and their families to care for others (EIGE, 2020c). The pandemic shed light on a longstanding problem in the healthcare industry: the lack of adequate personal protective equipment (PPE) for women, despite their overrepresentation in the care workforce. According to UN Women (2020), ‘as the pandemic has unfolded, it has become apparent that PPE does not protect all workers equally. This is because – quite often – these specifications are drawn up on the basis of the male body, which all too often is taken as the reference for the human population as a whole. As a result, for example, protective goggles may not be the right size or shape for many women’. A survey conducted by Prospect Union (2016) showed that only 29 % of

92

female respondents ( ) used PPE specifically designed for them. Most PPE is based on the size and characteristics of male populations in certain countries of Europe and the US, meaning that it does not fit most women, many men from black and minority ethnic groups, or those with facial hair (TUC, 2017).

This proved particularly dangerous with COVID-19, where adequate PPE is a lifesaving measure for healthcare personnel working with infected patients. In fact, while men are on average more likely to need intensive care or die of COVID-19 than women (Jin et al., 2020), the reverse is true among healthcare workers, with a higher prevalence of women’s deaths. In the medical community, many have denounced the alarming risks associated with unavailability of appropriately fitting PPE (Felice, Di Tanna, Zanus, & Grossi, 2020; Mark, 2020).

4.2.2 Toll on nursing care residents

Throughout the pandemic, the high risk of COVID-19 infection and its severe consequences among residents in nursing care facilities became evident. The vast majority of nursing care residents are older than 65 ( 93 ) (Onder et al., 2012) and many are ‘frail, with complex health needs, underlying chronic diseases and immunosenescence, commonly relying on medical support’ (ECDC, 2020, p. 2), which puts them at a particularly high risk of adverse consequences of COVID-19 infection. Looking at LTC facilities more broadly, they frequently share structural features that facilitate the spread of infectious diseases - they are often closed environments with communal living areas and multiple residents per room, with multiple caregivers providing care for multiple recipients (ECDC, 2020; Gandal, Yonas, Feldm, Pauzner, & Tabbach, 2020).

Emerging research indicates that these structural features of LTC facilities may have contributed to mortality in the COVID-19 pandemic – a high proportion of LTC facilities have seen COVID-19 outbreaks, leading to higher mortality rates in countries with higher numbers of LTC beds per capita (Gandal et al., 2020). Evidence from several Member States (BE, DE, IE, ES, FR, IT, SE, UK) indicates that people living in LTC facilities paid a very high price, with mortality in such facilities accounting for a significant share of all COVID-19 related deaths, from more than 20 % in England to 66 % in Spain (Comas-Herrera et al., 2020; ECDC Public Health Emergency team et al., 2020).

90 EIGE Gender Statistics Database, available at: https://eige.europa.eu/gender href="https://eige.europa.eu/gender-statistics/dgs/indicator/ta_wrklab_lab_employ_selected_healthcare__lfsa_egan22d_hlth">statistics/dgs/indicator/ta_wrklab_lab_employ_selected_healthcare__lfsa_egan22d_hlth

91 See section 4.1.1.

92 UK survey.

93 In 2018, in half of the Member States for which data is available, the share of people over 65 living in LTC institutions exceeded 4 % (see section 3.2.2). Source: OECD-Stat 2018, LTC recipients in institutions - Long-term care resources and utilisation: Long-term care recipients. https://stats.oecd.org/index.aspx?queryid=30143#. Data available for 14 EU Member State. Data extracted on 9 July 2020.

At the time of writing, there is a lack of data on mortality among nursing care residents disaggregated by gender. However, women may well be disproportionately affected, as they account for more than two-thirds of all nursing care residents in a number of Member States (Onder et al., 2012). This tragic loss of life highlights the systematic understaffing and underfunding of most residential LTC institutions, whether public or private. This could create an upswing towards autonomous living and prompt families to move away from residential care and intensify their efforts to provide home-based LTC for their relatives (EIGE, 2020d) but could then further aggravate the disproportionate burden of informal care shouldered by women (EIGE, 2019a).

4.2.3 Preliminary effects of public policies on care

The surge in COVID-19 cases in both healthcare and LTC institutions and the heightened exposure to infection among healthcare workers brought renewed attention to calls for greater investment in care systems. The chronic underfunding and understaffing of most public healthcare systems is often attributed to productivity and costsaving measures adopted during the austerity reforms in response to the economic and financial crisis of 2008. Lockdown and the labelling of most care-related occupations as ‘essential work’ has also reinvigorated public debate on the social value of different roles and their financial compensation. Although far from exhaustive, this section highlights some Member State-level examples of ongoing public debate and attempts to address underfunding in the care sector.

In France, a six-week national consultation on public healthcare led to the 21 July 2020 government announcement of a package of 33 measures to address some of the vulnerabilities noted by social partners and evident during the pandemic. The Ségur de la Sante includes EUR 8.2 billion earmarked for salary increases of hospital personnel and a further EUR 19 billion investment in the healthcare sector, including EUR 6 billion towards LTC institutions over the next five years (Stromboni, 2020).

In Germany, the Federal Cabinet announced EUR 1 billion investment in early childhood education and care services for 2020 and 2021 to expand services by 90 000 new places and adapt them to the sanitary conditions required by the COVID-19 pandemic. In addition, further funds amounting to EUR 1.5 billion have been earmarked for the expansion of all-day care at schools for grades 1 to 4 (BMFSFJ, 2020).

Across the EU, women’s organisations have called for gender-sensitive recovery efforts and further investment in care. At EU level, the European Women’s Lobby (EWL) has called for the adoption of a ‘Care Deal’ for Europe that includes investment in the care economy, development of care services, greater data collection on unpaid care and its inclusion in GDP calculations. It also advocates for the inclusion of gender impact assessments and gender budgeting principles in all funds spent in the framework of the Recovery and Resilience Instrument (EWL, 2020).

Similar demands have been made at national level. Following demands from the women’s movement for a strengthening of social protection measures, Austria has increased unemployment benefits. Similarly, in Germany and Austria, women’s associations are calling for greater acknowledgment and appreciation of unpaid work by women. In the UK, 92 civil society organisations representing unpaid carers have called for an increase in the carer’s allowance (CarersUK, 2020), drawing attention to the fact that informal carers have been placed at particular risk of poverty. Data shows that unpaid carers in the UK were twice as likely to use a food bank during the pandemic (Matthew R. Bennett, 2020).

On 21 July 2020, EU leaders agreed a EUR 750 billion recovery fund to address the consequences of the COVID-19 pandemic on economies and societies. Referred to as the ‘Recovery effort under Next Generation EU’, it accompanies a revised Multiannual Financial Framework (2021-2027) (Council of the European Union, 2020).

Conclusions

Women’s disproportionate burden of care work is the root cause of gender inequalities in pay

Within the EU, the bulk of unpaid care work is borne by women. This significantly hinders their participation in the labour market. Women have a lower employment rate than men, with a high prevalence of part-time workers, mostly due to their care responsibilities at home. Women are also more likely to take up non-standard and lowpaid jobs (with little or no security and social protection), as the flexibility of these arrangements allows them to reconcile their paid employment and caring duties.

When they enter the labour market, women often sort into care-related jobs (horizontal segregation) that reinforce and reflect their caring role in society. However, the care sector is systematically underpaid and underfunded compared to other, male-dominated sectors. This is due to the persistent cultural and economic devaluation of care tasks, which were traditionally performed by women in the domestic sphere and unremunerated. At the same time, women encounter obstacles in career progression and are largely underrepresented in managerial and supervisory positions in most sectors of the economy (vertical segregation), most visibly in female-dominated sectors such as healthcare and education. All of this results in women’s average gross hourly wages being 16 % lower than men’s (unadjusted gender pay gap).

Countries with a low gender gap in time spent by employees caring for children, grandchildren, older people and people with disabilities tend to have a lower unadjusted gender pay gap. At an individual level, outsourcing care tasks to external services (especially childcare services) plays a significant role in reducing gender inequalities in pay. Finally, some characteristics of female employment – sectoral segregation (horizontal segregation), high parttime employment prevalence, underrepresentation in big firms and in supervisory positions (vertical segregation) - determine a significant part of the gender pay gap.

The effects of WLB policies do not reach everyone

Public policies influence individual behaviours in terms of family formation and distribution of roles, including paid and unpaid work. They tend to support people with caring responsibilities through the provision of time off, money and/or services. While the design of most family leave policies is still marked by gender norms associating women with caring duties, progress is observed in several respects. Firstly, the WLB Directive has set minimum standards for family-related leave, namely paternity and parental leave. Secondly, in 2020, the majority of countries comply with the (modest) minimum standards for paternity leave and 20 Member States comply with the minimum of four months’ paid parental leave. Thirdly, some attempts are made to mitigate the effects of long maternity leave on women’s employment prospects and the likelihood of establishing an equal division of care between the parents, either by making some parts of maternity leave transferable to fathers or by moving towards a single parental scheme, inspired by the ‘Icelandic model’. However, improvements are needed in compensation and supportive work and societal norms to improve the low take-up of parental leave among fathers. In most cases, public policies supporting equal sharing of care are limited to people in employment, leaving behind those families who experience the most acute tensions between care responsibilities and paid work. Only a small number of countries are moving towards more universal systems.

In terms of service provision, public policies increasingly acknowledge the far-reaching impact of unmet care needs of care recipients themselves, their families and society at large. This is visible in LTC and active ageing becoming priorities in many countries. However, gender concerns are rarely reflected in such policies and no EU-wide targets on LTC service provision have been adopted. For ECEC services, the Barcelona targets adopted in 2002 would benefit from being revisited to include qualitative elements of service provision, such as quality, accessibility and affordability. Gaps in coverage thus persist, with costs often a barrier to accessing care services for children, older people and people with disabilities.

The combined effect of packages of measures outstrips the impact of single policies. From a gender perspective, the effects of FWAs, statutory leave policies, service provision and cash/tax benefits in respect of the division of unpaid care depend on how they are designed (eligibility criteria, duration, costs, level of income support, availability, quality etc.) and combined. Policy coherence and articulation is key to promoting positive outcomes.

External care services are essential but do not supersede efforts towards equal sharing

From 2000 to 2015, the share of employed women and men engaged daily in childcare and household care declined slightly, which is attributed to broad demographic changes, namely smaller families but also increased time pressure on employed people. Over time, the gender gap in time spent on care has narrowed continuously, decreasing by one hour a day since 2005.

Despite these changes, statistical analysis and qualitative research both show that equal sharing is not a reality for most families in the EU and that care activities remain divided along gender lines, with women contributing more, especially on caring directly for family members. According to the most recent data, employed women spend on average 30 minutes more than men on housework every day and 42 minutes more on childcare and LTC. Analysis of the use of care services for children and people in need of LTC points to insufficient coverage. It also describes the effects of care responsibilities on women’s and men’s careers very differently: about 60 % of employed women report experiencing some change in employment as a result of their childcare responsibilities, compared to 17 % of employed men; about 18 % of women reduced their working hours, compared to 3 % of men; about 10 % of employed women in the EU experienced a work interruption due to care responsibilities for relatives with health issues.

Analysis of the ISSP shows that some characteristics increase the likelihood of dividing care equally, including dual earning patterns and egalitarian gender equality values. Nevertheless, the latest available data shows that most cohabitating couples in the EU follow a pattern where women are the main caregivers in the household and only about one-third of families share care activities equally. Focus group discussions highlighted that women and men often perceive the (unfair) distribution of care in very different ways. In that context, the use of external care services is often an attempt by women to push back against the disproportionate expectation and burden of unpaid care and as a way to reclaim some time and reduce conflict within the family. Furthermore, the traditional assigning of care to women translates into the unwritten expectation that they will take responsibility for the organisation of external care services. This leads to the emergence of another form of unpaid and unshared care work linked to the mental load of organising care, such as planning, budgeting and scheduling of care and household tasks.

The devaluation of care has detrimental consequences for the care workforce and for society as a whole

Among the different policy approaches to achieve a more gender equal society and reduce gender pay gaps in the EU, externalisation seems to be the most frequently chosen. This arrangement, however, suffers from limitations deriving from the cultural and economic devaluation of care work. In fact, people employed in the care industry (mostly women) are among the lowest paid workers and face precarious jobs, heavy workloads and nonstandard work arrangements (e.g. shift work, weekend work) that place them in a vulnerable position in the labour market and in society. This disadvantage is exacerbated among foreign-born and migrant women, who constitute a substantial share of domestic cleaners and helpers directly employed by households and are the lowest-paid group among care workers.

The COVID-19 pandemic exposed the fragility of de-prioritised and de-funded care infrastructures ( 94 ), revealing the stark consequences of these crucial political choices for the economy and for society as a whole. Care and healthcare workers have been disproportionately affected by the virus, and the lockdown measures enforced across the EU aggravated the strain on households that rely on external care services. The global pandemic appears to have catalysed a revaluation of care work at societal level by sparking conversations on the essential role of intergenerational reproductive labour (both paid and unpaid) in the economy. Harnessing this momentum could see the post-COVID-19 pandemic recovery strategies designed so as to prioritise care on the EU and Member States’ political agendas.

Policy recommendations

• I. 

  Address all underlying factors of the gender pay gap, including the unequal distribution of unpaid care The analysis in the report has shown that the unequal division of care tasks in the household directly affects underlying characteristics of gender inequalities in pay. From this perspective, promoting a fairer distribution of unpaid care within the household would support efforts to reduce the gender pay gap and other gender inequalities.

For a fairer distribution of unpaid care to emerge, a dual approach to public policy should be promoted that would support equal sharing patterns at the family level, on the one hand and accessible quality external services on the other hand. This implies ambitious gender equality goals and the promotion of

positive gender norms to ensure women’s and men’s meaningful participation in all aspects of society.

II. Go beyond the full national-level transposition of the WLB Directive Women are disproportionally engaged in unpaid care work compared to men. Public policies encouraging equal sharing of unpaid care at the household level such as statutory leave policies or flexible working arrangements systems should be gender responsive and incorporate a transformative goal to increase take

94 The post Euro crisis years were characterised by a widespread contraction in social investments due to budgetary cuts and austerity measures adopted to prioritise fiscal consolidation (Bouget et al., 2015; Natali & Vanhercke, 2015; Ronchi, 2018). This had a notable detrimental impact on care infrastructures in several EU countries (European Public Service Union, 2019; Quaglio et al., 2013).

up among men. While countries should ensure the full transposition of the entitlements of the WLB Directive, they should also consider measures to strengthen the existing legal framework on WLB and go beyond the minimum standards set in the Directive. These could include higher levels of compensation for paternity, parental and carers’ leave and a longer period of non-transferable parental leave for men to encourage them to share responsibility for the upbringing of children. In addition, awareness-raising

campaigns are crucial to ensure that citizens know and can exercise their rights.

III. Increase availability, affordability and quality of care services for housework, children, older people and people with disabilities and other chronic conditions

Many Member States are not yet meeting the Barcelona targets on early childhood care and education service provision (agreed in 2002), with gaps evident in the availability of LTC services for older people and people with disabilities. Even where such services exist, affordability can be a serious obstacle to access. Those targets should be revised to be more ambitious for children under three and incorporate qualitative elements. The quality of services and working conditions within the sector are also of concern. Developing a European strategy on social care and social protection could guide the implementation of the European Pillar of Social Rights and complement the WLB Directive. To meet the caring needs of an ageing population, it would be useful to establish a framework to establish EU-wide targets for LTC services,

similar to the Barcelona targets regulating the provision of formal childcare.

IV. Combat both horizontal and vertical gender segregation

Tackling horizontal segregation should entail measures to attract more women into fields dominated by men (STEM, and ICT), as well as efforts to attract more men into female-dominated fields (e.g. care). Defining standards for qualifications and career progression in the care sector is a crucial step in this direction, as it would help to recognise the complexity of these jobs and better compensate their value. Improving pay and career prospects in caring professions is needed to increase the societal value given to caring roles, foster women’s economic independence and attract more men into care professions. Research has shown that higher pay and improved carreer prospects increase the likelihood of men entering female-dominated occupations (Bettio & Plantenga, 2008; Rubery & Fagan, 1995). Another crucial step is to formalise the recognition of skills gained through care work, whether paid or unpaid. This can support informal carers, especially women, in transitioning to other jobs and sectors in the labour market. The EU Gender Equality Strategy 2020-2025 calls for the EU Commission to present the Updated Skills Agenda for Europe and to propose a Council recommendation on vocational education and training, addressing gender balance in the labour market and gender stereotypes in education and training

(European Commission, 2020c).

Vertical gender segregation is equally important and must be addressed if gender equality is to be promoted. Women continue to be underrepresented in decision-making positions at all levels, even in female-dominated sectors and occupations such as education and healthcare. The EU Gender Equality Strategy 2020-2025 encourages the European Commission to adopt the 2012 proposal for a Directive on improving the gender balance on corporate boards, which aims for a minimum of 40 % of non-executive

members of the underrepresented sex on company boards (European Parliament, 2018).

• V. 

  Strengthen the legislative framework to ensure greater transparency in pay Substantial gender pay gaps persist in the EU labour market, partly due to gender segregation in certain sectors and occupations associated with high (men-dominated) or low (women-dominated) pay. In response to these longstanding pay inequalities, the EU Commission is working on a proposal for a Directive on pay transparency for women and men (European Commission, 2020b), with the aim of making pay systems more transparent, improving public understanding of the relevant legal concepts and strengthening enforcement mechanisms. Binding pay transparency measures are needed to tackle the asymmetry of pay information between employees and employers, the lack of information on wage structures, lack of understanding of some legal concepts (e.g. ‘pay’, ‘same work’, ‘work of equal value’) and the lack of gender neutrality in job classification and evaluation systems.

VI. Prioritise investment in care and social infrastructure Higher investments would help to close care gaps and create new jobs in the care and related sectors (e.g. people producing medical equipment, cleaners, delivery drivers, hospitality workers). The COVID-19 pandemic has shown that care jobs are essential for the functioning of society and the economy – now is the time to harness this momentum and prioritise care on the EU political agenda in the longer term. According to the Women’s Budget Group (WBG), investment in care sector ‘yields returns to the economy and society well into the future, in the form of a better educated, healthier and better cared for population, preventing social costs being shifted to other parts of the public sector, improving productivity and helping to prevent the need for greater health and care interventions in the future’ (Women's Budget Group, 2020, p. 5).

EIGE recently presented a tool to advance gender equality through gender-responsive interventions in EU funds, aimed at transforming roles and responsibilities in both formal and informal care structures (EIGE, 2020a). The model draws on three levers – legislative, policy and financial - and supports the formulation of programmes to promote work-life balance in the EU during the next round of the ESF and

the ERDF.

VII. Develop policies to monitor and regulate working conditions in the care and domestic services

Such policies should seek to improve and regulate working conditions, pay and employees’ WLB needs. This may be of particular benefit to migrant women, who are overrepresented in these sectors. The low attractiveness of employment in the care sector results in a severe shortage of professional caregivers, leading to low availability of formal services in most Member States. The size of the care sector means that improving the employment quality of the care workforce would have a direct positive effect on the employment quality of a large number of women in the total economy. It could further contribute to attracting more men into the sector, equalise the concentration of women and men in the care sector, and decrease the shortage of professional caregivers. The Commission’s commitment to putting forward a legal instrument on fair minimum wages for workers in the EU should provide an enormous benefit for

workers in the care sector. Another crucial step would be the ratification of two relevant ILO conventions: • Domestic Workers Convention, 2011 (No. 189). This piece of legislation recognises the significant contribution of domestic workers to the global economy, promotes the protection of their human rights, and encourages minimum wage regulation. This is especially important in times like the Covid-19 pandemic, where domestic workers are in an even more vulnerable position and are particularly impacted by lack of protection.

• Workers with Family Responsibilities Convention, 1981 (No. 156). This piece of legislation offers solutions in terms of a gender equality transformation agenda but is not widely ratified.

VIII. Invest in studies and in-depth analysis of the paid care sector, especially data collection and harmonisation Investment is needed in ad hoc research aimed at exploring the paid care sector in all its guises. More specifically, the following aspects should be analysed: (i) Exploitation: domestic workers are particularly vulnerable to exploitation, as they experience some of the worst working conditions across the care workforce; (ii) Working conditions and low pay: historically, care workers have been confronted with the systematic devaluation of their profession, leading to low wages, dire and precarious working conditions, and lack of social protection.

Monitoring and analysing gender equalities in paid and unpaid care in the EU calls for reliable, comprehensive and comparable data. It is thus necessary to: • Improve the collection of sex and age disaggregated data on relevant issues, such as differences in employment conditions and the sharing of care responsibilities within households. Such data should allow for an intersectional analysis on issues such as education level, family composition, migration background and other characteristics. Several European surveys collect information on participation and time spent on unpaid care work by women and men in a comparative EU perspective (Harmonised European Time Use Survey (HETUS), EQLS, EWCS, EU-SILC, EU-LFS, SHARE), but they all have limitations in timeliness, country coverage, data robustness and comparability between countries. • Encourage the collection of data that goes beyond the heteronormative assumption that households are constituted by a woman and a man, and include more types of family formations. For instance, data on the intra-household sharing of unpaid care activities among same-sex couples is still largely missing. • Support country cooperation for regular and timely collection of large time-use surveys, like HETUS. Time-use surveys should also collect data on earnings in order to assess the linkages between gender inequalities in unpaid care work and pay. • Improve EU data collection in regular and large sample size surveys of care needs, accessibility (availability, affordability, quality) and use of care service. Existing data collection efforts are fragmented across different data sources (e.g. EQLS, EU-SILC, EU-SILC and EU-LFS ad hoc modules, European Health Interview Survey (EHIS)) and are not collected on a regular basis or with a gender perspective.

Annex

• a. 

  What is care work?

Care work includes all activities and occupations that directly and indirectly involve care processes and entail ‘the provision of personal services to meet those basic physical and mental needs that allow a person to function at a socially determined acceptable level of capability, comfort and safety’ (Himmelweit, 2007, p. 581). Activities undertaken without remuneration (unpaid work) are included in the definition of care work alongside those undertaken for pay.

Unpaid care work is the production of care goods and services provided without a monetary reward by family members (parents and relatives), friends and volunteers (Miranda, 2011; Yeandle, Chou, Fine, Larkin, & Milne, 2017). It is increasingly recognised in the socioeconomic literature as an important aspect of economic activity and an indispensable factor contributing to the well-being of individuals, their families and societies (Stiglitz, Sen, & Fitoussi, 2009). Paid care work is performed by a wide range of care professionals, such as nurses, teachers, doctors and domestic workers, for a monetary reward (England & Folbre, 2003; Folbre, 1995, 2006; ILO, 2018).

Both paid and unpaid care work consist of two activities that frequently overlap in practice: direct and indirect care. Direct care activities involve face-to-face, personal care (sometimes referred to as ‘nurturing’ or ‘relational’ care), such as feeding a baby, nursing a sick partner, helping an older person to take a bath, carrying out health checks or teaching young children. Indirect care activities are those such as cleaning, cooking, doing the laundry and other household maintenance tasks (sometimes referred to as ‘non-relational care’ or ‘household work’) that provide the preconditions for personal caregiving (ILO, 2018).

Table 1: Definition of care work used in the report

CARE WORK

Activities and relations involved in meeting the physical, psychological and emotional needs of adults and children, old and young, frail and able-bodied

UNPAID CARE WORK

Caring for people and undertaking PAID CARE WORK

housework without any explicit monetary Care activities performed for pay

compensation

INFORMAL CARE GIVERS CARE WORKERS

CHILDCARE CHILDCARE

Caring for and/or educating children and

grandchildren Primary school and early childhood teachers, childcare workers, etc.

LONG-TERM CARE LONG-TERM CARE Caring for older family members, Personal care workers in health services,

neighbours or friends or those with

disabilities or other chronic health issues nurses

HOUSEWORK HOUSEWORK

Cooking and household chores Domestic workers and helpers

• b. 

  Unpaid care work: additional descriptive statistics

Annex figure 1: Participation rates in unpaid care work as a percentage of population (18+, EU-28, 2016)

Source: EIGE elaboration of EQLS 2016.

Note: Self-declared participation in unpaid care activities daily or at least several times a week; based on EQLS (Q42: ‘In general, how often are you involved in any of the following activities outside of paid work?’). Results do not consider records with unavailable information (don’t know/refusal/not applicable).

Annex figure 2: Employment rate by sex (20-64, EU-28, 2019)

Source: EIGE calculations based on EU-LFS data [t2020_10].

Annex figure 3: Women who are inactive due to care responsibilities, as a percentage of total population (15- 64, EU-28, 2019)

Source: EIGE calculations based on EU-LFS data [lfsa_igar].

Annex figure 4: Frequency of care activities of employed women and men (15+, EU-28, 2000-2015)

Source: EIGE elaboration of EWCS 2000-2015.

Note: Weighted data. Based on valid cases of EWCS 2000, 2005, 2010, 2015. Trend question: ‘In general, how often are you involved in any of the following activities outside work?’ - Caring for and educating your children, grandchildren; Cooking and housework; Caring for older members of the family and those with disabilities.

• c. 

  Gender pay gap

The gender gap in pay is calculated as the difference between the pay of women and men as a percentage of pay of men, using the following formula:

𝐺𝑒𝑛𝑑𝑒𝑟 𝑝𝑎𝑦 𝑔𝑎𝑝 = 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑝𝑎𝑦 𝑀 − 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑝𝑎𝑦 𝑊 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑝𝑎𝑦 ∗ 100

𝑀

Table 2: Measures of gender pay gap used in the report

Source Measure of pay

Unadjusted SES The Eurostat unadjusted gender pay gap (unadjusted gender pay gap) measures the gender pay gap difference between women’s and men’s gross hourly earnings, as a percentage of

men’s gross hourly earnings. This indicator has been recently included in the scoreboard of the European Pillar of Social Rights and is the main indicator used by the European Commission to monitor progress in reducing the gender pay gap in Member States. It is calculated by Eurostat based on the SES, the most specialised and robust dataset on earnings in the EU. The use of hourly wages implies that gender differences in working hours - relevant when assessing gender gaps in labour income - are not taken into account by the indicator, while the use of gross wages implies that the effect of taxation is not taken into account.

Gross hourly earnings are calculated as gross earnings in the reference month/number of hours paid during the same period. Gross earnings include remuneration in cash paid before any tax deductions and social security contributions payable by wage earners and retained by the employer and are restricted to gross earnings paid in each pay period during the reference month. The number of hours paid includes all normal and overtime hours worked and remunerated by the employer during the reference month. Hours not worked but nevertheless paid are counted as 'paid hours' (e.g. annual leave, public holidays, paid sick leave, paid vocational training, paid special leave, etc.).

Overall earnings SES Based on SES data (latest available is for 2014), Eurostat estimates the gap in the total

Source Measure of pay gender gap share of women’s and men’s earnings, combining three elements: (i) average hourly

earnings; (ii) monthly average of the number of hours paid (before any adjustment for part-time work); (iii) employment rate, and its impact on the average earnings of all women of working age - whether employed or not employed - compared to men. By taking into account gender differences in part-time work and employment, it provides a more comprehensive picture of the level of economic independence and labour market opportunities of women and men.

• d. 

  Cross-country correlation analysis: gender gaps in pay and care

Table 3 below presents the correlation coefficients between measures of gender inequalities in pay and in time spent in unpaid care among employees ( 95 ). Results show moderate positive correlations between inequalities in the daily time dedicated to caring for children, grandchildren, elderly people and people with disabilities (direct care work) and the SES 2014 gender pay gap indicators (the gross hourly gender pay gap and, to a lesser extent, the overall earnings gap).

Table 3: Cross-country correlations between inequalities in pay and gender care gaps among employees (Pearson’s r), EU-28

Gender gaps in time spent in care activities between employees (EWCS 2015) Childcare Direct care Housework Unpaid care work

Gender inequalities in pay

Unadjusted gender pay gap (SES 2014) 0.3417* 0.3584* -0.2219 -0.0676

Gender overall earnings gap (SES 2014) 0.2691 0.3250* 0.1603 0.3137

Source: EIGE elaboration based on Eurostat online database [earn_gr_gpgr2; teqges01]; EWCS microdata 2015.

Note: *Significant at least at 10 % level. Gender inequalities in pay: Unadjusted gender pay gap: difference between average gross hourly earnings of female and male employees as a percentage of male gross earnings (SES 2014). Gender overall earnings gap: synthetic indicator: (1) average hourly earnings; (2) monthly average of the number of hours paid (before any adjustment for part-time work); (3) employment rate, on the average earnings of all women of working age - whether employed or not employed - compared to men. Gender care gaps are calculated between employees as the difference between the mean time spent every day on unpaid care by women and men involved in everyday care, as a percentage of the mean time spent by employed men (EWCS2015). Childcare includes caring for and/or educating own children and grandchildren. Direct care includes childcare and caring for elderly relatives/relatives with disabilities. Housework includes cooking and housework. Unpaid care work is the sum of direct care activities and housework.

• e. 

  Multivariate regression analysis and decomposition techniques

Regression analysis: model specification

EU-SILC is a large sample survey aimed at collecting timely and comparable data on income, poverty, social exclusion and living conditions in the EU for persons aged 16+. The survey provides information on household context, personal and job-related characteristics, as well as information on gross

95 Only correlations with gender gaps in time spent in care activities among employed (data available only for daily carers) are presented because correlations with participation rates are not significantly different from zero.

personal income (total and components at individual level) in a 12-month reference period 96 . The 2016 ad hoc module on access to services provides information on time spent on unpaid care work for dependant people, together with the relative number of hours per week provided by individuals aged 16+.

The gender pay gap is measured in terms of log gross hourly income, i.e. employee cash or near cash income, which include wages and salaries paid in main and any secondary or casual jobs, as well as supplementary payments, commissions and bonus payments. As EU-SILC provides yearly gross earnings’ information referring to the last calendar year or the last 12 months (depending on the country) in order to calculate hourly income and to provide consistent information on job-related characteristics, the sample is restricted to employees with only one employment spell (part-time or full-time job) during the income reference period. The hourly income is obtained by dividing the yearly income by the number of months of the employment spell (obtaining the monthly income), and then by the number of hours worked per week on current main and secondary jobs. In order to appreciate the effect of these variables in explaining the observed gender pay gap, two sets of regressions were performed: the first on a benchmark model; the second on an augmented model, which also considered a set of variables proxying unpaid care work among women and men. For both the benchmark and the augmented model, a pooled regression over all EU-28 countries and separate regression for each country were run.

Following Boll et al. (2016) ( 97 ), the benchmark model used a set of explanatory factors (i.e. individual and job-related characteristics, household conditions) for decomposing the gender difference in log hourly average incomes:

• i. 

  Individual characteristics: age and age squared, highest level of education attained (education in six categories - ISCED-2011 0, 1, 2, 3,4, 5+6+7+8), country of birth in three categories (current country of living, any European country except the current one or any other country), health status in five categories (very good, good, fair, bad and very bad).

• ii. 

  Household conditions: marital status (married, unmarried), and if cohabiting with a spouse/partner, partner’s total gross income and categorical variables on employment status (full-time employed, part-time employed, unemployed, disabled, inactive) and level of education (using the same six categories described above).

• iii. 

  Job-related characteristics (which can capture gender segregation): occupation held in the main job into nine categories (ISCO-08 at 1-digit level), sector of employment into 13 categories (NACE rev.2) - the highest disaggregation provided by EU-SILC 2016 microdata for research; the size of the firm in terms of number of employed in four categories (0–10, 11–19, 20–49, 50+). A set of dummy variables was also included on working hours, form of contract

96 Eurostat uses the structure of earnings survey for the purposes of estimating gender pay gap, as it includes detailed information on wages collected directly from enterprises. However, this survey includes little information about individuals covered other than wage. Thus, for the purposes of this project, the decision was to use the EU-SILC survey, which provides much richer information about individuals covered, e.g. in terms of house composition, presence of children and other characteristics relevant for analysis of unpaid care work in relation to pay gaps. However, EU-SILC collects different, and in some ways less granular, information about wages. It also collects wage information directly from households/individuals surveyed, rather than enterprises.

97 This estimate differs from the variables included in the work of Boll et al. (2016) in that it uses information on occupations at one-digit level (instead of two-digit) and no information on over-education (the use of information on occupations at one-digit level doesn’t permit calculation and inclusion of a variable that proxies over-education); working hours are included as a dummy on part-time work (instead of a categorical variable distinguishing full-time, short and long part-time).

and supervisory position: namely, part-time work (versus full-time work); temporary contract

(versus permanent contract); supervisory position (versus no supervisory role).

The EU-SILC survey provides information on earnings, as well as some information on the participation of women and men in unpaid care work. However, this survey also suffers from some limitations that might influence the robustness of the results. EU-SILC is a large sample survey with detailed information on earnings but it includes limited information on the time spent in unpaid care activities by women and men. Unpaid childcare activities have to be proxied with other variables, such as the presence of children in the household or the level of delegation of such activities. This might limit the explanatory power of gender inequalities in unpaid care on gender pay gaps. For this reason, the augmented model includes a set of additional variables to assess the linkages between gender inequalities in pay and in unpaid care work. In particular,

• Information included in the 2016 EU-SILC ad hoc module was used to construct a categorical variable which measures the intensity of adult care (provides care or assistance at least 20 hours a week or more, between 10 and 20 hours, less than 10 hours, and provides no care or assistance).

• Some proxy variables were employed to account for the role played by the unequal division of unpaid childcare activities between women and men. Namely, the presence in the household of children up to six years old - since childbearing usually implies a temporary absence from the workplace for women that is associated with a delay in career progression or even a loss of task-specific human capital (Boll et al., 2016). For those with children below 12 years of age, a categorical variable was included to proxy the intensity of the time spent on unpaid childcare work. This is done by exploiting the information on the presence of children in the household and the amount of hours a week of childcare externalisation (i.e. average weekly number of hours per child of childcare at centre-based services, day care centre, with a professional childminder, grandparents, other household members, other relatives, friends or neighbours). Such a variable includes the following categories: 1. Children under 12 in the household, but do not use external childcare services or help (zero hours of child care externalisation), 2. uses childcare services/help up to 14 hours a week; 3. uses childcare services/help more than 14 hours a week; 4. no children under 12.

It is important to note that neither the benchmark model nor the augmented model include work experience, which empirical literature has shown to be a relevant factor in explaining the gender pay gap. If male workers have, on average, more work experience than female workers (or are more highly qualified with regard to other omitted variables), then the unexplained component (discrimination) will be overestimated.

Table 4: Observed characteristics from the EU-SILC 2016 used in the regression analysis

Personal characteristics and household context Age age; age squared

Country of birth Three categories: current country of living, any European country except the current one or any other country

Health status Five categories: very good, good, fair, bad and very bad Education level Six categories of ISCED (0, 1, 2, 3,4, 5-8) Married Married; unmarried Spouse education level Six categories of ISCED (0, 1, 2, 3,4, 5-8) Spouse employment Five categories: full-time employed, part-time employed, unemployed, disabled, status inactive Spouse personal income Total gross income Job-related characteristics Temporary contract Temporary contract; permanent contract Part-time work Ppart-time; full-time work Occupation Nine categories of ISCO-08 Sector 13 categories of NACE (a; b-e; f; g; h; i; jk; l-n; o; p; q; r-u) Supervisory position Supervisory position; no supervisory position Firm size Four categories: 0–10; 11–19; 20–49; 50+employees Country 28 EU countries Unpaid care variables Have children (0-6) Have children under seven; do not have children under seven Four categories: children under 12 in the household, but do not use external childcare

Childcare (proxy) services or help (zero hours of child care externalisation), uses childcare services/help up to 14 hours a week ; uses childcare services/help more than 14 hours a week; 4. no

children under 12 Household care No information

Adult care Four categories: provides care or assistance 20+ hours a week; 10-20 hours; less than 10 hours; does not provide care or assistance (ad hoc module EU-SILC 2016)

Table 5: Wage regressions: coefficients of proxy variables for unpaid care work, EU-SILC 2016

Referenc

e No children 0-6 yrs old Have children under 12, but zero hours of external care

1 Home care provision >20hrs a week

Variable Have children 0-6 Ext care <=14 hrs Ext care >=14 hrs No children 10-20 hrs <10 hrs week No home care prov Country Men Women Men Women Men Women Men Women Men Women Men Women Men Women EU 28 2.0 *** -0.3 2.6 *** 4.8 *** 1.2 4.1 *** 1.2 * 2.9 *** 1.5 2.0 3.3 2.1 2.6 2.9 ** AT -3.8 2.8 5.8 5.8 3.4 6.2 1.4 6.1 1.4 14.8 -2.6 13.9 -7.2 15.0 BE 0.2 0.0 0.2 3.9 -0.2 -8.5 ** -4.3 0.6 6.6 -3.7 5.9 4.2 7.7 1.6 BG -8.6 -1.6 -28.6 *** 2.0 -13.6 * 6.5 -20.2 *** 14.5 *** -31.4 43.8 *** -23.2 31.8 ** -16.4 32.6 *** CY -3.8 2.9 -4.0 -14.2 *** -7.1 * -19.5 *** -10.8 *** -15.3 *** -0.9 14.4 -1.3 5.2 3.3 3.4 CZ 8.2 ** 0.2 5.4 -0.9 9.8 ** 0.1 0.2 1.5 -9.3 9.4 -8.3 13.1 * -19.4 12.8 ** DE -1.7 2.0 7.7 ** 0.9 -0.2 1.8 3.9 0.7 -6.3 21.1 ** -4.9 21.4 *** -5.4 20.2 *** DK -0.9 6.3 * 8.1 8.0 ** 13.7 ** -15.3 *** 1.7 2.9 1.4 8.7 -2.5 15.7 ** -2.6 14.2 ** EE 0.1 -3.2 2.3 1.7 11.8 3.2 -6.6 0.9 -6.4 9.3 13.9 11.3 13.0 6.2 EL 2.0 2.7 1.7 -0.8 3.9 * 2.6 1.7 -0.2 7.9 1.0 4.0 -0.6 3.7 -2.0 ES 3.6 2.5 -2.7 5.4 -15.1 *** 1.6 -1.4 2.0 0.0 -0.2 17.6 ** 1.8 10.8 * -3.0 FI 0.0 4.5 7.1 3.6 5.5 9.5 3.9 4.5 -8.9 2.3 -3.5 -12.6 -7.0 -2.0 FR 0.4 0.6 0.0 8.3 ** 3.2 3.9 1.0 -1.3 8.3 3.1 12.7 -9.4 12.1 -9.8 HR -0.8 -32.2 *** -1.6 10.6 ** -0.6 6.0 -5.3 * -0.8 17.3 -2.9 9.2 -6.8 16.8 -0.2 HU 5.5 9.6 *** 6.5 * 4.4 7.0 11.0 ** 0.3 12.9 *** 1.2 9.8 -4.8 0.0 -2.2 3.4 IE -6.1 -12.2 *** -4.1 2.8 -2.0 8.1 * -10.0 ** -5.1 4.6 8.6 -4.4 5.3 -2.0 9.3 IT 5.0 ** 5.8 ** 2.6 2.6 1.2 1.9 -1.3 4.1 6.0 1.6 -0.4 10.1 * -0.1 5.7 LT 6.6 -32.5 *** 6.0 32.3 *** -8.6 12.7 * 10.9 22.3 *** 11.9 0.1 8.5 -8.4 13.1 0.7 LU -6.8 ** 2.1 11.8 *** 0.6 3.5 1.0 -5.9 -3.2 28.5 -9.7 26.4 * 8.4 22.8 10.1 LV -1.6 -6.6 * 5.4 8.3 * -13.0 * 3.0 -7.1 * 5.2 * -26.1 * 0.0 11.1 16.2 ** -0.1 9.2 * MT -1.6 8.2 ** -4.0 4.4 -3.0 3.5 -3.3 7.2 * -14.5 11.4 -2.8 2.5 -4.1 6.2 NL 2.0 2.8 -1.4 10.0 *** -5.5 13.5 *** -3.7 5.2 * 2.9 8.3 6.3 6.1 4.1 11.4 PL 2.8 -12.7 *** -2.2 -2.3 -4.5 -0.3 -9.4 ** -8.5 ** 7.1 3.1 12.0 -2.2 11.5 3.4 PT -1.0 -0.5 1.3 8.3 *** 2.8 5.4 * -0.1 7.3 ** 24.9 ** 1.1 0.1 0.5 4.6 2.9 RO 2.2 -5.8 ** 0.0 *** 0.0 *** 2.6 6.1 -1.0 2.9 50.2 ** 17.6 38.3 ** 4.6 33.9 ** -4.6 SE 3.2 -36.3 *** 4.9 -12.2 4.5 -0.2 10.7 * -2.4 -20.8 -34.7 * -17.1 -20.2 -9.5 -16.4 SI -2.7 -23.7 *** -5.9 1.1 -4.2 14.2 ** -6.4 -0.9 9.7 45.6 *** 2.7 40.6 *** -0.4 45.6 *** SK 0.2 3.5 4.0 -0.1 -2.6 -2.1 -3.0 0.8 3.0 2.7 13.2 -2.8 11.5 2.5 UK 9.2 ** 2.3 9.4 ** 7.4 ** 8.2 6.2 * 12.5 *** 6.0 * 3.8 -15.0 ** -1.5 -4.0 1.3 -1.2

Source: EIGE calculations on EU-SILC 2016.

Note: Controlling for: age; country of birth; health status; education level; married; if have spouse (spouse’s income; employment status; education level); temporary work; part-time work; occupation; sector; supervisory position; firm size; (country for pooled regression EU-28). * Significance levels: 10 % *; 5 % **; 1 % ***

84

The Oaxaca-Blinder decomposition

The Oaxaca-Blinder decomposition focuses on the gap in average hourly earnings between female and male workers. It performs a static decomposition of the observed gap into a part (statistically) explained by differences in observed worker and job-related characteristics (women and men may differ in certain wage-determining characteristics). The remaining, unexplained part, which reflects that women and men receive different economic returns for the same characteristic (discrimination) and/or due to the effect of unobserved workers’ characteristics, is not included in the model. Unobserved workers’ characteristics may relate to unobserved wage determinants, such as personal ability, negotiating skills or institutional setting. Other wage determinants that have been proved to influence the wage gap may not be included in the model because of limitations in the data source for the analysis. This is the case for work experience (i.e. duration of working life) and career breaks due to childcare. Therefore, results of the decomposition analysis are influenced by and limited to the information on wage determinants at hand, and the unexplained component should not be equated with discrimination. On the other hand, what is statistically ‘explained’ is not necessarily free from discrimination. Women and men might face unequal access to wage-attractive jobs (e.g. supervisory positions, full-time jobs). Therefore, both the explained and the unexplained part of the gap and their respective origins must be analysed with caution.

The Oaxaca-Blinder decomposition may suffer from selection bias related to the employment decision and produce biased estimates of the pay gap ( 98 ). Women and men might be differently selected into employment, resulting in inconsistently estimated wages (Boll et al., 2016). As argued by Grimshaw and Rubery (2002), in many countries labour market opportunities combined with welfare state policies may mean that only women in the higher salary/earnings ranges stay in the labour market, while women with low expected wages are more likely to opt out of labour market participation. If this is the case, then women who participate may not be representative of the female population. Ferrant et al. (2014) show that in countries where women shoulder most of the responsibility for unpaid care work, they are less likely to be engaged in paid employment.

Formally, the Oaxaca-Blinder-decomposition is carried out in two stages: (i) a regression analysis, and (ii) a decomposition analysis of the structure of earnings. The first stage consists of two separate regressions to estimate the determinants of earnings, one for women (W) and one for men (M). In a log-linear model, log hourly wages (y) are regressed on a range of worker and job-related characteristics, also termed endowments, as they are viewed as observable indicators of productivity differences, partly explaining the wage gap.

𝐾

𝑙𝑛𝑦 𝑀 𝑀 𝑖 = 𝛽 𝑀 0 + ∑ 𝑥 𝑘𝑖 𝛽 𝑀 𝑘 + 𝑢 𝑀 𝑖

𝑘=1

𝐾

 𝑙𝑛𝑦 𝑊 𝑊 𝑊

𝑖 = 𝛽 0 + ∑ 𝑥 𝑘𝑖 𝛽

𝑊 𝑊

𝑘 + 𝑢 𝑖

𝑘=1

In the second stage, the resulting coefficient estimates (𝛽̂) are used to decompose the gender difference in the average wage levels, assuming that the non-discriminatory earnings structure is that of men. The gender pay gap is thus decomposed into an unexplained and an explained part.

𝐾 𝐾

̅̅̅̅̅

𝑙𝑛𝑦 𝑀 ̅̅̅̅̅ − 𝑙𝑛𝑦 𝑊 = (𝛽̂ 𝑀 0 − 𝛽̂ 𝑊 0 ) + ∑ 𝑥̅ 𝑊 𝑀 𝑘 (𝛽̂ 𝑘 − 𝛽̂ 𝑊 𝑘 ) + ∑ 𝛽̂ 𝑀 𝑘 (𝑥̅ 𝑀 𝑘 − 𝑥̅ 𝑊 𝑘 )

𝑘=1 𝑘=1

98 The approach does not include a selection correction when estimating individuals’ earnings. Gender pay gap Unexplained Explained

The size of the explained component represents the part of the gender pay gap determined by gender differences in the observed wage-determining characteristics (e.g. education, occupation, work experience, unpaid care work). The size of the residual unexplained component is instead due to the influence of unobserved characteristics and/or to gender differences in returns for the same characteristic (unequal pay for equal work).

Table 6: Decomposition of the observed gender pay gap among employees (16+), EU-SILC 2016

Explained gender pay gap

Gender Empl. Have Unexplained pay Temporary Part Adult gap TOTAL Age

Country Health Education gender pay

of birth status lev Married

Income

spouse status Education Occupation Sector Supervisory Firm' children

spouse lev work

time

work posit size 0-6 yrs Childcare care Country gap

old

EU-28** 15.6 6.5 -0.9 0.0 0.3 -1.3 0.0 -2.5 2.0 0.1 0.5 2.5 -1.0 4.0 0.9 1.5 0.1 0.0 0.0 0.3 9.0

AT 18.0 15.4 -0.7 -0.1 0.2 0.3 0.1 -4.6 2.9 -0.2 0.0 8.7 1.2 3.7 1.2 3.2 -0.3 0.0 -0.2 - 2.6

BE 7.9 4.2 0.0 -0.1 0.1 -2.0 0.0 -1.8 1.4 0.6 0.4 -0.3 0.6 3.5 1.1 0.6 0.0 0.0 0.1 - 3.7

BG 10.7 -3.4 -1.4 0.0 0.6 -3.0 -0.2 0.1 4.9 -3.5 0.0 -0.4 -4.4 2.4 0.1 1.2 -0.4 0.4 0.0 - 14.2

CY 25.0 3.5 2.0 -0.4 -0.1 -0.7 0.2 -2.8 -3.4 4.2 1.7 0.1 1.6 -1.8 2.7 -0.2 -0.1 0.6 0.1 - 21.4

CZ 25.0 0.8 -1.2 0.0 0.3 -0.1 -0.2 -5.9 2.5 -1.2 0.4 -0.3 0.4 4.1 1.3 1.1 0.3 -0.3 -0.5 - 24.2

DE 19.2 16.8 -1.8 0.0 0.2 0.3 0.1 -2.6 3.9 -0.1 0.6 7.6 -0.9 5.1 0.9 3.8 -0.1 -0.1 0.0 - 2.4

DK 4.2 1.3 -0.4 -0.1 -0.8 -1.8 0.0 -0.9 0.0 0.6 0.2 2.3 -4.2 7.2 0.1 -0.9 0.0 0.1 0.0 - 2.9

EE 20.7 0.8 -1.3 0.4 0.2 -4.2 0.1 -1.8 -2.4 2.6 -0.3 0.9 -4.9 8.6 1.3 0.6 0.0 0.4 0.6 - 19.9

EL 6.8 1.3 1.1 -0.2 0.0 -1.3 0.1 -2.8 2.2 0.3 0.2 0.0 -1.5 1.1 0.7 1.5 0.0 -0.2 0.0 - 5.5

ES 12.8 3.5 0.4 0.5 0.4 -1.5 -0.2 -3.5 1.1 1.0 1.1 -0.3 -1.1 1.9 1.2 2.1 0.0 0.1 0.3 - 9.3

FI 17.0 4.7 -1.1 0.0 0.1 -0.6 0.0 -1.3 -0.4 -0.3 0.6 0.0 2.6 2.2 1.7 1.3 0.0 0.1 -0.2 - 12.3

FR 13.8 7.6 -1.1 0.0 0.3 -0.8 -0.1 -1.8 1.0 0.1 0.7 2.0 -0.5 6.3 0.5 1.1 0.0 0.0 0.0 - 6.2

HR 13.0 -0.1 -0.6 0.2 0.5 -1.7 -0.1 -1.5 -0.6 0.5 0.0 0.0 -2.2 2.6 1.3 1.0 0.0 0.1 0.3 - 13.2

HU 11.3 0.3 -1.1 0.0 0.9 -1.4 0.0 -1.9 0.5 -0.3 0.5 -0.2 -1.9 3.0 0.4 1.5 0.3 0.0 0.0 - 11.0

IE 9.7 -2.7 0.5 -0.1 -0.4 -0.5 0.5 -3.7 1.9 1.4 -0.1 -3.1 -2.9 1.6 1.3 0.9 -0.2 0.3 0.0 - 12.4

IT 13.3 4.8 -0.9 0.1 0.0 -1.6 0.1 -3.5 0.2 0.8 0.6 3.6 -2.8 5.6 0.8 1.7 0.2 0.0 -0.1 - 8.5

LT 13.6 -5.1 -0.5 0.0 1.7 -3.8 1.4 -2.3 -1.3 0.4 -0.2 -0.5 -1.6 1.5 0.6 -0.8 0.3 0.1 0.0 - 18.7

LU 8.2 1.8 -0.4 0.6 0.1 -0.9 0.0 -3.4 3.1 0.0 -0.3 1.2 -1.0 0.2 1.3 1.7 -0.2 -0.1 -0.1 - 6.4

LV 17.8 0.3 -0.1 0.0 1.3 -4.2 0.2 -1.7 -1.4 2.5 -0.1 0.3 -3.4 5.2 0.1 0.9 -0.1 0.4 0.2 - 17.6

MT 5.8 -2.3 1.8 0.0 -0.1 -5.3 -0.2 -2.2 3.6 0.8 -0.1 0.5 -1.4 -0.8 0.9 0.0 0.0 0.0 0.1 - 8.1

NL 17.0 9.4 0.7 -0.1 0.1 -0.4 0.1 -1.8 1.5 -0.2 0.2 1.5 1.6 3.9 2.1 0.5 0.0 0.1 -0.1 - 7.7

PL 13.2 -1.1 -0.3 0.0 0.2 -3.4 0.1 -3.4 1.6 0.4 0.4 -0.3 -0.4 2.4 0.5 0.8 0.0 0.0 0.2 - 14.3

PT 15.4 2.0 -0.4 0.0 0.6 -2.6 0.0 -1.3 -0.5 1.0 0.1 0.7 -2.8 5.4 0.9 1.0 0.0 0.0 -0.2 - 13.4

RO 11.3 -4.9 0.0 0.0 0.3 -1.7 0.0 -10.0 4.0 0.2 0.0 0.0 -0.1 1.2 0.2 0.9 0.0 0.0 0.0 - 16.2

SE 16.3 -2.6 -0.9 -0.5 0.2 -0.4 -0.1 -2.3 0.8 0.2 0.9 -0.3 -1.4 -0.8 1.0 0.9 0.1 -0.2 0.1 - 18.9

SI 10.9 -3.6 -1.0 -0.2 0.6 -3.7 -0.1 -2.1 0.8 0.0 0.2 0.2 -2.6 3.9 1.1 -0.6 0.0 0.0 -0.1 - 14.5

SK 17.7 -0.9 -0.6 0.0 0.3 -1.1 0.1 -4.0 1.2 -0.2 0.2 -0.2 0.1 1.8 0.2 1.0 0.0 0.0 0.1 - 18.7

UK 18.9 11.9 -1.0 0.0 0.4 0.0 0.1 -4.8 3.1 0.2 0.1 4.0 2.6 5.1 1.1 0.8 0.1 0.0 0.0 - 7.0

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Source: EIGE calculations on EU-SILC 2016.

Note: Difference between female and male hourly income as % of male hourly income. Gross hourly income: employee cash or near cash income. Pooled regression.

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• f. 

  Focus group discussion

Focus groups were organised and conducted in 11 EU Member States (one pilot focus group in HR, plus 10 covering DK, DE, EE, IE, FR, NL, PT, RO, SK, FI). This activity was part of the fieldwork related to discussions on the externalisation approach adopted in each country and aimed to gain an in‐depth understanding of the impact of social issues on the policy and individual factors relating to the externalisation of care work and its effects. The participants had diverse family circumstances and care needs.

Piloting and data collection took place between December 2019 and the beginning of February 2020 in the relevant Member State language. The focus group in Croatia was primarily to test the methodology. As no particular issues occurred, no changes were needed. The recruiting and selection criteria identified, as well as the guiding questions, allowed for smooth and effective organisation and discussion. Data from the pilot focus group was thus included in the analysis. Focus group discussions were carried out by experienced national researchers acting as moderators. They were supported by the core team, who prepared and organised the focus group discussions according to common guidelines and a detailed protocol on informed consent and confidentiality. In order to be eligible to participate in the focus group discussion, participants (both women and men) had to be employed and already making use of some level of externalised care. These eligibility criteria, together with a tight schedule, made the recruitment phase particularly challenging. However, national researchers were able to guarantee an effective mix of participants, presenting personal experiences and individual needs. The 11 focus groups involved 95 participants (67 women and 28 men) from diverse family circumstances (i.e. lone parents, households with children, with people with disabilities and other chronic health issues). They represented different care needs (e.g. day care for children and/or relatives with disabilities and/or older relatives, cleaning support), different age groups, education levels, employment status and socioeconomic backgrounds.

The main research questions explored the context and perceptions of externalisation of care. They aimed to investigate the state of play in households in terms of sharing of care responsibilities, decision-making on externalisation, the organisation of externalised care services, general satisfaction with services/externalisation, effect(s) on the household dynamics/gender roles, opportunities and constraints linked to externalisation.

• g. 

  The International Social Survey Programme (ISSP)

The International Social Survey Programme (ISSP) is an ongoing programme of cross-national collaborative research. Since 1985, it has gathered information yearly on individual behaviours, preferences, opinions, and attitudes among population samples across the world. The programme implements thematic modules that are repeated with slight changes every 8-10 years. For example, the existing rotating modules investigate topics related to religion, national identity, role of government, social inequalities, etc.

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The module ‘Family and changing gender roles’ first appeared in 1988 and was replicated in 1994, 2002, and 2012. It gathers information from representative samples of national populations on topics related to gender ideologies, family models, gendered division of household work, power and decision-making in couples, work-family conflict, happiness and satisfaction (Scholz, Jutz, Edlund, Öun, & Braun, 2014). The ISSP collects data through standardised questionnaires employing mixed modes (mainly CAPI and PAPI face-to-face interviews, occasionally postal survey and web survey). The sampling procedure is stratified random sampling (partly simple, partly multistage).

Typologies of gender contracts based on ISSP

The last edition of the ISSP module on ‘Family and changing gender roles’ includes the question: In your household who does the following things ...? (doing laundry; care for sick family members; shop for groceries; household cleaning; preparation of the meals; small repairs). For each task, the respondent could select one of the following options: always me; usually me; about equal or together; usually my spouse/partner; always my spouse/partner; done by a third person. The proposed measure of ‘gendered division of care’ is computed by collapsing the category always/usually. By combining the answers with the respondent’s sex (

99 ), four typologies of gender contract were obtained: couples where women do most of the care activities; couples where the man does most of these tasks; couples where the partners tend to share housework chores equally; couples that tend to externalise these tasks. The list of care tasks changed over time, thus only the tasks listed in the data collection of 1994, 2002 and 2012 were considered: doing the laundry; care for sick family members; shop for groceries; small repairs. ‘Small repairs’ was excluded because, unlike the other tasks, it is an occasion, rather than routine, activity.

Attitudes to gender equality

Attitudes to gender equality refers to the individual’s level of support for a gendered division of paid work and family responsibilities, under which men are primarily associated with the public sphere and paid work and women with unpaid work and the private sphere (Davis & Greenstein, 2009, p. 89). To grasp such attitudes through quantitative methods, survey programmes use items investigating attitudes to gender roles. For the purpose of this work, Figure 17 of the report uses an index of attitudes to gender equality, built taking into account the literature in the field of gender roles, in particular the empirical studies using ISSP, which also assessed the comparability of this measurement across cultural contexts (Constantin & Voicu, 2015; Lomazzi & Seddig, 2020 ).

The index of attitudes to gender equality is computed in two steps:

• 1) 

  As the mean of the answers to the following four items (only cases with at least three valid answers out of the four items were included):

  To what extent do you agree or disagree ...? a) A preschool child is likely to suffer if their mother works. b) All in all, family life suffers when the woman has a full-time job. c) A job is all right, but what most women really want is a home and children.

99 ISSP does not collect information on the sex of the respondent’s partner and it is not possible to obtain information on same-sex households.

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• d) 

  A man's job is to earn money; a woman's job is to look after the home and family. Answer categories: Agree strongly (1), Agree (2), Neither agree nor disagree (3), Disagree (4), Disagree strongly (5). The resulting index scores range from 1 (traditional attitudes) to 5 (egalitarian attitudes).

• 2) 

  The scores were recorded in three levels of support for egalitarian gender roles: - Traditional attitudes to gender equality: scores from 1 to 2.33.

  • - 

    Moderately egalitarian attitudes to gender equality: scores from 2.34 to 3.67. - Strongly egalitarian attitudes to gender equality: scores from 3.68 to 5.

Sample sizes

ISSP collects information from the general population aged 18-74. For the purposes of this report, valid cases of the sub-sample of respondents belonging to a cohabiting couple were used. This group is identified by combining respondents who declare being married or in civil partnership or in a steady relationship AND affirm their cohabitation with their partner.

Table 7: ISSP sample sizes by wave, country and sex of the respondent

1994 2002 2012 M F Total M F Total M F Total

BE 731 723 1454

BG 324 439 763 319 388 707 277 345 622

CZ 339 316 655 300 549 849 547 622 1169

DK 337 382 719

DE 1344 1216 2560 509 523 1032 579 575 1154

IE 267 306 573 318 424 742 316 526 842

ES 719 787 1506 727 793 1520 834 890 1724

FR 596 1023 1619

HR 272 344 616

LV 233 308 541

LT 306 331 637

HU 474 474 948 295 337 632 293 245 538

NL 508 614 1122 414 415 829 442 450 892

AT 298 355 653 502 719 1221 352 376 728

PL 521 522 1043 345 407 752 330 373 703

PT 256 272 528

SI 352 375 727 352 379 731 338 333 671

SK 384 347 731

FI 377 443 820

SE 402 471 873 368 420 788 346 377 723

UK 284 304 588 499 586 1085 246 201 447

Total 5832 6179 12011 4948 5940 10888 8392 9486 17878

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• h. 

  The paid care sector

There is no universal agreement on the types of labour that should be included in the definition of care work (Duffy & Armenia, 2019). One reason is related to the unavailability of detailed information on sectors (NACE ( 100 ) at the three-digit level) and occupations (ISCO at the four-digit level). Eurostat does not provide such detailed information due to collection and sample size issues. NACE classification of sectors does not permit an appropriate estimation of the number of people employed in household services (see EFSI (2018)). Therefore, existing research on paid care work varies in its definitions of care, as well as in the approaches and operationalisation to estimate its size. Some rely solely on information on sectors (Duffy & Armenia, 2019; European Commission, 2018b) or on occupations (EFSI, 2018). Others take a cross-sectional approach, using information on both sectors and occupations (ILO, 2018).

In order to estimate the size of the total care workforce in the EU, this report follows the approach used by ILO (2018). The ILO definition of the care workforce includes workers who provide direct personal care (e.g. doctors, nurses, teachers) and workers who provide indirect care in or for a household(s) (e.g. domestic cleaners, cooks, gardeners). This definition also includes workers employed in care sectors (education and healthcare) who are not directly involved in care provision (e.g. administrative officers, legal and IT professionals), as they support the provision of care services.

More specifically, the ILO definition includes: (i) All those employed in the care sectors – Education (NACE Section P), Health and social work

(Section Q); (ii) Workers in core care occupations (ISCO 22; 23; 32; 53)( 101 ) but employed in sectors other than

education, and health and social work; (iii) Domestic workers (i.e. those employed in Section T-97) ( 102 ).

However, the total care workforce estimated by the ILO definition is not a homogenous group: ‘there are differences and hierarchies among care workers, including in terms of pay, conditions and status’ (ILO, 2018). In addition, the total care workforce includes a wide range of occupations, comprising workers who are not directly involved in care and care workers with high-level qualifications (e.g. doctors, university and higher education teachers). Thus, an analysis at aggregate level of the care workforce, or even among the sole core care occupations, would average out differences and hierarchies among care workers.

After a brief overview of the total care workforce, chapter 4 carries out an in-depth investigation on a sub-section of care occupations. This sub-section of care occupations is included in the ILO

100 NACE rev. 2 classification of economic activities. 101 22 – Health Professionals; 23 – Teaching Professionals; 32 – Health Associate Professionals; 53 – Personal Care Workers.

102 This operationalisation of domestic work only includes employees directly employed by private households. It excludes workers employed by firms providing household services (e.g. workers in Section N (81.1 and 81.2), Section S (96.01 and 96.02) or Section Q (88.10).

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definition and can be viewed as an extension of women’s care roles within their own homes, which could be delegated to household caregivers. To estimate the size of the total care workforce, data from the EU-LFS was used. In particular, exploiting the ISCO three-digit information available in EU-LFS microdata (excluding BG, MT, PL, SI, as data on occupations is not available at the three-digit level for these countries), the focus is on three selected occupations: • Childcare workers and teachers’ aides (ISCO code 531); • Personal care workers in health services (ISCO code 532); • Domestic cleaners and helpers (proxied by those in ISCO code 911 working section T of the

NACE classification).

Statistics on selected care sector occupations

Annex figure 5: Selected care occupations: distribution by personal characteristics and income deciles (%, 15+, EU-28, 2018)

Source: EIGE calculations based on EU-LFS microdata.

Note: BG, MT, PL, SI not included, because no data was available for ISCO three-digit;

**Data on wage deciles does not include CZ, ES, AT, SI, FI, SE, due to lack of availability.

Annex figure 6: Share of part-time work and main reason for choosing it, in selected care occupations and total economy (%, 15+, EU-28, 2018)

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Source: EIGE calculations based on EU-LFS 2018 microdata.

Note: Share of part-time work calculated as employed in part-time jobs over total employed of the respective occupation. Percentage distribution of main reasons for part-time work: in education (person is undergoing school education or training); care responsibilities (looking after children or incapacitated adults; other family or personal reasons); not find full-time job (person could not find a full-time job); other reasons (own illness or disability; other reasons). BG, MT, PL, SI not included because no data is available for ISCO threedigit.

Annex figure 7: Share of temporary work and main reason for choosing it, in selected care occupations and total economy (%, 15+, EU-28, 2018)

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Source: EIGE calculations based on EU-LFS 2018 microdata.

Note: Share of temporary work calculated as employed in temporary jobs over total employees of the respective occupation. Percentage distribution of main reasons for temporary work: training/apprenticeship (it is a contract covering a period of apprenticeship or training, e.g. trainees, internships, research assistants; it is a contract for a probationary period); not find permanent job (person could not find a permanent job); not want permanent job (person did not want a permanent job). BG, MT, PL, SI are not included because no data was available for ISCO three-digit.

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Annex figure 8: Share of workers on atypical hours in selected care occupations and total economy (15+, EU-28, 2018)

Source: EIGE calculations based on EU-LFS 2018 microdata.

Note: Share of workers on atypical hours calculated as employed who work on atypical hours over total employed of the respective occupation. BG, MT, PL, SI not included because no data is available for ISCO three-digit.

Annex figure 9: Working conditions in selected care occupations and total economy (15+, EU-28, 2018)

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Source: EIGE calculations based on EU-LFS 2018 microdata.

Note: Reasons for looking for another job: increase hours worked (seeking an additional or another job to work more hours); better working conditions, other reasons – omitted. Hours of work in main and secondary job in reference week. Received education or training: person has received formal or informal education or training during the four weeks prior the interview. BG, MT, PL, SI not included because no data is available for ISCO three-digit.

Appendix: Policy boxes

Box 1 – Some examples of incentives to fathers’ take-up of parental leave

GERMANY: The German parental leave (Basiselterngeld) includes two fully paid bonus months if both parents take at least two months of leave. The bonus is called ‘partner months’ (Partnermonate).

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FINLAND: The parental leave can be taken part-time, from 40-60% of full-time hours, only if both parents take the part-time leave.

CROATIA: If both parents take parental leave, two additional fully paid months of leave are provided.

ITALY: Where the father takes at least three months of parental leave, the leave period can be extended to 11 months.

ROMANIA: Parental leave is a family entitlement and if both parents are eligible, at least one month should be granted to the non-claiming parent. If this does not happen, the total period of leave is reduced to 11 months.

SWEDEN: Despite the transferability of the parental leave, 90 days are reserved for each parent and cannot be transferred to the other.

Source: EIGE Annual Review 2019 - International network of leave policies and research

Box 2 - Italy ‘Bonus Asili Nido’ (kindergarten voucher)

According to L. 232/2016 of 11 December 2016, families with children born after 1 January 2016 are entitled

to a contribution for the payment of fees to attend public and private nursery schools. The benefit is provided after the submission of documents that prove the child’s enrolment in a childcare facility. The total amount of the Bonus Asili Nido is EUR 1 500 per year (11 months), corresponding to about EUR 136.37 per month.

Source: MISSOC database https://www.missoc.org/missoc-database/comparative-tables/results/ ;

INPS https://www.inps.it/nuovoportaleinps/default.aspx?itemdir=51105

Box 3 - France: Complèment de libre choix du mode de garde (CMG) (supplement for free choice of childcare)

The French approach to designing and implementing family policies has evolved from a male breadwinner model where policies favour women’s inactivity through compensation of children’s costs for families, to a model focusing on work and family reconciliation for both parents and their ‘freedom of choice’. Since the 1990s, policies have promoted the diversification of childcare and the development of both public ‘collective’ childcare and ‘individual’ childcare (childminders working at their or the parents’ home). Financing of these childcare policies comes mainly from the social security system (Caisse Nationale d’allocations familialies, CNAF). The CMG is funded by the Caisse d’allocations familialies (CAF) and aims to support families by refunding parents’ childcare expenditure. It amortises childcare costs for working parents of children under six years old. It is paid if the parents externalise childcare through: i) Employing a registered childminder; ii) Using a licensed organisation that employs a registered childminder, if the child uses day care services for a minimum amount of time (16 hours per month); iii) Using a small day care centre and provided that the child attends the centre for at least 16 hours per month. The benefit to parents includes: i) partial coverage of childcare costs – the rate varies depending on the number and age of children, household income and household composition (additional support is provided for single parents); ii) total or partial coverage of employer's social contributions. Source: MISSOC database: https://www.missoc.org/missoc-database/comparative-tables/; CAF http://www.caf.fr/allocataires/droits-et-prestations/s-informer-sur-les-aides/petite-enfance/lecomplement-de-libre-choix-du-mode-de-garde CLEISS: https://www.cleiss.fr/docs/regimes/regime_france/an_4.html#cmg

Box 4 - UK: tax-free childcare

Through this measure, the government aims to contribute to reducing childcare costs with an amount equivalent to average tax expenditure for households – thus, ‘tax-free childcare’. The share of the tax contribution is 20 % of costs. Tax-free childcare establishes that for every GBP 0.80 paid by families for formal/registered childcare, the state will contribute GBP 0.20. This results in a tax allowance/deduction from

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the costs of childcare. The benefit is accessible to any working family with children under 12. Although it depends on the working status of parents, it relies exclusively on public, rather than employer, intervention. The benefit is also available to self-employed parents. Sources: https://www.gov.uk/tax-free-childcare ; https://www.gov.uk/government/news/tax-free-childcare 10-things-parents-should-know

Box 5 – the Netherlands: Dutch Childcare Act, employer contributions

Since the adoption of the Dutch Childcare Act (2005), childcare has had a tripartite financing system, with the cost of childcare split between parents, governments and employers. From 2007, employers have been obliged to pay a percentage of the salary of all employees to the government to cover the costs of childcare. In addition, employees have the right to be refunded by their employer for one-third of childcare costs for children under 12. In the case of two employed parents, each parent will receive one-sixth of the childcare cost.

Source: https://www.government.nl/documents/leaflets/2011/10/13/fact-sheet-childcare-and-childcareallowance

Box 6 – UK: workplace nurseries exemption

In the UK, employers that decide to set up an in-company nursery facility are exempt from the payment of tax and national insurance on the value of the nursery, provided the service complies with certain conditions. The care in-place facility should satisfy the formal requirement of an appropriate registering organisation (this depends on the region of the UK where the company operates). In addition, it must be available and accessible to all employees, their children and children for whom they have parental responsibility. The employers offering the childcare facility may also claim tax relief for the day-to-day costs of the nursery, such as rent, heating, lighting, staff wages and play equipment. Source: https://www.gov.uk/expenses-and-benefits-childcare/whats-exempt

Box 7 - Denmark: ‘free place subsidy’ as an example of affordability of the centres

I n Denmark, a child is eligible for a free place subsidy for public childcare services, private childcare (except private childcare run by a childminder) if the total household income is less than about EUR 24 290 per year (corresponding to DKK 181 500). The income limits are raised by EUR 936 (DKK 7 000) for each additional child under 18 living at home and by EUR 8 498 (DKK 63 506) for single parents. If the annual household income is between EUR 24 290 and EUR 75 450, the parents can apply for a partially funded place subsidy. Source: https://international.kk.dk/artikel/cost-childcare-services

Box 8 – Romania: parents and relatives caring for children or adults with severe disabilities, as formal carers Law 448/2006 on the promotion of the rights of people with disabilities, updated in 2019, stipulates that a person (adult or child) with a severe handicap is entitled to either i) a personal assistant or ii) a professional personal assistant (certified carer). While the first category of personal assistants may care for either an adult or a child, the second category must be certified and provide care and protection solely to adults. In order to work as a personal assistant (first category of formal carers), a person must meet several criteria, such as adult age, clean criminal record and a minimum education level (graduation from compulsory education). The law exempts spouses and relatives (to the fourth degree of affinity) from the minimum education requirement. The personal assistant is employed under an individual contract with the city hall of the locality where the person (child or adult) with the severe handicap is domiciled or resides. Source: http://anpd.gov.ro/web/wp-content/uploads/2019/06/legea-448.doc

Box 9 - The Netherlands: PGB (persoongebonden budget – personal budget)

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The PGB (persoongebonden budget – personal budget) was introduced in 1995, giving recipients a choice between a cash allowance and services. The recipient can opt not to obtain care provision in kind but instead to receive a personal care budget (persoonsgebonden budget, PGB) that allows them to purchase care independently. The amount of the personal care budget depends on the care required. The PGB is conditional on obtaining the services of a formal carer. The person in need of care buys customised care and sends the bills to the Social Insurance Bank (Sociale Verzekeringsbank, SVB) which transfers the amount of the bill to the caregiver.

Source: MISSOC Database

Box 10 - Italy – Law No. 18 of 11 February 1980 on constant attendance allowance (Legge 11 Febbraio 1980, n. 18 –Indennità di accompagnamento agli invalidi civili totalmente inabili) The constant attendance allowance (assegno di accompagnamento) is a special non-contributory benefit (not subject to means testing) granted to people with disabilities and those who need the help of a third party to move around, or who require permanent assistance in order to carry out basic daily activities. It requires a 100 % level of dependency for both cash (EUR 517.84 per month) and in-kind benefits via different forms (home care services, including help, meal delivery, medical treatment and nursing care; possibility of stay in a day care centre; residential care in the most serious cases; provision of technical equipment). No specific requirements on the use of the cash benefit have been established. Source: MISSOC Database

Box 11 - Ireland: Irish Health Information and Quality Authority (HIQA)

Since 2009, HIQA has been legally responsible for the registration and inspection of all public, private and voluntary nursing homes and residential care services for older people in Ireland. Its National Quality Standards for residential care settings for older people in Ireland cover: the rights of older people, protection, health and social care needs, quality of life, staffing, the care environment, management and governance. They include supplementary criteria applying to units that specialise in the care of people with dementia. Each residential setting for older people is now required by law to register with HIQA, which must then verify that each centre is fit to operate. This is done through the process of ongoing inspections (announced and unannounced) from HIQA staff. Inspectors consult with managers, staff and residents, (if residents wish to be interviewed), and families. The focus is on the experience of the resident living in the nursing home. An inspection report, naming the residential centre, is posted on the HIQA website, which also has advice on how to choose a suitable nursing home and the standards that should be expected. Source: www.hiqa.ie

Box 12 - Sweden: core values in LTC

The national core values for LTC services is relatively new legislation in Sweden (from 1 January 2011). It states that care must focus on the dignity and well-being of older people, i.e. care should protect and respect everyone’s right to privacy and physical integrity, autonomy, participation and personalisation. Under this legislation, municipalities will have to develop a new dignity guarantee and this will be checked by the public authorities. The National Board of Health and Welfare works with the national core values and will contribute to ensuring that they are embedded and applied in practice. The work consists of training material, guidance at local level, website development and information material, a national instrument for needs assessment, etc.

Source: www.socialstyrelsen.se/aldre/nationellvardegrund

Box 13 - Finland: tax credit for household expenses

The tax credit for household expenses reduces the amount of tax payable on a long list of housework activities undertaken at home and in a holiday home. Cleaning and household expenses include the

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following: cleaning; cooking; laundry, ironing and garment care; yard maintenance and gardening; snow shovelling. The tax credit operates on central government taxes. If the reduction is greater than the amount of central government income tax, local government taxes can be reduced as well. Source: VERO (Finnish Tax administration) https://www.vero.fi/en/individuals/tax-cards-and-taxreturns/income-and-deductions/Tax-credit-for-household-expenses/

Box 14 - Sweden: tax deduction on household services

In July 2007 the Swedish government introduced a tax deduction on household services (Rengöring, underhåll och tvätt, RUT) which covers cleaning, laundry, moving services, gardening, childminding and care services. RUT services must be carried out in the customer’s home (or their parent’s home, provided that the client pays for this). The work cannot be performed by a relative. Deductions for RUT services are up to EUR 2 500 per year. The taxpayer can receive a tax credit of 50 % of the labour cost (including VAT) of the household services. The service must be provided by a registered company (or a single person who has their own registered company).

Source: Skatteverket (Swedish Tax Agency) https://www.skatteverket.se/servicelankar/otherlanguages/inenglish/businessesandemployers/declaringtaxes businesses/rotandrutwork.4.8dcbbe4142d38302d793f.html

Box 15 – Belgium: vouchers for housework activities

On 1 January 2004, the Belgian federal government launched a system (still ongoing) of service vouchers (dienstencheques/titres-services) in an attempt to boost job creation by promoting the demand for domestic services and proximity services. The voucher for housework activities may be used exclusively for housework carried out within or outside the user’s home. All residents in Belgium can buy service vouchers in order to purchase domestic help, including the following activities: cleaning, laundry, ironing, preparation of meals, shopping, etc. Care of dependent people is excluded, except for accompanying people with restricted mobility requiring transportation. However, nothing prevents a dependent person from benefitting from the services mentioned above under the service voucher system (e.g. house cleaning), when this complements another type of care support. The Belgian voucher relies on a fixed price and the list of authorised activities is strictly limited to housework. The activities paid with service vouchers are carried out by employees working for a company that is recognised as a service voucher company. Source: https://www.eurofound.europa.eu/data/tackling-undeclared-work-in-europe/database/servicevouchers-belgium

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