# Who took care of what? The gender division of unpaid work during the first year of the COVID-19 pandemic in France

Marta Pasqualini, Marta Dominguez Folgueras, Emanuele Ferragina, Olivier Godechot, Ettore Recchi, Mirna Safi

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## To cite this version:

Marta Pasqualini, Marta Dominguez Folgueras, Emanuele Ferragina, Olivier Godechot, Ettore Recchi, et al.. Who took care of what? The gender division of unpaid work during the first year of the COVID-19 pandemic in France. Demographic Research, 2022, 46, pp.1007-1036. 10.4054/DemRes.2022.46.34. hal-03677747

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DEMOGRAPHIC RESEARCH

VOLUME 46, ARTICLE 34, PAGES 1007–1036
PUBLISHED 24 MAY 2022

https://www.demographic-research.org/Volumes/Vol46/34/
DOI: 10.4054/DemRes.2022.46.34

*Research Article*

Who took care of what? The gender division of
unpaid work during the first year of the COVID-
19 pandemic in France

Marta Pasqualini

Olivier Godechot

Marta Dominguez-Folgueras

Ettore Recchi

Emanuele Ferragina

Mirna Safi

© 2022 Marta Pasqualini et al.

This open-access work is published under the terms of the Creative Commons Attribution 3.0 Germany (CC BY 3.0 DE), which permits use, reproduction, and distribution in any medium, provided the original author(s) and source are given credit.

See https://creativecommons.org/licenses/by/3.0/de/legalcode.
# Contents

<table><tr><td>1</td><td>Introduction</td><td>1008</td></tr><tr><td>2</td><td>Background</td><td>1009</td></tr><tr><td>2.1</td><td>The COVID-19 lockdowns' effect on the domestic division of work and care</td><td>1009</td></tr><tr><td>2.2</td><td>Context: A story of two lockdowns</td><td>1013</td></tr><tr><td>3</td><td>Data, variables, and methods</td><td>1017</td></tr><tr><td>3.1</td><td>Participants</td><td>1017</td></tr><tr><td>3.2</td><td>Variables</td><td>1018</td></tr><tr><td>3.3</td><td>Methods</td><td>1019</td></tr><tr><td>4</td><td>Results</td><td>1020</td></tr><tr><td>4.1</td><td>Descriptive findings</td><td>1020</td></tr><tr><td>4.2</td><td>Couples' divisions of domestic and care work: time, work, educational gaps and tasks</td><td>1021</td></tr><tr><td>5</td><td>Discussion and conclusions</td><td>1028</td></tr><tr><td></td><td>References</td><td>1031</td></tr></table>
# Who took care of what? The gender division of unpaid work during the first year of the COVID-19 pandemic in France

Marta Pasqualini<fnref n="1" />

Marta Dominguez-Folgueras<fnref n="2" />

Emanuele Ferragina<fnref n="2" />

Olivier Godechot<fnref n="2" />

Ettore Recchi<fnref n="3" />

Mirna Safi<fnref n="2" />

## Abstract

## BACKGROUND

France was one of the first countries implementing lockdown measures to mitigate the spread of COVID-19. Since families spent more time at home, household and care workloads increased significantly. However, existing findings are mixed in terms of whether this situation contributed to a more gender-egalitarian division of unpaid work.

## OBJECTIVE

This paper explores the division of domestic work within couples across two different COVID-19 lockdowns and compares them to the out-of-lockdown period in France. We use the theoretical lenses of time availability, relative resources, and ‘doing gender’ to make sense of these changes.

## METHODS

Our longitudinal analyses rely on an original panel study we collected in France between April 2020 and April 2021. It includes a sample of 1,959 observations (of 809 individuals living in couples). We employ the different types of restrictions to mobility and social life imposed during the first year of the pandemic as a contextual background, within which we measure the main drivers of change in the division of unpaid work within couples. We use individual fixed effect regression models to estimate changes in men’s

<footnote n="1">¹ Sciences Po, OSC-CNRS, Paris, France, and Sapienza Università di Roma, Rome, Italy.
Email: marta.pasqualini@uniroma1.it.</footnote>

<footnote n="2">² Sciences Po, OSC, and MaxPo CNRS, Paris, France.</footnote>

<footnote n="3">³ Sciences Po, OSC and MaxPo, CNRS, Paris, France and Migration Policy Centre, Robert Schuman Centre for Advanced Studies, EUI, Florence, Italy.</footnote>
share of unpaid work by time, changes in work conditions, partners' educational gaps, and types of domestic tasks.

## RESULTS

The first lockdown contributed to a slight rebalancing of unpaid work within couples. However, our results show an impact of both absolute and relative time availability on men's share of unpaid work and that the overall rebalancing of unpaid work hides highly gendered patterns. Indeed, we find men doing more shopping and women doing more child care. This gendered division of labour is slightly more prevalent among couples in which the man is more educated than his partner.

## CONTRIBUTION

Our findings suggest the reaffirmation of traditional gender roles even during the exceptional first year of the pandemic in France.

# 1. Introduction

France was one of the first countries to implement strict lockdown measures to mitigate the spread of COVID-19. These measures dramatically affected many aspects of social life, such as employment conditions, time management, and remote work. The severe restrictions implemented during the first lockdown also included the total closure of schools and child care facilities. Consequently, people spent more time at home, and care workloads within the household increased significantly.

Previous studies have analysed the domestic division of work and care during the pandemic in a variety of national contexts. They interpret lockdown periods as 'natural experiments' to test whether specific mechanisms are at play and can explain changes in the division of unpaid work. Overall, they find that both men and women increased their domestic and care work during the initial lockdowns at the onset of the pandemic in spring 2020 (Andrew et al. 2020; Biroli et al. 2021; Carlson, Petts, and Pepin 2020; Craig and Churchill 2021; Farré et al. 2020; Fodor et al. 2021; Hank and Steinbach 2021; Hipp and Bünning 2021; Kreyenfeld and Zinn, 2021; Safi et al. 2020; Seiz 2021; Sevilla and Smith 2020; Zamberlan, Gioachin, and Gritti 2021), but these increases did not seem to translate into a more egalitarian division of unpaid work. Results are more mixed regarding the driving factors of these changes and the extent to which the gender gap narrowed over the period.

This paper contributes to the literature on gendered division of household and care work, comparing the explanatory power of existing theories – time availability, relative resources, and doing gender – in a context where the time dedicated to unpaid work increased because of lockdown restrictions imposed by the French government. France
can be considered a ‘crucial case’ to investigate our dependent variable of interest (Eckstein 1975; Gerring 2007). This is because it stands out among European countries in the contrast between forms of lockdowns adopted, thus permitting us to compare their distinct impact not only epidemiologically (Desson et al. 2020; Ferragina et al. 2021; Or et al. 2021; Yan et al. 2020) but also with regards to family organisation – particularly the division of household work within couples.

The study is based on a unique longitudinal dataset – the Coping with COVID-19 survey (CoCo) – representative of the mainland French population, which we collected and employed to perform a systematic analysis of the variation in the domestic division of work and care during three different periods of the pandemic (characterised by different types of restrictions). The first was a strict lockdown period in spring 2020, during which schools were shut down; the second was the summer 2020 ‘return to normal’; the third was a lighter lockdown period in April 2021, during which schools were open. Although we cannot directly compare the pandemic time with a pre-lockdown period with our data, the use of an out-of-lockdown period (summer 2020) as a reference point allows us to investigate how couples reacted to a context and to single out mechanisms that might explain changes in the division of unpaid work in ‘hard times.’

## 2. Background

### 2.1 The COVID-19 lockdowns' effect on the domestic division of work and care

Previous literature highlights that important life changes and exogenous shocks can influence the domestic division of work. Longitudinal studies have shown that life course transitions have an impact on the division of household work and child care within couples. For instance, the transition to parenthood is positively associated with a more traditional division of work (Sanchez and Thomson 1997; Grunow, Schulz, and Blossfeld 2012). Transitions to unemployment also influence the amount and share of domestic work that individuals do. In the United States, several studies have shown that during the 2007–2009 recession, unemployed men and women devoted more time to domestic work. This reduced the gender gap, although the reduction was due to fathers’ greater involvement in child care rather than in routine domestic chores (Berik and Kongar 2013; Morrill and Pabilonia 2012). Women continued to allocate more time to domestic work than men (Aguiar, Hurst, and Karabarbounis 2013).

The lockdowns instated to curb the COVID-19 pandemic altered the working and living conditions of the population. Although restrictions were different across countries and time (see below), lockdowns led to an increase in work from home and unemployment. Because work patterns and time availability are two of the main
explanatory factors for the division of unpaid work, we expect that the lockdowns had an impact on the domestic division of work and care. In this respect, most previous research relies on convenience samples and retroactive questions about the division of unpaid work before the start of the pandemic (Andrew et al. 2020; Biroli et al. 2021; Carlson, Petts, and Pepin 2020; Craig and Churchill 2020; Fodor et al. 2020; Hipp and Bünning 2021; Kreyenfeld and Zinn 2021; Seiz 2021; Sevilla and Smith 2020). Therefore the results should be interpreted with caution. Studies using representative samples (Hank and Steinbach 2021; Zhou et al. 2020; Farré et al. 2020; Recchi et al. 2020) show similar results: both men and women increased the time spent on household work and care during the lockdowns, but these increases did not necessarily translate into greater gender equality. While preliminary analyses in the United States and Canada showed a more gender-equal division of unpaid work (Carlson, Petts, and Pepin 2020; Shafer, Scheibling, and Milkie 2020), research across European countries proposes mixed results, with some studies revealing persistent patterns of gender inequality during lockdowns (Farré et al. 2020; Sevilla and Smith 2020; Zhou et al. 2020).

Following the literature on the domestic division of work, three main factors help explain partners' contributions: time availability, relative resources, and gender.

First, the time availability approach suggests that the time devoted to unpaid tasks relates to couples' commitments in life, the time available after they have dealt with paid work, and the amount of unpaid work necessary within the household (Hiller 1984). This approach assumes rationality and gender neutrality, which means that the composition of the household and the number of paid working hours are the main determinants of the amount and share of unpaid work. The empirical evidence for this approach is mixed. Some studies have shown that in Europe and the United States (Gough and Killewald 2011), being unemployed is often associated with devoting a greater amount of time to household chores. However, other research has demonstrated that women who work longer hours than their partners do not spend significantly less time doing household chores (Flèche, Lepinteur, and Powdthavee 2020). Moreover, studies on the effect of unemployment find that unemployed women devote more time to unpaid work than unemployed men (Aguiar, Hurst, and Karabarbounis 2013; Berik and Kongar 2013; Pailhé, Solaz, and Souletie 2019). Time availability is expected to affect both men and women, and spending more time at home was one of the main changes brought about by the lockdowns, so we expect this factor to impact the division of domestic work for both men and women.

H1: Changes in working conditions affect individuals' contributions to housework. Hence we expect increased involvement in unpaid tasks for both men and women if they are unemployed or work remotely. And we expect their partner's working conditions to similarly affect their involvement.
Because unpaid work is considered less attractive and desirable than paid work, rational choice approaches have hypothesised that partners negotiate their contributions to domestic work on the basis of their own resources, including educational level, occupational status, and income (Blood and Wolfe 1960; Lundberg and Pollak 1996). Indeed, couples may maximise efficiency through specialisation (Becker 1991) and let family members with more conspicuous assets on the labour market (education or wages) spend a larger amount of time in paid work. This perspective also assumes gender neutrality, suggesting that the level of disposable assets would have the same consequences for men and women in the process of negotiating the division of household and care tasks.

Once again, the empirical evidence is mixed. On the one hand, dual-earning couples display a more egalitarian distribution of household and care work than couples where women do not work for pay (Aassve, Fuochi, and Mencarini 2014; Lachance-Grzela and Bouchard 2010). On the other hand, women may still perform a larger share of household work even when the spouse has a lower income (Lachance-Grzela and Bouchard 2010; Mandel, Lazarus, and Shaby 2020). It is important to note that the variables used to measure relative economic resources sometimes overlap with those used to measure time availability.<fnref n="4" /> In this paper, we use educational attainment as an indicator of relative resources that was not affected by changes in economic conditions and time availability during the pandemic period.

**H2:** Differences between partners' educational attainments affect their relative bargaining power and hence individual contributions to housework. Thus we expect men to contribute less if their educational attainment is higher than their partner's.

Finally, the role of gender has also been highlighted in the literature. The doing gender approach considers that cultural and symbolic mechanisms related to gender identities drive the division of unpaid work within couples. This literature highlights the role of gender stereotypes in defining gender roles that both men and women end up performing in their everyday lives. Sizable gender inequalities characterise household work and child care; women devote more time to unpaid work than men in every country where reliable measures are available (Altintas and Sullivan 2016; Horne et al. 2018; Siminski and Yetsenga 2020; Dieckhoff et al. 2020; Grotti and Scherer 2016; Vitali and Arpino 2016). According to this framework, household work and child care are often considered feminine tasks. These norms influence how men and women are socialised

<footnote n="4">⁴ For instance, full-time workers usually earn higher hourly wages than part-time workers, and they also have less time available; women who are not active in the labour market have both more time available and low economic resources.</footnote>
and the quantity of unpaid work undertaken within couples (Bittman et al. 2003; Agarwal 1997; Pearse and Connell 2016). Women and men ‘do gender’ (West and Zimmerman 1987) when they divide work tasks, and women ultimately do more unpaid work because of existing gender norms and internalised expectations. Gender norms also influence the type of household work that each member of the couple performs. For example, while women often spend more time on child care, men may be inclined to take on child care (Craig and Mullan 2011) or certain other tasks (Coltrane 2000) because they are perceived as more pleasant than certain other unpaid tasks (Coltrane 2000; Altintas and Sullivan 2016).

In the case of the pandemic, other studies reveal that some couples reorganised towards more egalitarian and non-normative arrangements of unpaid work (Seiz 2021). Results differ depending on the tasks examined and in general show a more egalitarian division of child care provision than of routine household work (Fodor et al. 2021; Mangiavacchi, Piccoli, and Pieroni 2021; Del Boca et al. 2020). Biroli et al. (2021) also found that shopping became a more masculine task during the pandemic. This might be related to shopping being a less specialised task. It may also be related to its implications at the outset of the pandemic: shopping was one of the few tasks that allowed people to go out during the lockdowns and was also considered a dangerous endeavour, at least during the first lockdown, when the virus was still unfamiliar and protective measures like widespread mask usage and vaccinations were absent.

Moreover, prior research highlights that gender norms shape the ways in which the two aforementioned factors affect the division of domestic work. For example, studies find that the effect of time availability on the contribution to unpaid work is stronger for women than for men (Andrew et al. 2020; Biroli et al. 2021; Carlson, Petts, and Pepin 2020; Craig 2020; Dominguez-Folgueras 2021; Hank and Steinbach 2021; Safi et al. 2020; Sevilla and Smith 2020; Zamberlan, Gioachin, and Gritti 2021). Moreover, while women with more economic resources do less unpaid work than others, the division of work is not egalitarian, even in couples where women have higher wages (Andrew et al. 2020; Zamberlan, Gioachin, and Gritti 2021). Thus, in line with these findings, gender might shape the ways in which other factors influenced the division of work during the pandemic.

H3: We expect the effects of working conditions and educational differences to vary depending on gender. Women’s contributions to unpaid work will be less responsive to changes in employment conditions or educational gaps. Moreover, gender norms will affect the type of tasks performed.
## 2.2 Context: A story of two lockdowns

In France, a lockdown was instated on 17 March 2020 to contain the COVID-19 outbreak, two days after schools were shut down. This first lockdown was the most restrictive; only services deemed essential remained open, and the government required working from home to be implemented for everyone who could do so, with few exceptions. All residents in the country could leave their homes for specific purposes only: to shop for essential goods, to commute to work, to walk or exercise (for an hour a day and within a one-kilometre radius of home), to take care of somebody, or for medical reasons. Many companies shut down their operations, and the French government enabled them to put employees on furlough (chômage partiel). Workers on this scheme received unemployment benefits without losing their jobs. Almost a third of the working-age population benefited from this measure (Ferragina and Zola 2022). This first lockdown entailed important changes in working conditions and saw a rise of unemployment. At the beginning of May 2020, 25% of people previously employed were now on furlough, one-third kept going to their usual workplaces, another third worked remotely at least part-time, and 15% were on leave, an option also used by firms (and workers) to handle the health crisis. Working remotely was more customary for managers, professionals, and mid-level employees than for lower occupational categories (Safi et al. 2020).

The first lockdown ended on 11 May 2020, but some restrictive measures remained in place. For instance, schools reopened progressively (for a limited number of students), and working remotely was still encouraged. At the beginning of the summer of 2020, social life started to return to normal. By September 2020, schools, cafés, restaurants, museums, and concert venues had generally reopened. However, during autumn, a surge in the number of cases led the government to impose a 9 p.m. to 6 a.m. curfew in the most affected areas of the country. The restrictions were extended with a second lockdown between 30 October and 15 December. As during the spring 2020 lockdown, the second lockdown included mobility restrictions, furloughs, and the closing of social venues (restaurants, concert halls, and so on). However, schools remained open, and most workers could continue to commute to their usual workplaces. The high number of cases at the end of the second lockdown led to the extension of curfew restrictions and the ongoing closure of social venues. Finally, a last lockdown was imposed between 3 April and 3 May 2021. During this lockdown, mobility restrictions were light (travel within a 10-kilometre radius of one's home did not require written justification), but schools and child care facilities were closed for three weeks to reduce the epidemiological impact of the pandemic. The government combined one week of school closure (3–9 April) with two weeks of preplanned spring break (10–25 April).<fnref n="5" />

<footnote n="5">⁵ Middle and high schools had one supplementary week of closure and reopened on 3 May.</footnote>
Although only essential services were allowed to remain open during the three lockdowns, the definition of essential was loosened during the second one, permitting many shops and services to remain open. Because of the lighter restrictions, the economic consequences of the second and last lockdowns were less dramatic than those of the first (Ferragina et al. 2021).

Overall, comparing the first lockdown, the out-of-lockdown period, and the two other lockdowns provide a natural experiment because the first one was highly restrictive. During the first lockdown, the labour market was more heavily affected, many more companies ceased operations (at least temporarily), and all schools and child care facilities were closed. For most families, the amount of household and care work that could not be outsourced increased significantly. This first phase can thus be considered a shock for the total demand of housework and particularly intense for a gendered task like child care. The two other phases of lockdown were less strict, providing more opportunities for outsourcing household chores, and with fewer interruptions of schools and child care services.<fnref n="6" /> This was also true of the out-of-lockdown period. Despite the different nature of these lockdowns, people described spending much more time at home than in non-lockdown times, and this affected the total demand of unpaid work.

Figure 1a synthesises the timeline of restrictions in France in relation to this study's empirical design, and Figure 1b shows the importance of shifts in respondents' paid work situations during the different CoCo waves exploited for this study. Figure 1b shows that, among couples, employed workers before the pandemic fell into four work situations of approximately equal size: on leave, on furlough, doing remote work, and working at the usual workplace.<fnref n="7" /> In October 2020, during the out-of-lockdown period, the furlough scheme diminished substantially, and to a lesser extent so did remote work. However, both increased again during the second and last lockdowns, especially for women. On-leave situations remained high during the October 2020 and April 2021 survey waves, partly as a result of the coincidence of these waves with school breaks.

<footnote n="6">⁶ The eighth survey wave we reference took place between the 22 April and 29 April, a period in which primary schools were reopening.</footnote>

<footnote n="7">⁷ The definition of 'remote work' in wave 1's retrospective question for the pre-lockdown period differs slightly from the definition for the rest of the period: "Before March 15th did you do remote work: 1. Always, 2. Regularly, 3. Occasionally, 4. Rarely, 5. Never" versus "During the two last weeks, you: 1. Worked mostly at your usual workplace, 2. Mixed between remote work and your usual workplace, or 3. Did mostly remote work." We used items 1 and 2 in the first question and 2 and 3 in the second question to code remote work.</footnote>
<figure><img src="image_4.png" /><figcaption>Figure 1a: Restriction timeline in France and CoCo survey waves</figcaption></figure>

Source: Authors' elaboration.
<figure><img src="image_5.png" /><figcaption>Figure 1b: Variation of paid work situation over CoCo survey waves</figcaption></figure>

Regarding the division of work in France, as in other countries, there has been a
trend towards convergence, but women still perform the lion's share. The most recent
time-use data show that women do 71% of routine domestic work and 65% of child care
(Champagne, Pailhé, and Solaz 2015). Women in France spend on average four hours a
day in domestic and care work, which places their investment in domestic chores at an

<footnote>* "Inactive" includes students and unemployed workers.</footnote>

<footnote>Source: Authors' elaboration.</footnote>

<footnote>Note: Estimates for respondents living in couples.</footnote>
intermediate level in Europe; the average in Italy and the Netherlands is closer to five
hours, whereas it is three hours in Sweden (Pailhé, Solaz, and Stanfors 2020). The
gendered segregation of tasks found in many countries exists also in France, with women
doing larger shares of routine domestic work and child care, and men investing more in
less routine tasks (repairs, gardening, taking care of pets) and shopping, as well as
increasing their involvement in child care over time (Champagne, Pailhé, and Solaz 2015;
Pailhé, Solaz, and Stanfors 2020).

To investigate whether couples’ divisions of unpaid tasks changed during the
COVID-19 pandemic, we compared the out-of-lockdown period (October 2020) with the
first (April–May 2020) and last (April 2021) lockdown periods. Moreover, we explored
changes in the share of unpaid chores within couples as a consequence of lockdown
measures and through the lens of the three hypotheses discussed above.

**3. Data, variables, and methods**

**3.1 Participants**

We expanded data from the ELIPSS<fnref n="8" /> probability-based panel study, launched in 2012, with the online collection of eight additional waves from the beginning of the pandemic in April 2020 until April 2021.<fnref n="9" /> The initial sample includes 1,404 residents of mainland France. Weights are computed to account for design effects from the initial stage, bias due to acceptance rates during the first enrolment phase, and post-stratification on the basis of gender, age, education, and region. The CoCo project took advantage of this existing panel by running eight new surveys covering different stages of the COVID-19 crisis.

The first wave used in this paper was administered four weeks into the first
lockdown (29 April–6 May).<fnref n="10" /> The reference period is the sixth wave (22–29 October;
response rate about 75.2%), which was administered during the out-of-lockdown
period.<fnref n="11" /> Our third period corresponds to the eighth wave of the panel, which was

<footnote n="8">⁸ The ELIPSS panel study was established by the French National Institute of Statistics and Economic Studies (INSEE). The sample was randomly selected from 2011 census data using two stratification variables: region of residence and type of municipality. In 2019 the panel included 1,404 respondents from previous waves. All panel members were invited to take part in the first wave of the CoCo study, and after two recruitment phases, all respondents agreed to participate.</footnote>

<footnote n="9">⁹ The study was directed by the ELIPSS team (Recchi et al. 2022).</footnote>

<footnote n="10">¹⁰ Since child care information was not available for 29 April–6 May, we used information collected between 15 April and 22 April.</footnote>

<footnote n="11">¹¹ During this survey wave, people were nevertheless subjected to a 9 p.m.–6 a.m. curfew in half of France’s *départements* (representing two-thirds of the population).</footnote>
administered 22–29 April 2021 (response rate 71.1%), at the end of the last lockdown (when child care facilities and primary schools had reopened). In terms of the analytic sample, we selected only individuals living in couples taking part in the above-mentioned three survey waves (1,959 observations; 809 individuals living in couples).

## 3.2 Variables

The main dependent variable of this study is the share of housework carried out by each partner in cohabitating heterosexual couples. Respondents living with a partner were asked how often they, their partner, and an eventual other person living in the household took care of various household tasks. These tasks include total housework, cooking, shopping, ironing, laundry, repairs/home improvement, and child care (including home-schooling supervision). We turned the ordinal 4-level response scale into a 0% to 100% score: always = 100%, often = 66%, sometimes = 33%, and never = 0%. We calculated the standardised male share for each of these tasks by dividing the index of male participation by the sum of index scores of the two partners.<fnref n="12" /> In addition, with regards to child care, we used an additional dependent variable related to the daily hours spent in care tasks. Respondents were asked how many hours per day (on average) they had devoted to child care during the previous two weeks. Possible answers (I did not do this task; between 0 and 1 hour; between 1 and 2 hours; between 2 and 3 hours; between 3 and 4 hours; between 4 and 6 hours; between 6 and 8 hours; between 8 and 10 hours; more than 10 hours) have been recoded using the middle value of each answer (0, 0.5, 1.5, 2.5, 3.5, 5, 7, 9, or 12 hours). Unfortunately, the survey does not allow us to disaggregate child care tasks in the same way as routine domestic work.

The time period (the three phases included in our study) is the main independent variable of our models, as we are interested in looking at the effect of the pandemic’s lockdown and out-of-lockdown phases on the share of paid and unpaid work. We used a variable accounting for the period when the wave was collected (the first lockdown in April 2020, out of lockdown in October 2020, and the last lockdown in April 2021).

As mediating variables, we employ respondents’ and their partners’ working conditions at each point in time. Possible answers: out of employment (where we group retired workers with students, inactive workers, and unemployed persons); on leave;<fnref n="13" /> on furlough; remote work; work at workplace. Educational attainment is based on a self-

<footnote n="12">¹² As we do not know the gender of the partner, we assume that all couples are heterosexual, which was the case for more than 99% of couples in France in 2018 (cf. https://www.insee.fr/fr/statistiques/4215399). The advantage of our standardised ‘share of work’ variable is that it discounts for the share done by another person, which could be a salaried house cleaner or a relative whose gender we do not know.</footnote>

<footnote n="13">¹³ This category includes on holiday, on sick leave, and on parental leave.</footnote>
rated question about respondents’ and partners’ highest educational level (less than high school degree, high school degree/some college, undergraduate degree or higher). With this information we construct a dummy variable that accounts for whether men reported a higher educational level than their partners.<fnref n="14" />

### 3.3 Methods

We adopt a fixed effect approach to control for individual unobserved characteristics. We include individual fixed effects in the regression controls for time-invariant respondent characteristics. In particular, we employ an individual fixed effects linear regression model controlling for time (Model 1) to investigate changes in the male share of unpaid tasks during the two lockdown periods. Model 1’s outcomes consist of the sum of the housework tasks (Model 1a); single housework tasks (cooking, shopping, ironing, laundry, repairs) and child care (Model 1b); and daily hours spent in child caregiving (Model 1c).

In addition, to test whether changes in the male share of housework and child care were driven by changes in the employment conditions of both partners (Model 2), we use fixed effects linear regression models that specifically look at: the association between changes in men’s employment status and changes in men’s contribution to unpaid work (defined as the sum of the housework tasks, Model 2a); the association between changes in men’s employment status and changes in men’s contribution to unpaid work (defined as single specific tasks, Model 2b); the association between changes in women’s employment status and changes in men’s contribution to unpaid work (defined as the sum of the housework tasks, Model 2c); and the association between changes in women’s employment status and changes in men’s contribution to unpaid work (defined as single specific tasks, Model 2d). Then, in one single linear regression model, we simultaneously estimate the changes in men’s contribution to unpaid work as a function of the two lockdowns and of women’s and men’s changes in employment status (Model 2e and Model 2f, respectively, when the outcome is the sum of the unpaid tasks or the single tasks).<fnref n="15" />

Model 3 (a and b) examines the moderation effect of an educational gap within the couple in the association between the two lockdown periods and the male share of housework by the inclusion of an interaction term in the linear regression model.

<footnote n="14">¹⁴ This variable is constructed in line with the other variables by looking at (for example, the share of work done by) men compared to partners.</footnote>

<footnote n="15">¹⁵ An additional model including an interaction between men’s and women’s changes in employment conditions has been done as a robustness check (available upon request). Main findings are in line with those shown in the manuscript.</footnote>
# 4. Results

## 4.1 Descriptive findings

Table 1 presents the weighted outcomes and the sample characteristics when France was out of lockdown (22–29 October 2020; wave 6). According to the respondents’ reports, men did less than their partners for most of the housework tasks. Looking at the overall housework couples performed, men contributed on average to about 37% of the total unpaid work. Males did 44% of child care, 40% of shopping, and just below 20% of ironing and laundering. Men did more than their partners only in the areas of repairs, gardening, and decorating, with a share of 65%. Finally, among those with children at home, men reported spending on average about 2.44 hours versus women’s 3.80 hours on child care.

Concerning the sample characteristics, about 46% of respondents were women, 55% were between 35 and 64 years old, and only about 2% were foreign-born residents. About half of the men and 45% of the women living in couples were out of work already before the lockdown; about 8% of men and 10% of women were on leave in October 2020. The share of individuals on furlough during the lockdown was, in October 2020, about 2.5% among men and about 3.7% among women. Moreover, a slightly higher percentage of women worked remotely (8.2%) compared to men (6.3%). About 34% of respondents reported working at their usual workplaces in October 2020. Finally, the share of couples with men having a higher educational attainment than their partner was about 20%.

<table><caption>Table 1: Weighted descriptive statistics for wave 6</caption><thead><tr><th>Dependent variables</th><th>Mean (SD)</th><th>N</th></tr></thead><tbody><tr><td>Men's share of total housework (%)</td><td>37.09 (15.26)</td><td>681</td></tr><tr><td>Men's share of cooking (%)</td><td>34.90 (25.48)</td><td>687</td></tr><tr><td>Men's share of shopping (%)</td><td>40.69 (22.48)</td><td>688</td></tr><tr><td>Men's share of laundry (%)</td><td>19.23 (25.47)</td><td>686</td></tr><tr><td>Men's share of ironing (%)</td><td>18.79 (32.18)</td><td>593</td></tr><tr><td>Men's share of repairs (%)</td><td>65.64 (24.05)</td><td>669</td></tr><tr><td>Men's share of child care (%)</td><td>44.37 (12.26)</td><td>234</td></tr><tr><td>Number of hours spent in child care (men)</td><td>2.44 (3.45)</td><td>178</td></tr><tr><td>Number of hours spent in child care (women)</td><td>3.80 (3.79)</td><td>183</td></tr><tr><th>Sociodemographic characteristics</th><th>%</th><th></th></tr><tr><td>Women</td><td>45.88</td><td>695</td></tr><tr><td>Foreign</td><td>1.73</td><td>695</td></tr><tr><td>Age bracket</td><td></td><td>695</td></tr><tr><td>&lt; 35</td><td>25.03</td><td></td></tr><tr><td>35–64</td><td>54.86</td><td></td></tr><tr><td>65+</td><td>20.11</td><td></td></tr></tbody></table>
<table><caption>**Table 1:** (Continued)</caption><thead><tr><th>Dependent variables</th><th>Mean (SD)</th><th>N</th></tr></thead><tbody><tr><td>Self-rated health</td><td></td><td>695</td></tr><tr><td>Poor/very poor</td><td>3.26</td><td></td></tr><tr><td>Education</td><td></td><td>695</td></tr><tr><td>CAP/BEP or under</td><td>52.18</td><td></td></tr><tr><td>Bac/bac+2</td><td>31.70</td><td></td></tr><tr><td>Bac+3</td><td>16.12</td><td></td></tr><tr><td>Wealth</td><td></td><td>473</td></tr><tr><td>&lt; 150,000€</td><td>34.79</td><td></td></tr><tr><td>150,000–300,000€</td><td>31.71</td><td></td></tr><tr><td>&gt; 300,000€</td><td>33.50</td><td></td></tr><tr><td>Men's occupation</td><td></td><td>688</td></tr><tr><td>Out of employment</td><td>49.09</td><td></td></tr><tr><td>On leave</td><td>7.81</td><td></td></tr><tr><td>Furlough</td><td>2.59</td><td></td></tr><tr><td>Remote work</td><td>6.29</td><td></td></tr><tr><td>Work at workplace</td><td>34.22</td><td></td></tr><tr><td>Women's occupation</td><td></td><td>690</td></tr><tr><td>Out of employment</td><td>44.85</td><td></td></tr><tr><td>On leave</td><td>9.60</td><td></td></tr><tr><td>Furlough</td><td>3.72</td><td></td></tr><tr><td>Remote work</td><td>8.22</td><td></td></tr><tr><td>Work at workplace</td><td>33.61</td><td></td></tr><tr><td>Educational gap within the couple</td><td></td><td>695</td></tr><tr><td>Education of men &gt; women</td><td>19.55</td><td></td></tr></tbody></table>

Source: Coping with COVID-19, sixth wave (CoCo-6), 22–29 October 2020, ELIPSS/CDSP. Mean and standard deviations (in parentheses) are reported for continuous variables; percentages (%) for discrete variables. N refers to the total sample at the sixth wave (CoCo-6), 22–29 October 2020.

## 4.2 Couples’ divisions of domestic and care work: Time, work, educational gaps and tasks

Findings listed in Table 2 suggest that men did a slightly higher proportion of unpaid work within couples during the first lockdown compared to the out-of-lockdown period (a difference of about 0.82 percentage points). When analysing specific tasks, we observe that men’s contribution to unpaid work mostly concerned shopping, which – compared to the out-of-lockdown period – was about 6.64 percentage points higher in the first lockdown and about 1.88 percentage points higher in the last lockdown, when schools were open. As expected, men’s contribution to routine household tasks, such as laundering, did not increase – and even decreased – during the last lockdown (coef. = – 1.23; p < 0.05).
<table><caption>**Table 2:** Lockdowns' effects on men's share of housework within couples (individual fixed effect, clustered SE)</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="3">Model 1a</th><th colspan="3">Model 1b</th><th colspan="3">Model 1c</th></tr><tr><th>All<br>coef (95% CI)</th><th>Cooking<br>coef (95% CI)</th><th>Shopping<br>coef (95% CI)</th><th>Laundry<br>coef (95% CI)</th><th>Ironing<br>coef (95% CI)</th><th>Repairs<br>coef (95% CI)</th><th>Child care<br>coef (95% CI)</th><th>Hours spent<br>in child care<br>coef (95% CI)</th></tr></thead><tbody><tr><td>First lockdown (ref.<br>out of lockdown)</td><td>0.819<br>(0.12-1.51)</td><td>0.270<br>(-0.91-1.45)</td><td>6.639<br>(4.42-8.85)</td><td>-0.737<br>(-1.87-0.39)</td><td>-0.675<br>(-1.97-0.62)</td><td>0.566<br>(-1.02-2.15)</td><td>-3.146<br>(-5.74-0.54)</td><td>1.117<br>(0.51-1.72)</td></tr><tr><td>Last lockdown (ref.<br>out of lockdown)</td><td>0.355<br>(-0.29-1.00)</td><td>0.667<br>(-0.57-1.90)</td><td>1.881<br>(0.51-3.24)</td><td>-1.230<br>(-2.41-0.04)</td><td>-0.720<br>(-2.19-0.75)</td><td>-0.400<br>(-1.84-1.04)</td><td>-0.460<br>(-2.69-1.77)</td><td>0.804<br>(0.26-1.33)</td></tr><tr><td>Men * First<br>lockdown</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.829<br>(-1.53-0.12)</td></tr><tr><td>Men * last lockdown</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.293<br>(-1.02-0.43)</td></tr><tr><td>Constant</td><td>35.78<br>(35.42-36.12)</td><td>34.07<br>(33.43-34.69)</td><td>40.54<br>(39.61-41.46)</td><td>17.85<br>(17.24-18.46)</td><td>14.77<br>(14.02-15.51)</td><td>62.38<br>(61.54-63.20)</td><td>44.59<br>(43.42-45.76)</td><td>2.572<br>(2.38-2.75)</td></tr><tr><td>Observations</td><td>1,886</td><td>1,896</td><td>1,897</td><td>1,897</td><td>1,610</td><td>1,851</td><td>590</td><td>923</td></tr><tr><td>R-squared</td><td>0.005</td><td>0.001</td><td>0.041</td><td>0.004</td><td>0.001</td><td>0.001</td><td>0.022</td><td>0.044</td></tr><tr><td>Number of ID</td><td>794</td><td>796</td><td>799</td><td>797</td><td>713</td><td>785</td><td>287</td><td>403</td></tr></tbody></table>

Source: Coping with Covid-19, ELIPSS/CDSP.

Note: "1st lockdown" is survey wave 3 for housework and survey wave 2 for child care and share of child care. "All" does not include child care. Linear regression coefficients with 95% confidence intervals in parentheses.
Our estimates also show that men's share of child care, including home-schooling supervision, was lower by about three percentage points in the first lockdown compared with the out-of-lockdown period. Accordingly, the daily number of hours spent in child care also significantly increased during both lockdowns, but mostly because women spent more time taking care of children (interaction coef. = -0.829; p < 0.05).

As expected, men's changes in working conditions mattered in determining their contributions to unpaid work (Table 3). We observe that a change from working at one's workplace to being on leave (holiday, sick, or parental leave; p < 0.01), on furlough (p < 0.01), or working remotely (p < 0.1) increases men's overall share of unpaid work. However, when we look at specific tasks, significant differences arise. While men who were on leave during the lockdowns made higher contributions to cooking, shopping, decorating, and child care, for those benefiting from the furlough scheme during the pandemic, a larger share of unpaid work mostly concerned cooking and shopping. Men working from home devoted more time only to shopping (+8.1 percentage points), while they participated less in ironing (coef. = -3.1; p < 0.05). Our estimates also confirm the overall increase in child care done by men on leave (coef. = 1.55; p < 0.1). With regards to the association between women's changes of working conditions and men's contribution to housework, our estimates show that men contributed less to unpaid work if women moved from the workplace to being on furlough (coef. = -1.83; p < 0.05). In line with what we found in prior estimates (see Table 3), most of the decreased contribution of men to unpaid work concerned cooking and ironing when the partner was on furlough or on leave. However, living with a woman who moved to remote work was associated with an increase in men's share of shopping of about six percentage points. Women contributed more to child care during both lockdowns, especially if they were not working at the workplace.

The effect of the first lockdown was partially driven by changes in working conditions, as shown by results listed in Table 5. When both partners were working at the workplace, the first lockdown saw a significantly more robust participation of men in shopping (coef. = 6.30; p < 0.01) but a comparatively lower investment in child care time (coef. = -3.86; p < 0.01).<fnref n="16" /> Finally, as shown in Table 6, couples with an unbalanced level of education show a different level of men's contribution to unpaid work, which is only due to men not doing laundry.<fnref n="17" />

<footnote n="16">¹⁶ During the last lockdown, men contributed even less to laundry compared to the out-of-lockdown period (coef. = -1.09; p < 0.1).</footnote>

<footnote n="17">¹⁷ In resonance with the relative resources hypothesis, we found that the level of men's contribution to laundry during the first lockdown was lower among male respondents with a higher educational attainment compared to their partners than in the out-of-lockdown period (coef. = -2.71; p < 0.1).</footnote>
<table><caption>Table 3: Men's share of housework within couples: The role of men's employment status (individual fixed effect, clustered SE)</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="3">Model 2a</th><th colspan="3">Model 2b</th><th rowspan="2">Hours spent<br>in child care<br>coef (95% CI)</th></tr><tr><th>All<br>coef (95% CI)</th><th>Cooking<br>coef (95% CI)</th><th>Shopping<br>coef (95% CI)</th><th>Laundry<br>coef (95% CI)</th><th>Ironing<br>coef (95% CI)</th><th>Repairs<br>coef (95% CI)</th><th>Child care<br>coef (95% CI)</th></tr></thead><tbody><tr><td>Men's occupation</td><td>2.221<br>(0.21-4.22)</td><td>5.465<br>(1.69-9.23)</td><td>5.309<br>(0.55-10.06)</td><td>0.581<br>(-3.29-4.45)</td><td>-0.123<br>(-4.28-4.04)</td><td>2.484<br>(-2.05-7.02)</td><td>9.645<br>(4.05-15.23)</td><td>0.0449<br>(-1.15-1.24)</td></tr><tr><td>Out of employment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>On leave</td><td>2.799<br>(0.94-4.65)</td><td>4.175<br>(0.82-7.52)</td><td>5.207<br>(-0.08-10.50)</td><td>2.278<br>(-0.54-5.09)</td><td>0.0564<br>(-3.19-3.30)</td><td>4.092<br>(0.15-8.02)</td><td>4.336<br>(0.17-8.49)</td><td>-0.163<br>(-1.27-0.94)</td></tr><tr><td>On furlough</td><td>3.873<br>(1.66-6.07)</td><td>4.438<br>(0.68-8.19)</td><td>8.317<br>(2.36-14.26)</td><td>1.191<br>(-2.25-4.63)</td><td>-1.414<br>(-4.23-1.40)</td><td>1.561<br>(-2.07-5.19)</td><td>2.997<br>(-0.97-6.97)</td><td>0.477<br>(-0.18-1.14)</td></tr><tr><td>Remote work</td><td>1.272<br>(-0.12-2.66)</td><td>0.872<br>(-1.52-3.26)</td><td>8.123<br>(3.66-12.58)</td><td>-0.606<br>(-3.30-2.09)</td><td>-3.108<br>(-5.58-0.63)</td><td>-0.099<br>(-3.59-3.39)</td><td>3.074<br>(-1.57-7.72)</td><td>0.546<br>(-0.69-1.78)</td></tr><tr><td>Men * out of<br>employment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.049<br>(-1.53-3.63)</td></tr><tr><td>Men * on leave</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.552<br>(-0.15-3.26)</td></tr><tr><td>Men * on furlough</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.634<br>(-0.66-1.93)</td></tr><tr><td>Men * remote work</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.176<br>(-1.61-1.25)</td></tr><tr><td>Constant</td><td>34.54<br>(33.42-35.64)</td><td>31.14<br>(29.06-33.21)</td><td>38.94<br>(36.17-41.70)</td><td>16.76<br>(14.68-18.83)</td><td>14.77<br>(12.46-17.07)</td><td>60.88<br>(58.42-63.32)</td><td>41.05<br>(39.45-42.64)</td><td>2.616<br>(2.16-3.06)</td></tr><tr><td>Observations</td><td>1,876</td><td>1,886</td><td>1,887</td><td>1,887</td><td>1,600</td><td>1,841</td><td>577</td><td>899</td></tr><tr><td>R-squared</td><td>0.023</td><td>0.014</td><td>0.019</td><td>0.004</td><td>0.004</td><td>0.006</td><td>0.028</td><td>0.024</td></tr><tr><td>Number of ID</td><td>792</td><td>795</td><td>798</td><td>795</td><td>712</td><td>784</td><td>285</td><td>398</td></tr></tbody></table>

Source: Coping with Covid-19. ELIPSS/CDSP.

Note: "All" does not include child care. Linear regression coefficients with 95% confidence intervals in parentheses.
<table><caption>Table 4: Men's share of housework within couples: The role of women's employment status (individual fixed effect, clustered SE)</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="3">Model 2c</th><th colspan="3">Model 2d</th><th rowspan="2">Hours spent<br>in child care<br>coef (95% CI)</th></tr><tr><th>All<br>coef (95% CI)</th><th>Cooking<br>coef (95% CI)</th><th>Shopping<br>coef (95% CI)</th><th>Laundry<br>coef (95% CI)</th><th>Ironing<br>coef (95% CI)</th><th>Repairs<br>coef (95% CI)</th><th>Child care<br>coef (95% CI)</th></tr></thead><tbody><tr><td>Women's occupation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Out of employment</td><td>-1.448<br>(-3.76-0.86)</td><td>-0.516<br>(-4.84-3.81)</td><td>-0.384<br>(-5.52-4.75)</td><td>-2.550<br>(-6.25-1.15)</td><td>0.888<br>(-3.68-5.45)</td><td>2.362<br>(-1.47-6.20)</td><td>1.585<br>(-5.90-9.07)</td><td>2.145<br>(0.57-3.71)</td></tr><tr><td>On leave</td><td>-0.906<br>(-2.31-0.50)</td><td>-3.770<br>(-6.30-1.23)</td><td>2.050<br>(-2.53-6.63)</td><td>-0.389<br>(-2.66-1.88)</td><td>-2.832<br>(-5.75-0.08)</td><td>0.975<br>(-1.81-3.76)</td><td>-1.594<br>(-6.49-3.30)</td><td>1.108<br>(0.23-1.98)</td></tr><tr><td>On furlough</td><td>-1.829<br>(-3.53-0.11)</td><td>-4.314<br>(-7.67-0.94)</td><td>-0.198<br>(-4.40-4.01)</td><td>-1.601<br>(-4.59-1.38)</td><td>-4.105<br>(-8.04-0.16)</td><td>-1.388<br>(-5.50-2.76)</td><td>-3.741<br>(-8.56-1.08)</td><td>1.743<br>(0.74-2.74)</td></tr><tr><td>Remote work</td><td>0.881<br>(-0.54-2.32)</td><td>0.067<br>(-2.37-2.51)</td><td>5.769<br>(1.98-9.55)</td><td>-0.994<br>(-3.39-1.40)</td><td>-2.419<br>(-5.81-0.97)</td><td>-1.174<br>(-4.24-1.89)</td><td>-2.901<br>(-7.19-1.39)</td><td>0.757<br>(0.04-1.46)</td></tr><tr><td>Men * women out of<br>employment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-2.105<br>(-4.06-0.14)</td></tr><tr><td>Men * women on<br>leave</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.989<br>(-2.03-0.06)</td></tr><tr><td>Men * women on<br>furlough</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-1.231<br>(-2.56-0.10)</td></tr><tr><td>Men * women remote<br>work</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.740<br>(-1.61-0.13)</td></tr><tr><td>Constant</td><td>36.85<br>(35.68-38.00)</td><td>35.24<br>(33.06-37.40)</td><td>42.36<br>(39.63-45.08)</td><td>18.61<br>(16.76-20.45)</td><td>14.75<br>(12.31-17.19)</td><td>61.51<br>(59.45-63.56)</td><td>44.54<br>(42.49-46.57)</td><td>2.523<br>(2.24-2.79)</td></tr><tr><td>Observations</td><td>1.876<br>(0.010)</td><td>1.886<br>(0.016)</td><td>1.887<br>(0.008)</td><td>1.887<br>(0.003)</td><td>1.600<br>(0.012)</td><td>1.841<br>(0.003)</td><td>574<br>(0.014)</td><td>895<br>(0.038)</td></tr><tr><td>R-squared</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Number of ID</td><td>794</td><td>796</td><td>799</td><td>797</td><td>713</td><td>785</td><td>284</td><td>398</td></tr></tbody></table>

Source: Coping with Covid-19, ELIPSS/CDSP.

Note: "All" does not include child care. Linear regression coefficients with 95% confidence intervals in parentheses
<table><caption>Table 5: Lockdowns' effects on the male share of housework within couples: The role of partners' employment status (individual fixed effects, clustered SE)</caption><thead><tr><th rowspan="2"></th><th colspan="3">Model 2e</th><th colspan="3">Model 2f</th><th rowspan="2">Hours spent<br>in child care<br>coef (95% CI)</th></tr><tr><th>All<br>coef (95% CI)</th><th>Cooking<br>coef (95% CI)</th><th>Shopping<br>coef (95% CI)</th><th>Laundry<br>coef (95% CI)</th><th>Ironing<br>coef (95% CI)</th><th>Repairs<br>coef (95% CI)</th></tr></thead><tbody><tr><td>First lockdown<br>(ref. out of<br>lockdown)</td><td>0.702<br>(-0.02-1.43)</td><td>0.502<br>(-0.73-1.73)</td><td>6.289<br>(3.93-8.64)</td><td>-0.741<br>(-2.00-0.52)</td><td>0.178<br>(-1.24-1.60)</td><td>0.977<br>(-0.78-2.73)</td><td>-3.862<br>(-6.89- -0.83)</td><td>0.647<br>(0.20-1.08)</td></tr><tr><td>Last lockdown<br>(ref. out of<br>lockdown)</td><td>0.447<br>(-0.21-1.10)</td><td>0.833<br>(-0.42-2.09)</td><td>1.776<br>(0.33-3.21)</td><td>-1.101<br>(-2.33-0.13)</td><td>-0.345<br>(-1.82-1.13)</td><td>-0.324<br>(-1.80-1.16)</td><td>-0.474<br>(-2.76-1.81)</td><td>0.642<br>(0.26-1.02)</td></tr><tr><td>Men's<br>occupation<br>Out of<br>employment</td><td>2.687<br>(0.72-4.64)</td><td>6.579<br>(2.80-10.35)</td><td>6.177<br>(1.15-11.19)</td><td>1.030<br>(-2.94-5.00)</td><td>0.467<br>(-3.90-4.84)</td><td>2.536<br>(-2.05-7.12)</td><td>11.51<br>(5.49-17.53)</td><td>-0.343<br>(-1.50-0.82)</td></tr><tr><td>On leave</td><td>3.099<br>(1.22-4.97)</td><td>5.602<br>(2.31-8.88)</td><td>4.065<br>(-1.16-9.29)</td><td>2.599<br>(-0.35-5.55)</td><td>0.704<br>(-2.64-4.05)</td><td>4.116<br>(0.05-8.17)</td><td>5.555<br>(0.93-10.17)</td><td>-0.550<br>(-1.63-0.53)</td></tr><tr><td>On furlough</td><td>4.058<br>(1.82-6.28)</td><td>5.343<br>(1.63-9.05)</td><td>5.434<br>(-0.56-11.43)</td><td>1.630<br>(-1.95-5.21)</td><td>-0.943<br>(-4.13-2.24)</td><td>1.682<br>(-2.27-5.63)</td><td>6.418<br>(2.07-10.76)</td><td>0.017<br>(-0.75-0.79)</td></tr><tr><td>Remote work</td><td>1.089<br>(-0.39-2.57)</td><td>1.026<br>(-1.57-3.62)</td><td>5.435<br>(-0.96-9.90)</td><td>-0.001<br>(-2.87-2.87)</td><td>-2.854<br>(-5.25- -0.45)</td><td>0.156<br>(-3.63-3.93)</td><td>6.047<br>(1.08-11.00)</td><td>0.146<br>(-1.09-1.38)</td></tr><tr><td>Men * out of<br>unemployment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.503<br>(-1.01-4.01)</td></tr><tr><td>Men * on leave</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.912<br>(0.16-3.65)</td></tr><tr><td>Men * on<br>furlough</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.866<br>(-0.49-2.22)</td></tr><tr><td>Men * remote<br>work<br>Women's<br>occupation<br>Out of<br>employment</td><td>-1.821<br>(-4.04-0.40)</td><td>-1.540<br>(-5.68-2.60)</td><td>-1.198<br>(-6.38-3.98)</td><td>-2.391<br>(-6.10-1.32)</td><td>1.185<br>(-3.35-5.72)</td><td>2.063<br>(-1.82-5.94)</td><td>1.627<br>(-5.78-9.03)</td><td>2.009<br>(0.48-3.53)</td></tr><tr><td>On leave</td><td>-1.443<br>(-2.88- -0.00)</td><td>-4.986<br>(-7.65- -2.32)</td><td>0.433<br>(-4.29-5.16)</td><td>-0.340<br>(-2.66-1.98)</td><td>-2.657<br>(-5.44-0.12)</td><td>-0.174<br>(-3.02-2.67)</td><td>-1.341<br>(-6.57-3.89)</td><td>1.221<br>(0.34-2.09)</td></tr><tr><td>On furlough</td><td>-2.949<br>(-4.74- -1.15)</td><td>-5.674<br>(-9.10- -2.24)</td><td>-5.502<br>(-10.00- -0.99)</td><td>-1.359<br>(-4.51-1.80)</td><td>-3.811<br>(-7.90-0.28)</td><td>-2.408<br>(-6.82-2.00)</td><td>-3.744<br>(-8.82-1.33)</td><td>1.485<br>(0.46-2.50)</td></tr><tr><td>Remote work</td><td>0.127<br>(-1.29-1.54)</td><td>-0.790<br>(-3.40-1.82)</td><td>1.362<br>(-2.34- 5.07)</td><td>-0.567<br>(-3.31-2.18)</td><td>-1.731<br>(-5.16-1.80)</td><td>-1.861<br>(-5.07-1.35)</td><td>-2.612<br>(-7.45-2.23)</td><td>0.427<br>(-0.41-1.26)</td></tr></tbody></table>
<table><caption>Table 5: (Continued)</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="3">Model 2e</th><th colspan="4">Model 2f</th></tr><tr><th>All<br>coef (95% CI)</th><th>Cooking<br>coef (95% CI)</th><th>Shopping<br>coef (95% CI)</th><th>Laundry<br>coef (95% CI)</th><th>Ironing<br>coef (95% CI)</th><th>Repairs<br>coef (95% CI)</th><th>Child care<br>coef (95% CI)</th><th>Hours spent<br>in child care<br>coef (95% CI)</th></tr></thead><tbody><tr><td>Men * women<br>out of<br>employment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-2.138<br>(-4.16- -0.01)</td></tr><tr><td>Men * women<br>on leave</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-1.460<br>(-2.55- -0.36)</td></tr><tr><td>Men * women<br>on furlough</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-1.513<br>(-2.80- -0.21)</td></tr><tr><td>Men * women<br>remote work</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.864<br>(-1.80-0.08)</td></tr><tr><td>Constant</td><td>35.05<br>(33.48-36.61)</td><td>31.70<br>(28.76-34.62)</td><td>37.22<br>(33.74-40.69)</td><td>18.24<br>(15.60-20.86)</td><td>14.60<br>(11.59-17.59)</td><td>60.13<br>(57.11-63.14)</td><td>41.99<br>(39.85-44.13)</td><td>2.051<br>(1.56-2.53)</td></tr><tr><td>Observations</td><td>1,871</td><td>1,881</td><td>1,882</td><td>1,882</td><td>1,595</td><td>1,836</td><td>572</td><td>888</td></tr><tr><td>R-squared</td><td>0.040</td><td>0.039</td><td>0.056</td><td>0.010</td><td>0.015</td><td>0.011</td><td>0.081</td><td>0.097</td></tr><tr><td>Number of ID</td><td>792</td><td>795</td><td>798</td><td>795</td><td>712</td><td>784</td><td>284</td><td>397</td></tr></tbody></table>

Source: Coping with COVID-19, ELIPSS/CDSP.

Note: "First lockdown" is survey wave 3 for housework and survey wave 2 for child care and share of child care. "All" does not include child care. Linear regression coefficients with 95% confidence intervals in parentheses.
<table><caption>Table 6: Lockdowns' effects on the male share of unpaid work within couples: The role of an educational gap (individual fixed effects, clustered SE) – Model 3</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="3">Model 3a</th><th colspan="4">Model 3b</th><th rowspan="2">Hours spent<br>in child care<br>coef (95% CI)</th></tr><tr><th>All<br>coef (95% CI)</th><th>Cooking<br>coef (95% CI)</th><th>Shopping<br>coef (95% CI)</th><th>Laundry<br>coef (95% CI)</th><th>Ironing<br>coef (95% CI)</th><th>Repairs<br>coef (95% CI)</th><th>Child care<br>coef (95% CI)</th></tr></thead><tbody><tr><td>First lockdown<br>(ref. out of<br>lockdown)</td><td>1.023<br>(0.22-1.81)</td><td>0.444<br>(-0.90-1.79)</td><td>6.350<br>(3.76-8.93)</td><td>-0.145<br>(-1.42-1.13)</td><td>-0.823<br>(-2.15-0.50)</td><td>0.093<br>(-1.74-1.92)</td><td>-3.732<br>(-6.57- -0.88)</td><td>1.011<br>(0.41-1.60)</td></tr><tr><td>Last lockdown<br>(ref. out of<br>lockdown)</td><td>0.237<br>(-0.51-0.99)</td><td>0.960<br>(-0.50-2.42)</td><td>1.544<br>(-0.03-3.11)</td><td>-1.583<br>(-2.84- -0.32)</td><td>-0.942<br>(-2.57-0.69)</td><td>-0.151<br>(-1.80-1.50)</td><td>-0.970<br>(-3.35-1.41)</td><td>0.918<br>(0.33-1.50)</td></tr><tr><td>Men * First<br>lockdown</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.838<br>(-1.57- -0.10)</td></tr><tr><td>Men * Last<br>lockdown</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.469<br>(-1.29-0.35)</td></tr><tr><td>First lockdown *<br>Education of<br>men > women</td><td>-0.936<br>(-2.58-0.71)</td><td>-0.808<br>(-3.58-1.96)</td><td>1.333<br>(-3.55-6.21)</td><td>-2.709<br>(-5.45-0.03)</td><td>0.655<br>(-3.02-4.33)</td><td>2.132<br>(-1.51-5.77)</td><td>3.964<br>(-3.03-10.95)</td><td>-0.478<br>(-1.99-1.04)</td></tr><tr><td>Last lockdown *<br>Education of<br>men > women</td><td>0.535<br>(-0.92-1.99)</td><td>-1.346<br>(-3.96-1.26)</td><td>1.549<br>(-1.51-4.69)</td><td>1.640<br>(-1.62-4.90)</td><td>0.969<br>(-2.77-4.71)</td><td>-1.153<br>(-4.56-2.26)</td><td>3.735<br>(-3.09-10.56)</td><td>-0.693<br>(-2.04-0.66)</td></tr><tr><td>Men * First<br>Lockdown *<br>Education of<br>men > women</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.716<br>(-1.15-2.58)</td></tr><tr><td>Men * Last<br>lockdown *<br>Education of<br>men > women</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.360<br>(-1.36-2.08)</td></tr><tr><td>Constant</td><td>35.78<br>(35.42-36.12)</td><td>34.06<br>(33.42-34.69)</td><td>40.55<br>(39.62-41.47)</td><td>17.85<br>(17.24-18.45)</td><td>14.77<br>(14.02-15.51)</td><td>62.38<br>(61.54-63.21)</td><td>44.57<br>(43.40-45.74)</td><td>2.569<br>(2.38-2.74)</td></tr><tr><td>Observations</td><td>1.886</td><td>1.896</td><td>1.897</td><td>1.897</td><td>1.61</td><td>1.851</td><td>590</td><td>915</td></tr><tr><td>R-squared</td><td>0.007</td><td>0.002</td><td>0.042</td><td>0.011</td><td>0.002</td><td>0.004</td><td>0.027</td><td>0.038</td></tr><tr><td>Number of ID</td><td>794</td><td>796</td><td>799</td><td>797</td><td>713</td><td>785</td><td>287</td><td>401</td></tr></tbody></table>

Source: Coping with COVID-19, ELIPSS/CDSP.

Note: "First lockdown" is survey wave 3 for housework and survey wave 2 for child care and share of child care. "All" does not include child care. Linear regression coefficients with 95% confidence intervals in parentheses.

## 5. Discussion and conclusions

This study builds on longitudinal data and employs variations in policies implemented to curb the pandemic to examine differences in couples' divisions of household and care
work. We explore two explanatory factors: the effect of each partner's time availability (as measured by changes in employment conditions) and relative education (as a proxy for bargaining power in the couple). We also document variations of these effects along gender lines.

Our findings confirm prior studies showing that men's share of housework was higher during both lockdown periods in France than in the out-of-lockdown period. As we hypothesised (H1), this is partly due to men's increased time availability. Indeed, we show that changes in working conditions have significantly shaped men's share of unpaid work during the pandemic. Moreover, men's share of unpaid work strongly depended on whether the partner was at home. This finding is in line with the time availability approach (Hiller 1984), suggesting that the time devoted to unpaid tasks depends on couples' constraints. The time availability hypothesis broadly holds when it comes to the division of child care, as men's hours spent on child care increased during the last lockdown only when men were on leave from work. Hence our results point at both the impact of absolute time availability – because men working from home, on furlough, on leave, or out of employment did more household work – and at relative time availability, taking into account the partner's employment situation.

As for the relative resources hypothesis (H2), it seems to apply only for some tasks. In particular, men's poor contribution to laundry is even scarcer if men are more educated than their partners. All in all, our findings suggest that bargaining power did not matter much in the reconfiguration of housework during the lockdown periods in France. Rather, our findings hint at the central role of gender norms in shaping couples' changes in the division of domestic work during lockdowns (H3). Our data show that although men's share of housework was higher during both lockdown periods, this did not concern all tasks. While we found a stronger contribution of men to shopping, other tasks, including child care, mostly fell on women's shoulders. This is in line with the doing gender perspective (West and Zimmerman 1987), according to which women and men enact gender scripts when they divide work. Shopping was one task that was shared more equally before the pandemic (Kan, Sullivan, and Gershuny 2011), but it became a more masculine practice over the course of 2020 and 2021 (cf. Biroli et al. 2021). In the context of the pandemic, and especially during the first lockdown, shopping was perceived as potentially dangerous – since masks and other barrier measures were not widely available – but also as an opportunity to take a walk, a relief from home seclusion, and an occasion to interact with others. This finding suggests that men not only engaged in more 'masculine' tasks but also devoted more time to relatively less routine tasks, which also confirms that women tend to be a “shock absorber of last resort” in periods of crisis (Elson 2002; see also Ferragina 2019).

During lockdowns, men also spent more time on child care – an activity in which some have been more involved in recent years (Altintas and Sullivan 2016). However,
their involvement did not translate into more egalitarian shares because women
performed even more child care than in the out-of-lockdown period. This finding is also
in line with previous research showing that child care induced the most important
negotiation in the redivision of labour, as couples with children reported more tension at
home during the first lockdown (Safi et al. 2020).

We acknowledge that our analysis has some limitations. Because we do not have
information on household and care work before the first lockdown, we use the out-of-
lockdown period during the COVID-19 pandemic as a reference. While this period does
not necessarily reflect couples’ divisions of work before the pandemic, it does provide us
with a reference point against which to compare arrangements in household life under
strict lockdown rules. Finally, more detailed data on tasks carried out in the home during
lockdowns, such as those included in time-use diaries, would give us a more accurate
depiction of unpaid work involvement.

In conclusion, we contribute to the literature on unpaid work and the COVID-19
pandemic by documenting differences in household life organisation under differing anti-
pandemic policies. Our results reveal that men spent more time on child care during the
two lockdown phases, although this did not translate into a more equitable gender
distribution of tasks within the household. We found a significantly higher share of
unpaid work only in the first lockdown, although more detailed models show that this
was mostly due to shopping and decorating in the case of families with children of school
age. These tasks are closer to leisure when compared to routine unpaid tasks, and
therefore this higher investment in unpaid tasks displays a gendered pattern. Finally, our
results illustrate the complementarity of the existing theoretical approaches in explaining
changes in domestic division of labour during the pandemic.

It is important to stress that our findings are context related; research has
investigated the relationship between macro-level factors, social policies, and the
domestic division of work (Anxo, Baird, and Erhel 2017; Fuwa 2004; Mandel, Lazarus,
and Shaby 2020). For instance, Mandel, Lazarus, and Shaby (2020) show that even
though wives undertake more housework than their spouses in most countries, in more
gender-egalitarian societies, women have a stronger bargaining power in negotiating
housework responsibilities within the couple. Our results must therefore be read a fortiori.
Even in a country like France, where women's labour market participation is relatively
high compared to other European countries (Eurostat 2021) and gender egalitarianism is
increasingly a mainstream cultural script, the domestic sphere resists change, and it does
so amidst a drastic peacetime transformation in the organisation of everyday life.
Scrutinising both the overall and the task-to-task shifts in unpaid work within couples,
we show that even in 'hard times,' the process of negotiating household work between
men and women is still intensely driven by gender norms.
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