Understanding relative commuting within dual-earner couples in Germany

Transportation Research Part A 134 (2020) 113–129

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Transportation Research Part A journal homepage: www.elsevier.com/locate/tra

Understanding relative commuting within dual-earner couples in Germany

T

Bhuvanachithra Chidambaram , Joachim Scheiner ⁎

TU Dortmund University, Faculty of Spatial Planning, Department of Transport Planning, 44227 Dortmund, Germany

ARTICLE INFO

ABSTRACT

Keywords: Commute distance Dual-earner couples Economic power Car access Gender roles Gender differences

Women’s entrenched workforce participation has contributed to the rise in dual-earner households over the last two decades in Germany. In transport research, dual-earner households are gaining more importance over time, as intra-couple interactions play a significant role in housing, mobility and travel behaviour. Various studies on gender differences in commuting claim that women commute shorter distances than men due to their secondary labour status within the family. However, this gender gap in commuting behaviour has steadily declined over recent decades. Nevertheless, the intra-household factors causing the gender gap in commute distance between partners are not yet fully understood. The study examines the association between intra-household arrangements (economic power, car access, labour and domestic worksharing and preferences on work-sharing) within dual-earner couples and the gender gap in their commute distances (called relative commuting here). We used the German National Time Use Survey and employed regression analysis. Four general findings of the study are: (a) male partners commute longer than female partners, (b) gender differences in economic prospects increase the gender gap; (c) a relative dominance of car access by the female partner reduces the gender gap in commute distances, and (d) an increase in time spent on unpaid work by the male partner decreases the gender gap.

1. Introduction Despite the gender inequalities in labour market demand in Germany, women’s employment rate significantly increased from 56% in 1992 to 75% in 2017 (Crößmann and Mischke, 2018; Statistisches Bundesamt, 2014). This upward trend has contributed to the increase in dual-earner households: 50% in 1996, 54% in 2013 and 61% in 2017 of total couple households (Keller and Haustein, 2013; Keller and Kahle, 2018). Labour market reforms in Germany have encouraged this increase. In transport research, (heterosexual) dual-earner households undoubtedly attract more attention than single-earners, as they are invariably the central component in the job-commute-residence nexus. Most empirical studies have attempted to unravel the social complexity of this nexus by focusing on commute distances or time (Beck and Hess, 2016; Sultana, 2005; van der Klis and Mulder, 2008). They have observed that dual-earner couples often trade-off between the two work locations and the residence to optimise total commute distance or time. Accordingly, women from dual-earner households tend to spatially restrict their job search area and allow their partners to undertake long-distance commuting to avoid the high opportunity costs arising from migration to the partner’s work location. In Germany, men spend about 27 min per day on average for commuting and 22 min for domestic travel, while women spend about 15 min per day for commuting and 27 min for domestic travel (European Communities, 2004). This commute gap has

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Corresponding author. E-mail addresses: [email protected] (B. Chidambaram), [email protected] (J. Scheiner).

https://doi.org/10.1016/j.tra.2020.02.006

0965-8564/ © 2020 Elsevier Ltd. All rights reserved.

Transportation Research Part A 134 (2020) 113–129

B. Chidambaram and J. Scheiner

also been found in other countries (European Communities, 2004 for all EU countries, Kwan and Kotsev, 2015 in Bulgaria; Mcquaid and Chen, 2012 in the UK; Motte-Baumvol et al., 2017 in France; Östh and Lindgren, 2012, van Ham and Hooimeijer, 2009 in the Netherlands; Sang et al., 2011 in the USA). Over time, the gender gap in commute distance and other measures of travel, such as nonwork travel distances and mode choices, tends to decline. The substantial decrease in car use and licensing among young men and increased travel distances among women have jointly contributed to the decline (Kuhnimhof et al., 2012; Tilley and Houston, 2016). Despite this convergence, the gender commute gap remains (de Meester and van Ham, 2009; Kim et al., 2012; Konrad, 2016). Most studies on commute distance differences between men and women (de Meester and van Ham, 2009; Fan, 2017; Holz-Rau et al., 2014; Konrad, 2016; Plaut, 2006; Scheiner and Holz-Rau, 2012a) claim that women's social roles (housework, children and family care) and secondary labour status within the family (see Table 1 below for a sample distribution from Germany) leave them with limited transport resources, i.e. money, time and mobility, for commuting to work. For instance, a woman typically has lower income and, thus, bargaining power than her male partner (Boll et al., 2017). Therefore she is held responsible for the domestic labour, albeit this not being her preference. This may influence her travel choices in various ways: first, she accepts a job below her qualification level that allows short-distance commuting; second, she makes more trips than her partner to combine work and household maintenance trips (e.g., child chauffeuring, shopping, errands); and third, she may have less car access, particularly in 'low-car' couples sharing a car (Scheiner and Holz-Rau, 2012b). The present study examines the relationship between intra-household allocations and the gender commute distance gap (also called 'relative commuting') in heterosexual dual-earner couples in Germany. Additionally, we present an analysis of various household types to set the stage, asking to what extent gender differences in commute distance and intra-household allocations vary by household type (in single-earner and dual-earner couples). While the limitation to heterosexual couples may be seen as a drawback in the broad, multi-shaded and diverse field of gender studies (see for critical discussions Law, 1999; Smart and Klein, 2013), most gender roles, symbolic codes of gender and gendered behaviours are constantly negotiated and renegotiated between men and women. Furthermore, the vast majority of people are heterosexual, e.g. over 95% in the US (Gates, 2011) and 93–94% in Europe and, specifically, Germany (Deveaux, 2016). Additionally, our data do not permit the identification of homosexual couples (in contrast to, e.g., the US National Household Travel Survey, see Smart and Klein, 2013). The focus on the commute inevitably narrows the perspective on travel behaviour, as feminist researchers have long pointed out, the gendered character of travel behaviour can only be adequately understood by looking at a broader set of mobilities, including care trips and household maintenance trips, or non-realised trips (Scheiner, 2016; de Madariaga and Zucchini, 2019). Nonetheless, the commute is the economic nexus of household travel, thus reflecting economic power in couple households in travel behaviour. Our study is primarily motivated by a desire to understand better the effects of these various intra-household allocations on the commute distance gap by using a simultaneous analysis. The latter is crucial, as these effects may be expected to intersect, rather than working in isolated ways. We empirically explore various dimensions of intra-household allocations: economic prospects, car access, and division of paid and unpaid labour. The novelties of our study are, firstly, that we consider both actual and preferred worksharing in dual-earner couples, thus acknowledging the effect of preferences for certain gender role patterns (traditional, egalitarian and reverse). Secondly, we control for personal income, which is hardly ever possible in the transport literature due to a lack of information on individual income in travel surveys (but see Boarnet and Hsu, 2015; Black et al., 2014; Preston and McLafferty, 2016). Thirdly, we use information on domestic work-sharing, while transport studies are typically limited to out-of-home activities, thus employing a reductionist understanding of activity patterns and work-sharing. Germany has a somewhat conservative culture with respect to gender relations (Kan et al., 2011; van der Lippe et al., 2011), placed between the Mediterranean and the Nordic social democratic regime. The German conservative background is reflected in some notable incentives for couples to adopt male-breadwinner-and-female-housewife type work-sharing, including the joint income tax system for couples and the limited provision of public childcare (Cooke, 2006; Kan et al., 2011). Parental leave regulations included little financial benefit until 2006 (Geisler and Kreyenfeld, 2012), although they were quite generous (36 months since 1992). Also, Germany has undertaken considerable efforts for expanding childcare facilities, encouraging women into employment and fathers to take paternal leave (Geisler and Kreyenfeld, 2012). Hence gender relations have recently experienced a process of rapid change, although there is constant negotiation between conservative forces that favour traditional work-sharing, and attempts to achieve more gender equality (Beck-Gernsheim, 2012). This paper is structured as follows. In Section 2, we briefly outline theoretical perspectives on the effects of intra-household allocations in couples on the commute gap. In Section 3, we discuss the data and variables used. Section 4 presents the empirical analysis and findings. We conclude with a discussion and point out limitations and further directions for research in Section 5. 2. Literature review and hypotheses Gender and travel behaviour has evolved as a research field from the late 1970s (Rosenbloom, 1978), with Law's (1999) seminal paper indicating a significant shift from the study of women's issues to gender issues, and from transport to 'daily mobility'. This dual shift firstly marked a transition from a perspective focused on a population group (i.e. women) that was recognised as being ignored and disadvantaged in transport research and planning to a relational understanding of cross-gender and intra-gender differences according to specific needs, behaviours and meanings associated with mobility. Secondly, it was part of a cultural turn in transport studies that argued gender should be understood as a social category that structures social relationships, power interactions, inequalities and subject identities. This line of inquiry opened the gates for various theoretical approaches and research streams including 'new mobilities', action theories and practice theories (see Hanson, 2010, on an attempt to bridge two basic methodologies 114

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Fig. 1. Relative commuting and intra-household arrangements within dual-earner couples. Graphic: authors' draft.

in gender/transport studies, Schwanen, 2011, for a mixed-methods empirical study, Smart et al., 2017, for rare empirical work on the travel behaviour of homosexual couples). Intra-household resource allocations have been widely acknowledged in transport studies (de Meester and van Ham, 2009; Fan, 2017; Kawabata and Abe, 2018; Scheiner and Holz-Rau, 2012a). Several hypotheses concerning intra-household attributes such as economic power, resource access, social roles and preferences have been analysed to understand gender differences in activity-travel patterns. In the following, these hypotheses are revisited and extended with a focus on commuting to make predictions on the commute gap between dual-earners. Fig. 1 illustrates the hypotheses. 2.1. Socio-economic positions An important perspective to explain the gender commute gap holds that economic factors (income and work hours) and social status (i.e. education level and employment status) in couples are at work. Research claims that women with lower educational qualifications and lower income commute shorter distances than their male counterparts (McDonald, 2000; Cristaldi, 2005; Shearmur, 2006). Low wages have rendered longer commutes unbeneficial for women, encouraging them to accept locally available job offers (Blumenberg, 2004; de Meester and van Ham, 2009). The location pattern of “typical women's jobs” plays an additional role in encouraging short-distance commuting (Giménez-Nadal et al., 2018). In stark contrast to the above studies, some researchers have demonstrated that women commute longer than men for low incomes (Black et al., 2014; Preston and McLafferty, 2016). For our paper, we conclude that there is still no strong empirical evidence linking economic power and commuting within dual-earner households due to the lack of information on personal income in travel surveys. We propose the following. H1. Male partners’ higher contribution to household income, higher education level and higher employment position contribute to their commutes being longer than those of their female partners. 2.2. Car access within couples For several decades it has been realised that in low-car households, women retain lower car access than their partners and this causes women to accept jobs that allow short-distance commuting (Guiliano, 1979; Hanson and Johnston, 1985; Rutherford and Wekerle, 1988). It has also been claimed that the spatial distribution of female-dominated jobs makes women less dependent on private cars than men (Matas et al., 2010). This counters the argument that women are more in need of cars than men due to their multiple obligations (Scheiner, 2014). The evidence shows strong gender convergence in mode use over the past decades in Germany (Konrad, 2016), although the percentage of public transport commuting is still slightly higher for women than men (16% versus 14%), and the same is valid for walking (11% versus 8%) (calculation based on https://www.mobilitaet-in-tabellen.de, 30.10.2019). Recent studies have found that a higher level of car availability, for instance, in multi-car households, has decreased the gender gap in car access in dual-earner households (Crane, 2007; Scheiner and Holz-Rau, 2012b). However, this has only worsened the negotiating 115

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position of female partners in terms of taking on additional household trips like child chauffeuring and shopping (Han et al., 2019; Scheiner, 2016). In one-car couples, partners need to negotiate for the car, notably, when both commute longer distances, whereas in multi-car couples there is no such negotiation. Therefore, we propose the following hypothesis: H2. Lower car access among female partners than among their male counterparts in one-car couples leads to a more significant gender gap in commute distances, whereas the gender gap in commute distances between partners in multi-car couples is generally weaker.

2.3. Gender roles in workload allocation The recent transformation of family households from a male-breadwinner type to a dual-earner model reflects shifts in gender role ideologies in the labour market. However, in many couples women allocate fewer working hours to paid employment and more to unpaid work than men. Also, the literature claims that culturally prescribed gender role structures still remain unchanged within households (Coltrane, 2000; Warren, 2003). Women from dual-earner households still perform a disproportionate share of in-home maintenance like cooking, washing, cleaning, shopping and childcare, which has led to the – somewhat contested – hypothesis of a “second shift” at home (Hochschild, 1989). In gender studies, this is referred to as the household responsibility hypothesis (Kawabata and Abe, 2018; Silveira Neto et al., 2015). According to this, women take on household and family responsibilities that constrain them both temporally and spatially, thus preventing more gender equality and restricting women’s economic independence, activity spaces and access to labour markets, which ultimately leads to shorter commuting distances (Lee and McDonald, 2003; McQuaid and Chen, 2012). The following hypotheses arise. H3. Male partners spend more time on employment than their female partners, and this affects their commute distance positively. H4. Female partners tend to do more household and family work (e.g. child care) than their male partners, and this family obligation negatively affects their commute distance.

2.4. Gender preferences From a social-psychological perspective, there is another view to this unequal division of labour in couples. This claims that the unequal allocation of paid work and domestic work is due to gendered preferences1 (Crompton and Lyonette, 2005; Lewis et al., 2008; Wilkie et al., 1998). It is thus argued that men’s preferences are principally career-oriented whereas women’s preferences are heterogeneous, partly career-oriented and partly family-oriented (Hakim, 2000). Gender inequality in the division of household work is an issue for couples if their preferences do not match their tasks, as this may ultimately end up in injustice. Nevertheless, recent research also suggests that gender roles are increasingly becoming less traditional, and gradually shifting towards egalitarianism (Scheiner, 2013; Neilson and Stanfors, 2014; Sayer, 2016). Also, the empirical evidence suggests that there is no association between the gender gap in domestic work and the gender gap in preferences for domestic work between partners (Crompton et al., 2005; Fortin, 2005), but Ettema and van der Lippe (2009) find that traditional role attitudes among women are associated with them accounting for a smaller share of paid work in a couple. We are not aware of any evidence concerning how gender preferences concerning unpaid work impact partners’ commute distances. The gender preference perspective remains highly contested. It has been claimed that even if preferences can be shown to affect travel behaviour – including commuting – “preferences may have their roots in societal traditions and may hence operate on the basis of patriarchy, inequality and culturally defined social roles. Thus, preferences may mirror societal power relationships rather than having much explanatory power in themselves” (Scheiner and Holz-Rau, 2012b). On the other hand, the preference hypothesis can hardly be ignored, given the relatively high level of individual freedom in modern western societies, indicating the need for empirical research. This suggests the following hypothesis: H5. Traditional preferences concerning intra-household work-sharing increase the gender gap in commuting. Overall, the conflicting claims concerning the relationship between economic power and relative commuting among dual-earners, the competing views on actual versus preferred paid and unpaid work-sharing, and the lack of acknowledgement of in-home activities in transport studies call for more research that simultaneously accounts for their effects on commuting within dual-earner couples. 1 In recent transport research, the term attitudes is often used to capture preferences. Attitudes are a person's evaluations of objects, including stimuli, behaviours, or concepts (Herkner 1991, 180-273). Preferences are a particular type of such evaluations. Preferences are dispositions towards an alternative, typically conceived of as shaping individual or household decisions and actions (Mas-Colell, Whinston, and Green 1995). However, such evaluations also include levels of (dis)satisfaction, by which existing or perceived characteristics of an object are assessed. A public transportliking person living far from public transport has a strong preference (positive attitude) towards public transport, but may be dissatisfied with public transport as it is (negative attitude). As we are interested in the first type of attitudes ("what people want"), we use the term preference for clarity, wherever possible.

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Table 1 Working type, children and car ownership of married or cohabiting couples in the sample. Married or cohabiting couples

Couples with child (ren) N(%)

Couples w/o car

N(%)

Couples w/o child (ren) N(%)

Dual-earner householdsa M full time & F part time Both M & F full time M part time & F full time Both M & F part time Total

985 (38.4) 495 (19.3) 44 (1.7) 72 (2.8) 1596 (62.3)

106 (15.9) 164 (24.6) 12 (1.8) 21 (3.2) 303 (45.5)

Single-earner householdsb M full time & F not working M part time & F not working M not working & F full time M not working & F part time Total

409 (15.9) 57 (2.2) 93 (3.6) 120 (4.7) 679 (26.5)

Both M & F not working Total number of couples

289 (11.2) 2564

a b

All couples

N(%)

Couples with one car N(%)

Couples with 2 + cars N(%)

879 (46.3) 331 (17.4) 32 (1.7) 51 (2.7) 1293 (68.1)

17 (17.7) 11 (11.5) 2 (2.1) 9 (9.4) 39 (40.6)

307 (31.0) 174 (17.6) 22 (2.2) 27 (2.7) 530 (53.6)

661 (44.7) 310 (20.9) 20 (1.4) 36 (2.4) 1027 (69.4)

72 (10.8) 22 (3.3) 39 (5.9) 38 (5.7) 171 (25.7)

337 (17.8) 35 (1.8) 54 (2.8) 82 (4.0) 508 (26.8)

9 (10.4) 4 (4.2) 5 (5.2) 4 (4.2) 23 (24.0)

159 (16.1) 30 (3.0) 45 (4.6) 57 (5.8) 291 (29.4)

241 (16.3) 23 (1.6) 43 (2.9) 59 (4.0) 366 (24.7)

192 (28.8) 666 (26.0)

97 (5.1) 1898 (74.0)

34 (35.8) 96 (3.7)

168 (17.0) 989 (38.6)

87 (5.9) 1480 (57.7)

Households in which both partners reported at least minimum hours of paid employment. Households in which only one partner reported at least minimum hours of paid employment.

3. Data and variables used in the analysis 3.1. Sample This study uses the German Time Use Survey (GTUS), conducted by the Federal Statistical Office in 2012/2013 and provided by the Forschungsdatenzentrum (www.forschungsdatenzentrum.de). It is a cross-sectional survey, repeated once in ten years, with the survey instrument changing over time. The GTUS includes a time-use diary, personal and household questionnaire. In order to capture seasonal variation, the survey was conducted continuously over a period between August 2012 to July 2013. The time-use diary randomly samples the information of 12,254 persons (aged 10 years and older) from 4775 households for three random days (two weekdays and one weekend day). In contrast to travel surveys, the German time-use survey uniquely contributes to transport research by providing information on (i) in-home activities; (ii) personal income which allows the analysis of intra-household economic power, (iii) gender role preferences, and (iii) extremely differentiated trip purposes. Some of the limitations are, firstly, that short trips and activities are underrecorded, as the activities are recorded in ten-minute intervals. Secondly, the survey does not include trip distance. Instead, the distance and duration of travel to the workplace are separately recorded in the personal questionnaire. Table 1 shows the types of cohabiting couples: dual-earner, single-earner and non-working households. The dual-earner couples (our group of interest) constitute about 62% of all couple households. Accordingly, 1596 heterosexual couples are considered for the analysis, with an age range between 25 and 70. There are some retirees (M:1.44%; F:0.75%) and students (M:0.25%, F:0.5%) included who have a side job. The study demarcates full-time and part-time employment based on working hours in primary and secondary jobs. Respondents who work between 30 and 40 h per week in their primary jobs and/or between 20 and 30 h per week in their secondary jobs are defined as full-time workers while those who work less than 30 h per week in their primary jobs and/or between 10 and 20 h per week in their secondary jobs are defined as part-time workers.2 3.2. Variables The outcome variable for our regression analysis is the gender gap in commuting in dual-earner couples, defined as the difference in self-reported commute distances between male and female partners (M-F). Such relative measures have been used before in studies of the gender-transport nexus (e.g. Motte-Baumvol et al., 2017; Scheiner, 2013). We use the difference as a measure instead of the distance ratio as calculating the ratio results in extreme values. The following are the explanatory variables considered for analysis. 3.2.1. Socio-economic variables We use direct information on personal monthly net income for our analysis. We generate the metric variable years of education, where we combine the categorical variables of German school and professional education, and convert those into years of education. Both income and education are measured initially at the individual level, and then the differences between partners are calculated. 2

Few respondents have secondary jobs, and they are seasonal unlike primary jobs. 117

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Table 2 Description of respondents' work status. Work status

Description

Examples

1. Salaried employee

White-collar jobs including employees and civil servants, with mostly higher net income, job security and pensions Blue-collar jobs, both high-skilled and low-skilled. Average net income is slightly lower than that of salaried employees

High-skilled professionals (e.g. technicians, teachers and professors) and low-skilled clerical jobs (e.g. office and administrative jobs) High-skilled occupations such as crafts and trades and low-skilled jobs such as cleaning or construction jobs, elementary jobs at plants and industrial machine operation Engage in non-technical activities such as agriculture, art and entertainment, wholesale retail, the construction business and other knowledge-intensive activities

2. Labourers 3. Self-employed

Mostly highly educated with much work experience. They enjoy the benefits of job flexibility and less mobility. However, they are exempt from social protection benefits (e.g. statutory minimum wage, public holidays, paid sick leave)

Regarding work status, we generate relative work status at the partnership level by combining the two partners' individual work status as described in Table 2. We also include household monthly income to explore the effect of household monetary resources. Furthermore, we also tested the age difference between partners, as higher age may suggest social dominance, and age (or cohort membership) may also reflect different stages or types of socialisation. However, we subsequently excluded the variable due to the lack of significant effects. 3.2.2. Car access We have no direct information on personal car availability but on the number of household cars. Additionally, car use can be extracted from the activity diaries. We use both variables to construct a variable of relative car access. We compute car usage for both partners in terms of time spent driving on the three diary days. We take the percentage of both partners from the total to determine which partner dominates in car use (equaling > 60 percent of the total; we consider both partners drive the same amount in cases where both are in the range 40–60 percent). We distinguish between couples who share one car (low-car households) and multiple-car households. This results in the categories shown in Table 6. 3.2.3. Gender roles in workload allocation We measure social roles by actual time spent on paid and unpaid work. Paid work is the hours spent in employment per day, whereas unpaid work is the hours spent on household work, childcare, family care and trips carried out for domestic work per day. Table 3 shows the description of paid and unpaid work in detail. For all variables, we calculate the percentage of time spent by a partner in total time spent by a couple. We classify couples based on their work-sharing pattern type (traditional, egalitarian and reverse roles), following Scheiner (2013) and Grunow et al. (2007, p. 170) (Table 6). In the traditional role model, female partners spend more time in unpaid work than male partners. In the egalitarian model, both partners spend equal amounts of time, and in the reverse model, male partners spend more time than female partners in unpaid work. For paid work, the opposite is true. Additionally, we include the number of children below ten years of age per household to understand how their presence influences the commute gap. The reasoning behind this age threshold is that in Germany children's mobility tends to become more selfdependent at this age when they enter secondary school (Manz et al., 2015). We collapse households with older children and without any children into one category to avoid subgroups too small for analysis. 3.2.4. Gender preferences We measure male and female preferences based on the match between the actual roles they perform (i.e. time use), and their attitude towards the respective role. This has two different forms for paid and unpaid work due to the questionnaire. Table 3 Description of time spent on paid and unpaid activities. Time spent on paid and unpaid activities (hours/day)

Description

1. Paid work in employment and employmentrelated activities 2. Unpaid work a. In-home 1. Household work

Primary jobs and secondary jobs

2. Childcare 3. Family care b. Out-of-home

In-home and out-of-home activities Preparing and clearing away meals, maintenance of house, clothing and textiles, gardening and pet care, construction and maintenance services, shopping for food and other household-related purchases Engaging with children: supervision, homework, sports, storytelling, other activities Caring for elders and other members of household Out-of-home activities like shopping and travel time associated with household work, shopping, childcare and family care

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Table 4 Gender preference variables used for the analysis. Attitude towards actual share of time spent on unpaid work

Actual work-sharing of unpaid work (time use) Traditional F > M

Egalitarian F = M

Male attitude Time is insufficient Time is sufficient

Male partner preferences Prefers egalitarian role Prefers reverse role Prefers traditional role Prefers egalitarian role

Female attitude Time is insufficient Time is sufficient

Female partner preferences Prefers traditional role Prefers traditional role Prefers traditional role Prefers egalitarian role

Reverse M > F Prefers reverse role Prefers reverse role

Prefers egalitarian role Prefers reverse role

For paid work, the data include a direct measurement of preferred working hours per week. We tested this in various formulations (categories, continuous scale), but finally excluded it due to a lack of effect. For unpaid work, the procedure is more complicated, as there is no direct preference measure. However, the respondents state whether or not the time they actually spent on unpaid work (childcare, family and household work) in the weeks prior to the survey was sufficient or if they would have preferred to spend more time on any of these activities. Responses were based on a five-point Likert scale from completely sufficient (1) to totally insufficient (5). This does not in itself reflect a work-sharing preference. We first transformed this variable into a binary scale, sufficient (1, 2 and 3) and insufficient (4 and 5). We combined this binary variable with the realised type of work-sharing (Table 4) to draw conclusions on preferred work-sharing. For instance, when a male partner from a traditional household feels the time they actually spend on unpaid work is insufficient, they prefer a more egalitarian role distribution. If they feel satisfied, this implies that they are satisfied with the traditional role. Conversely, when a female partner in a traditional household feels her time spent on unpaid work is insufficient, she would like to spend even more time in unpaid work than she actually does. This denotes that she prefers a traditional role model (maybe even strongly traditional). We use the individual level (male and female preferences) variables instead of relative variables for simplicity, to avoid confusion due to more relative dummy variables. We are aware that this measurement is clearly less than perfect. Many individuals may feel that the amount of time they spend on any activity is insufficient, and answer affirmatively. Hence, the variable we use may reflect work-sharing preferences only to a limited extent. However, a more direct measurement of gender work-sharing preferences may have other, equally serious biases. Our data are a rare case of including some information on preferences, and we take this opportunity to contribute to an otherwise underresearched question and shed some light on the preference hypothesis. 3.2.5. Residential location We include the type of residential location to examine its associations with the commute gap. More traditional work-sharing may be expected in rural areas (Grimsrud, 2011; Istenič, 2007). 3.3. Analysis Descriptive analysis of the above variables is performed to portray gender differences. We compare various household types: single-earner (male and female breadwinners), dual-earner (with and without children), and single-person male and female households (with and without children). We tested the gender differences using t-tests. First, we conducted a series of independent-samples t-tests between male and female single earners, and between male and female singles (with and without children, respectively). Second, within dual-earner couples (with and without children), we used paired sample t-tests. This was followed by a series of OLS regressions limited to dual-earner households. Our primary interest is in the model using commute difference as the dependent variable. We added two models of female and male individual commute distance for the same sample to understand whether the commute gaps found refer to the female and/or male commute. 4. Results and discussions 4.1. To what extent do gender differences in commute distances vary between and within households? – Descriptive analysis Table 5 provides a descriptive summary of male and female respondents, classified by various households without and with children under 10, and the corresponding t-test results. Men across all considered household types commute longer, earn more income and work more extended hours, but spend less time in unpaid activities than women. The gender gap in economic variables mostly favours males, whereas the gender gap in unpaid work favours females. However, the extent of the gender differences varies with context. It should be noted that commute trips are longer in households with small children than in those without. Firstly, the gender gaps in household types with small children are larger than in those without. For instance, the gender commute difference in single-earner partner households with small children is 9.6 km, but only 6.3 km in their counterparts without small 119

120

9. Preference for paid work (hours/day) 10. Monthly household income (€)

Out-of-home: Family care travel Out-of-home: Shopping activity Out-of-home: Shopping travel 7. Mean age, children < 10 8. Mean age

Out-of-home: Household travel Out-of-home: Escort

In-home: Family care

4060(1425)

M: 50.5(7.7) F:47.8(7.4) M: 7.4(1.7) F: 5.4(2.1)

−1.2***

M: 1.3(1.3) F: 2.5(1.4) M:0.1(0.3) F:0.2(0.6) M: 0.3(0.4) F: 0.3(0.5) M: 0.0(0.1) F: 0.0(0.1) M:0.0(0.1) F:0.1(0.2) M: 0.0(0.1) F: 0.0(0.1) M: 0.5(0.5) F: 0.7(0.6) M: 0.2(0.3) F: 0.2(0.3) na

na

2.0***

2.7***

na

0.0***

−0.2***

0.0

−0.1

0.0

0.0***

−0.1

−1.7***

1.8***

0.1***

0.3***

1276***

t-test paired sample 4.9***

Gender gap M-F

M:2.3(1.6) F:4.0(1.9)

1063 M: 16.5(22.2) F: 11.6(13.3) M:2494(1208) F: 1218(8 1 1) M: 13.8(2.8) F: 13.5(2.4) M: 1.1(1.0) F: 1.0(0.9) M: 6.0(2.1) F: 4.2(2.1)

N 1. Commute distance (km) 2. Monthly income (€) 3. Education (years)

4. Car use (hours/ day) 5. Time spent on paid work (hours/day) 6. Total time spent on unpaid work (hours/day) In-home: Household work In-home: Childcare

Dual-earners

Intra-household variables

Household without children under 10 years Partner Households

Table 5 Descriptive summary across various household types.

3492(1595)

7.2(2.1)

52.2(9.4)

M:1.2(1.0) F:3.6(1.8) M:0.2(0.7) F:0.8(0.7) M:0.3(0.4) F: 0.7(1.8) M:0.0(0.1) F: 0.0(0.1) M:0.0(0.1) F: 0.8(1.8) M:0.0(0.1) F:0.0(0.1) M:0.5(0.6) F: 0.8(0.7) M:0.2(0.3) F:0.3(0.3) na

M:2.5(1.6) F:6.1(2.4)

285 17.7 (24.1) 2550 (1403) 13.8 (2.9) 1.1 (0.9) 5.7 (2.3)

Male singleearner

3203(1385)

5.5(2.1)

53.2(7.4)

M:2.1(1.6) F:1.9(1.4) M:0.0(0.3) F:0.1(0.6) M:0.4(0.5) F:0.3(0.4) M:0.0(0.0) F:0.0(0.1) M:0.0(0.0) F:0.0(0.2) M:0.0(0.2) F:0.0(0.1) M:0.9(1.0) F:0.6(0.6) M:0.3(0.4) F:0.2(0.3) na

M:3.9(2.3) F:3.2(2.0)

170 11.4 (12.8) 1295 (9 4 9) 13.2 (2.6) 0.9 (0.8) 4.2 (2.4)

Female singleearner

289*

1.7***

−1.0

na

0.0

−0.1***

0.0

0.0

0.0

0.0

0.1

−0.7***

−0.7***

1.5***

0.2*

0.6*

1255***

t-test indep. sample 6.3**

Gender gap M-F

2185(1322)

4.7(3.8)

51.9(14.7)

na

0.2(0.4)

0.6(0.6)

0.0(0.1)

0.0(0.1)

0.0(0.1)

0.3(0.4)

0.0(0.1)

1.5(1.3)

2.6(1.7)

5.1(4.1)

0.9(1.0)

13.7(2.7)

1927(1073)

624 9.0(16.7)

Male

Single households

1811(1018)

3.8(3.4)

53.8(13.4)

na

0.3(0.3)

0.7(0.6)

0.0(0.1)

0.0(0.1)

0.0(0.1)

0.4(0.5)

0.1(0.3)

2.3(1.4)

3.8(1.9)

4.0(3.7)

0.7(0.7)

13.3(2.6)

1517(8 7 6)

1216 7.2(12.5)

Female

(continued on next page)

374***

0.9***

−1.9*

na

−0.1

−0.1***

0.0

0.0

0.0

−0.1***

−0.1

−0.8***

−1.2***

1.1***

0.2**

0.4**

410***

t-test indep. sample 1.8

Gender gap M-F

B. Chidambaram and J. Scheiner

Transportation Research Part A 134 (2020) 113–129

121

3895(1381)

M: 41.7(5.7) F: 38.6(5.3) M: 7.5(1.6) F: 4.8(1.9) na

2.7***

3.1***

na

−0.1***

−0.2***

0.0

−0.3***

0.0

−0.2***

3353(1277)

7.6(1.4)

41.3(5.8)

M:1.0(1.1) F:3.2(1.7) M:0.8(0.8) F:2.1(1.5) M:0.2(0.3) F:0.4(0.5) M:0.0(0.1) F:0.0(0.1) M:0.1(0.2) F:0.5(0.5) M:0.0(0.0) F:0.0(0.1) M:0.3(0.4) F: 0.7(0.6) M:0.1(0.2) F:0.2 (0.3) 2.0(0.9)

M:2.6(1.7) F:7.1(2.7)

3070(1274)

6.0(1.7)

40.0(6.5)

M:1.6(1.7) F:1.2(1.1) M:1.1(1.3) F:1.1(1.4) M:0.2(0.4) F:0.1(0.3) M:0.0(0.1) F:0.0(0.0) M:0.3(0.5) F:0.1(0.3) M:0.0(0.2) F:0.0(0.0) M:0.6(0.7) F:0.3(0.5) M:0.2(0.3) F:0.1(0.3) 2.3(0.8)

M:3.9(3.4) F:3.0(2.6)

5.0(2.5)

0.7(0.8)

14.6(2.9)

1746(1132)

43 11.9(11.7)

Female singleearner

283

1.6***

1.3

na

0.0

0.0

0.0

0.0

0.0

0.1

−0.3*

−0.2

−0.4

1.4***

0.3

−0.4

979***

t-test indep. sample 9.6*

Gender gap M-F

Note: M- Male; F- Female; na- not applicable; all values except N are variable means (in brackets: standard deviations) in bold are significant (2-tailed): *** -p < 0.001, **- p < 0.01, and *- p < 0.05; na – not applicable; Source: own calculations

9. Preference for paid work (hours/day) 10. Monthly household income (€)

Out-of-home: Family care travel Out-of-home: Shopping activity Out-of-home: Shopping travel 7. Mean age, children < 10 8. Mean age

Out-of-home: Household travel Out-of-home: Escort

In-home: Family care

−1.1***

M: 1.2(1.0) F: 2.3(1.3) M: 0.8(0.8) F: 1.5(1.1) M: 0.3(0.4) F: 0.5(0.6) M: 0.0(0.0) F: 0.0(0.1) M: 0.1(0.2) F: 0.4(0.4) M: 0.0(0.1) F: 0.0(0.0) M: 0.4(0.5) F: 0.6(0.6) M: 0.1(0.2) F: 0.2(0.2) 2.1(0.8) −0.7***

−2.6***

6.4(1.9)

2.5***

14.2(3.0)

0.0 1.0(0.8)

2725(1184)

1420***

0.0

181 21.5(27.3)

Male singleearner

t-test paired sample 5.8***

Gender gap M-F

M:2.9(1.7) F: 5.5(2.0)

534 M: 19.4(25.3) F: 13.6(17.7) M: 2570(1190) F: 1150(7 8 4) M: 14.3(2.9) F: 14.3(2.6) M: 1.1(0.9) F: 1.1(0.8) M: 6.1 (2.1) F: 3.6(1.9)

N 1. Commute distance (km) 2. Monthly income (€) 3. Education (years)

4. Car use (hours/ day) 5. Time spent on paid work (hours/day) 6. Total time spent on unpaid work (hours/day) In-home: Household work In-home: Childcare

Dual-earners

Household with children under 10 years Partner Households

Intra-household variables

Table 5 (continued)

3085(1465)

6.7(2.9)

38.6(7.3)

3.8(2.7)

0.2(0.3)

0.4(0.5)

0.0(0.0)

0.1(0.2)

0.0(0.0)

0.3(0.4)

1.2(1.0)

1.0(1.0)

3.2(2.1)

7.6(3.0)

1.1(1.0)

13.7(2.7)

2005(1046)

80 14.9(19.5)

Male

1944(1015)

4.1(3.0)

38.5(6.8)

5.8(2.6)

0.2(0.3)

0.6(0.5)

0.0(0.1)

0.4(0.4)

0.0(0.1)

0.4(0.4)

1.7(1.3)

2.2(1.5)

5.6(2.3)

3.8(3.0)

0.9(0.8)

14.0(3.0)

1426(9 7 3)

155 9.4(14.8)

Female

Single/ lone-parent households

1141***

2.6***

0.1

na

0.0

−0.2**

0.0

−0.3***

0.0

−0.1*

−0.5**

−1.1***

−2.4***

3.8***

0.2

−0.3

579***

t-test indep. sample 5.5*

Gender gap M-F

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B. Chidambaram and J. Scheiner

children. Secondly, there is a large gender gap in personal income in dual-earner couples without children (€1276 gap) and those with children (€1419 gap). In households without small children, there are also significant gender gaps in education and car use, favouring male respondents. However, there are no significant gender differences in household types with small children. In all household types, male respondents work longer hours for pay than female respondents. In particular, a large and significant gender gap is observed between partners from dual-earner households (with and without children) and between male and female lone-parents. These findings corroborate the idea of unequal gendered status positions in couples. Thirdly, females spend more time than males on all unpaid activities (significant for most household types). The critical determinants of unpaid activities for households without small children are household work and family care in-home and shopping and travel in out-of-home activities. Fourthly, the presence of small children markedly increases total unpaid activities for both males and females, except for single earning women. Finally, the preference for paid working hours indicates that in most household types, both males and females would prefer to work an hour more than their actual working hours. There is no sign of any wish for a change in inequality from paid work preferences. In addition to the descriptive analysis, Table 6 shows the percentage share of intra-household allocations in dual-earner couples used in regression analysis. About 50% of total dual-earner couples are both salaried, which may indicate an equal employment status within couples. In terms of car access, female (11%) and male (12%) dominance in car usage is almost equal in low-car households, while men dominate in multi-car households (27% versus 16%). Overall, these findings confirm the following concerning dual-earner couples: (i) female partners have a short commute, low income and few working hours, and bear a large share of unpaid work, whereas the opposite is true for male partners; (ii) the presence of children further increases the commute distances and the overall amount of unpaid work for both male and female partners; (iii) moreover, the presence of children tends to increase the gender gap in commuting, in time spent on paid and unpaid work, in personal income and in preference for paid working hours. The burden of childcare-related activities additionally falls on women, leading to decreased time spent on paid work and earning less. 4.2. How do intra-household allocations affect relative commuting within dual-earner couples – Regression analysis Table 7 shows the regression analysis for three dependent variables: (1) difference between male and female partners’ commute distances (i.e. the gender gap). To better understand the differences, we additionally present two models for male (2) and female (3) commute distances separately. It is important to note that the regression model has a low R2 value (0.11), which is, however, typical for individual- or household-level travel behaviour studies. It should also be noted that the constant (8.697) implies that the commute gap is almost 8.7 km, all else equal. This is even more than the descriptive results in Table 5 suggest. 4.2.1. Socio-economic characteristics The gender commute gap is positively associated with the gender gap in income – the wider the gender income gap, the larger the commute gap. This finding is consistent with previous studies (Black et al., 2014; Preston and McLafferty, 2016; Sandow and Westin, 2010). The same is true for the education gap, again consistent with previous studies (Cassel et al., 2013; Sandow & Westin, 2010). More income on the household level is associated with longer female commutes, thus reducing the gender gap in commuting. This is probably due to more career-oriented women commuting longer and contributing more to household income. Concerning working status, the commute gap decreases when the female partner's work status is either equal to or higher than that of their male partner. For instance, in households where both partners are self-employed, the gender gap significantly decreases from the reference category (both partners are salaried). Also in households where males are self-employed and females are either salaried or labourers, males' commutes are shorter than those of females, which significantly decreases the commute gap. In contrast, in households where males are labourers and females are self-employed, females' commutes are shorter, which increases the commute gap. These findings commonly indicate that self-employed partners travel shorter distances than their salaried partners, as pointed out by Giuliano (1998), Lee and McDonald (2003) and Stutzer and Frey (2008). Also, it is argued that self-employed employees tend to locate their jobs closer to home or work from home in contrast to other employees (van Ommeren and van der Straaten, 2008). 4.2.2. Car access As expected, there is some association between relative car availability and relative commuting. We use a side-spread case as a reference: the partners share a car, and both of them drive equally (between 40 and 60%). Notably, in both low-car and multi-car households, female dominance in car use is associated with increased female commute distances and decreased male commute distances, which significantly decreases the gender gap. Other categories of car availability have no significant association with commute distance difference. However, multi-car households with equal car use for both partners are associated with longer commutes among them, with no effect on the gender gap. This finding suggests a strong link between household car ownership and labour market activity spaces. However, the findings concerning car access should not be interpreted in terms of causal effects, but associations. It is very likely that long commutes of either partner tend to give this partner more car access rather than the other way round. 122

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Table 6 Percentage share of intra-household allocation within dual-earner couples. Intra-household variables within dual-earner couples Economic

1. Income level Male partner earns more than female partner Both earn equally Female partner earns more than male partner 2. Education (years)1 Both equally educated Female partner is more educated than male partner Male partner is more educated than female partner 3. Relative work status Both MF salaried Both MF labourers Both MF self-employed M salaried, F labourer M salaried, F self-employed M labourer, F salaried M labourer, F self-employed M self-employed, F salaried M self-employed, F labourers

Car access

4. Relative car use Male 60–100%, female < 40% driving (M > F); Multi-car household Both equal (40–60%) driving (M = F); Multi-car household Female 60–100%, male < 40% driving (F > M); Multi-car household Male 60–100%, female < 40% driving (M > F); Low-car household Both equal (40–60%) driving (M = F); Low-car household Female 60–100%, male < 40% driving (F > M); Low-car household Zero car household

Gender roles

5. Time spent on paid work1 Strongly traditional; male 80–100% and female < 20% Traditional; male 60–80% and female 20–40% Egalitarian; male 40–60% and female 40–60% Reverse; male 20–40% and female 60–80% Strongly reverse; male < 20% and female 80–100% 6. Time spent on unpaid work1 Strongly traditional; female 80–100% and male < 20% Traditional; female 60–80% and male 20–40% Egalitarian; female 40–60% and male 40–60% Reverse; female 20–40% and male 60–80% Strongly reverse; female < 20% and male 80–100% 7. Children under 10 years No children One child Two or more children

Preferences

Environment

%

1

8. Preference for unpaid work – Male Preference for traditional pattern Preference for egalitarian pattern Preference for reverse pattern 9. Preference for unpaid work – Female Preference for traditional pattern Preference for egalitarian pattern Preference for reverse pattern 11. Type of residential location Large cities Semi urban Rural Semi-rural

79.8 6.8 13.4 33.1 33.2 31.1 49.0 7.2 4.6 2.6 4.3 14.6 1.1 15.7 0.9 27.4 10.7 15.8 11.9 10.7 10.5 2.4 11.7 41.0 39.1 6.0 2.2 17.7 43.5 31.4 6.8 0.6 69.7 17.7 12.6 26.5 50.9 22.6 77.5 19.2 3.3 23.8 42.1 19.2 15.0

Note: M- Male; F- Female. Source: own calculations. 1 These variables have been used in their metric form for the regression analysis in Table 7.

4.2.3. Gender roles in workload allocation An increasing gap in time spent on paid work significantly decreases the female commute and hence increases the commute gap. For unpaid work it is the other way round. The gap is negative here (i.e. women spend more time than their partners on unpaid work). The negative coefficient we find suggests that when male partners spend more time on household work, the commute gap decreases. This means that equality in commuting depends not only on paid work, but also on household work allocation, and men 123

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Table 7 Regression analysis for difference in commute distance within dual-earner couples. Variable

Commute distance difference (M-F)

Male commute distance

Female commute distance

Coef. Constant Personal income level difference (M-F, €1,000/month) Education level difference (M-F, years) Work status: Both salaried(ref.) both MF labourers both MF self-employed M salaried & F labourer M salaried & F self-employed M labourers & F salaried M labourers & F self-employed M self-employed & F salaried M self-employed & F labourer Car access: M = F + Low-car household(ref.) M > F + Low-car household F > M + Low-car household M > F + Multi-car household M = F + Multi-car household F > M + Multi-car household No cars Difference in time spent in employment (M-F, h/day) Difference in time spent in household (M-F, h/day) Number of children below 10 years: no children (ref.) One child Two or more children Male preference for unpaid work: Egalitarian pattern (ref.) Traditional Reverse Female preference for unpaid work: Egalitarian pattern (ref.) Traditional Reverse Household income (€1000/month) Type of residential location: Urban/megacity (ref.) Semi-urban Rural Semi-rural Adj. R2(%) N

B 8.697** 1.134* 0.489*

B 14.585*** 0.829 0.409

B 5.888** −0.305 −0.080

−2.456 −8.658** −2.093 5.016 −5.093* 10.730 −14.352*** −14.414*

−6.130** −18.177*** −6.394 −5.067 −5.025** 1.521 −14.878*** −17.989**

−3.674* −9.519*** −4.301 −10.083*** 0.068 −9.209* −0.527 −3.575

−1.241 −6.575* 4.588 0.782 −10.937*** −4.021 1.024*** −1.073*

−0.652 −2.937 5.084* 4.150* −4.507* 3.701 0.351 −0.577

0.589 3.638* 0.496 3.368* 6.430*** 7.722** −0.672*** 0.496

−0.380 −3.348

1.054 0.154

1.434 3.501**

−3.305* 1.016

−3.553* 1.303

−0.248 0.286

2.500 4.685 −1.207*

1.632 1.262 −0.013

−0.868 −3.423 1.195***

0.938 −1.613 −0.484 11.5 1425

3.723* 2.722 3.067 11.1 1425

2.785** 4.335*** 3.552** 11.8 1425

Note: Values in bold are significant: *** -p < 0.001, ** - p < 0.01, and * - p < 0.05. Source: own calculations.

may contribute to their wives' commuting activity spaces by taking household work responsibility. Having children below ten years of age does not significantly affect the commute distance difference. Notably, having more than one child significantly increases the commute distance of female partners. This may sound counter-intuitive but is confirmed by descriptive analysis.3 It could be attributed to the additional stops they make on the way to/from work to pick up and drop off children at childcare or school (McGuckin and Nakamoto, 2005; Wang, 2015). It is also supported by recent findings taken from panel data in Germany, although these refer to driving rather than distances covered. They show that women living in low-car households increasingly drive after the birth of a second or higher-order child, but not after the birth of a first child (Scheiner, 2020). 4.2.4. Gender preferences in work-sharing Male preferences for the traditional pattern negatively affect the commute gap (p < 0.05) compared to those with a preference for the egalitarian pattern. This finding may suggest reverse causality to be at work: men with a long, possibly exhausting commute and little time for their family and partner may have a preference for a less traditional work-sharing pattern. Otherwise, our analysis does not reveal any significant associations. This also includes the preference measurement for more or fewer paid work hours (which we excluded from the analysis altogether after some initial attempts). Taken together, this favours the idea that preferences have little effect on the gender commute gap, although a note of caution may be warranted as our measurement is less than optimal.

3 The mean commute distances for dual-earners without small children are M:16.5 and F:11.6 km; for dual earners with one child below 10 years M:18.0 km, F:14.0 km; and for dual earners with two or more children below 10 years M:18.0 km, 15.1 km respectively.

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4.2.5. Residential location Both male and female partners from low-density regions commute longer than those living in larger cities, although not all location categories are significant. There is no significant effect on the gender commute gap, i.e. there is no indication of greater equality in urban areas. 4.3. Discussion Our descriptive analysis confirms that significant gender differences exist within dual-earner couples in terms of commute distance and other intra-household allocations. Also, the regression analysis shows notable associations between the intra-household allocation of resources and the commute gap within couples, in line with previous research, and despite research on trends over time that has suggested some gender convergence both in work-sharing and commuting. Our findings show that on average female partners have lower commute distances, monthly incomes and working hours than their counterparts. As expected from the economic power hypothesis, higher economic and social status is associated with a longer commute within dual-earner households. This evidence is strong as various relevant factors are statistically significant: personal income, education level, employment status and time spent on paid work. All these factors contribute to men's longer commutes (Hypotheses H1, H3). Conversely, the more time male partners (and the less time female partners) spend on unpaid work, the more the commute gap decreases. Hence, the commute gap is strongly subject to female household and family obligations (H4), and, remarkably, the effect magnitude is on the same level as that of paid work. Dual-earners face restrictions on commuting longer distances, as they need to balance work and family. As de Meester and van Ham (2009) point out, one of the partners may commute farther while the other – typically the woman – works closer to home. This is the case for the majority of couple households in Germany. In our sample, the traditional arrangement of unpaid work still characterises about 60% of dual-earner households (Table 6). In single-earner couples – which are dominated by male-breadwinner-female-housewife combinations – the inequalities are even stronger. Partners with more car access are likely to commute longer distances than their counterparts. A high level of car driving among female partners significantly reduces the commute gap in both one-car and multi-car couples. This finding is in line with other research (Best and Lanzendorf, 2005; Konrad, 2016; Scheiner and Holz-Rau, 2012b) and suggests that women's car availability is a key resource in gender equality (H2), although the gap is not generally smaller in multi-car households (contrary to H2). The presence of two or more children in a dual-earner couple reduces the commute gap. As mentioned earlier, female partners tend to make household maintenance and escort trips on their commute, which may contribute to longer commutes. Also, the descriptive analysis shows that females with small children commute farther than females without children. There may also be selfselection at work: those mothers with young children who work tend to be those who are eager to pursue a career, which in turn is associated with longer commutes. To our surprise, male traditional role preferences reduce the commute gap (countering H5), which may suggest reverse causality to be at work. Most studies (Leslie, 2017; Schwartz, 2014) confirm that education, employment and earning status are prime factors in men’s preference for traditional roles and women’s preference for reverse roles. However, our study only provides limited insight into the association between preferences and commuting, as the variable itself is not a direct representation of preferences. The lack of effect of the direct measurement for less (or more) paid work favours the idea that preferences do not play an important role. Household income significantly reduces the gender commute gap, suggesting more equality in higher-income households. In line with Plaut (2006) and Surprenant-Legault et al. (2013), commutes within dual-earners couples tend to complement each other, as both partners similarly commute longer. 5. Conclusions This study underscores the relationship between the gender commute gap and intra-household arrangements within heterosexual dual-earner couples in Germany. While our study is rooted in the transport literature on the effects of gender on travel – rather than being concerned with the construction of gender by means of mobility – it establishes an understanding of how various intrahousehold allocations contribute to gender inequality in commuting distance and, thus, individual activity spaces in the labour market. To reiterate for clarity, these allocations include (1) both partners' contributions to household income and other social status measures such as education level and work status, (2) contributions made by both partners to unpaid household and family work, (3) the allocation of car use to both partners, (4) household responsibilities beyond the mere time devoted to household tasks (c.f. number of children) and, possibly, social norms that are at play, as reflected in the finding that total household income reduces the gender commute gap over and above the two partners' personal incomes. This is probably due to the higher household incomes among those households where female partners strongly contribute to income, thus suggesting an equal intra-couple economic power distribution per se. This economic reasoning may be supported by findings that suggest more modernised, 'equity in power' gender norms among higher-income groups (Evertsson et al., 2009; Bertrand et al., 2015). On the other hand, our findings suggest (5) limited relevance of gender preferences. Although there is some significant effect, the direction of causality is not clear and the variable that should be of primary importance if preferences played an important role – preference for paid work hours, reflecting economic dominance or the pursuit of a career – turns out insignificant. While our quantitative approach is limited in terms of in-depth understanding of the partners' own subjective perspectives on these allocations, it is strong in providing quantified empirical evidence of mechanisms being at work such as resource allocations, socioeconomic positions and household responsibilities. There are three specific points to mark the unique contribution of our study 125

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to transport research. Firstly, most transport research on intra-household allocations focuses on out-of-home activities. However, as pointed out by McGinnity and Russell (2008:72), time spent on in-home activities is very significant in analysis of the gender gap between partners. We included the gender gap in in-home activities over and above out-of-home activities. Secondly, we tested the effect of personal income that is arguably the key resource in negotiations of intra-couple economic power allocations; most transport research ignores this due to a lack of data on individual income in travel surveys (see Boarnet and Hsu, 2015, for an exception). Thirdly, we tested the effects of preferences concerning work-sharing over and above the realised division of work, thus providing evidence on the contested issue of the role of preferences in gender inequalities. Concerning the extent of gender differences, the descriptive analysis shows that the gender gap in partner households is more substantial than between single-person households. This is especially notable for dual-earners with small children. Taken together, these two findings suggest that unequal gender roles are most prevalent within partnerships with children that constrain the working and commuting arrangements of women. On the other hand, working women with small children tend to commute relatively long distances. Some of the intra-household allocations within dual-earner couples have significant associations with the commute gap. From the findings, we conclude the following. First, reducing male dominance in employment, income and car access clearly has the potential to reduce the gender commute gap. Second, female partners are more likely to face role and time constraints concerning commuting and intra-household arrangements. For instance, from the descriptive analysis we take that men tend to dominate in car use. In households where women dominate car use the commute gap is smaller. Also, the presence of children decreases the time spent on household activities but increases childcare and household travel activities for both partners. So female partners engaged in childcare or household trips along with commuting could reduce the time they spend on household work. This suggests that long commuting may indeed have some benefits for women, as suggested by Blumen (2000): better jobs, private time and unique geographical experience. She argues that any additional time that women save in commuting is most likely to be spent on unpaid activities. Third, the relevance of gender role expectations is confirmed by the association between the time spent on unpaid activities and the gender commute gap. More specifically, when male partners spend more time on household work, the commute gap decreases (i.e. the female partner may commute longer). Fourth, despite being only marginally significant, the role preferences of male partners may be associated with the commute gap. In any case, we feel that the role of preferences in shaping gender arrangements in commuting (and other domains) needs further investigation. Particular emphasis should be placed upon the potential endogeneity of preferences to power relations and the unequal distribution of resources, and potential biases in preference measurement caused by affirmative responses. Overall, our evidence provides some hint to intra-household allocation between dual-earners in Germany. The gender gap in commute distances we found reflects the pattern of the “modernised breadwinner model”, in line with Barlen and Bogedan (2012), and fits with the aforementioned transition in Germany from a conservative gender culture to a more modern model, i.e. a process of change, even though our analysis is cross-sectional in nature. A word of caution is that this trend in gender equity may increase the complexity in time-use patterns of both male and female partners, as suggested by Scheiner (2014). Further research on complexity may shed light on the amount and kind of time use, travel and activity patterns. Male partners commute for longer and provide more economic support to the family with their full-time employment, whereas female partners commute shorter distances to offer both financial and family support by accepting part-time jobs. Commuting by car facilitates this integration. The processes of change give rise to negotiation about work-sharing within couples, and such decision-making processes in couples also deserve more research. Our findings may provide some input for policy. In the past decade, German gender policy culture has been characterised by constant negotiation between staunchly conservative elements, favouring traditional work-sharing, and more left-wing attempts to achieve more gender equality. Although gender policies like employment policies (employment security and social security), family policies (childcare services, leave facilities, flexible working arrangements) are already in place in Germany, previous studies have shown that reconciling women’s working and family lives and the gender pay gap have not been adequately addressed (Botsch, 2015; Rubery et al., 2007). Hence more practical and realistic approaches instead of theoretical and idealistic notions are required to facilitate dual-earners to initiate changes in employment behaviour (from part time to full time or vice versa), while at the same time helping male breadwinner (single-earner) couples who aim to switch to dual-earner arrangements, supporting women's economic independence. From the mobility perspective, more innovative policies should address women’s complex mobility needs: child chauffeuring, commuting and household-related trips. Our evidence shows that car availability helps women overcome spatial limitations in job access, but at the same time Germany and other countries strive for more sustainable, non-car-based transport; this also poses challenges for the development of public transport that better addresses women's complex trip chaining patterns (Scheiner, 2014). Many questions concerning the effect of intra-household allocations on relative commuting are left unanswered. For instance, females tend to use other transport modes than the car, e.g. public transport, but we were unable to study how access to public transport affects relative commuting. Also, women's lower incomes imply higher transport cost burden. Also, we have generated individual proxy variables for gender preferences. This indirect measurement limits our understanding of how preferences relate to relative commuting. There are more in-depth open questions in this line of research, such as whether and how two partners' preferences and aspirations align (or not) in partnerships (Kalmijn, 2005), thus continuously constructing and changing 'male' and 'female' thinking that may contribute to future work-sharing and commuting arrangements in partnerships. We leave these questions and topics for future research. 126

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CRediT authorship contribution statement Bhuvanachithra Chidambaram: Conceptualization, Methodology, Software, Validation, Formal analysis, Writing - original draft. Joachim Scheiner: Writing - review & editing, Supervision, Resources. Acknowledgements This research was funded by the German Research Foundation (DFG- SCHE 1692/5-1) as part of the project “Gender, Pendeln, Aktivitätsmuster” (Gender, Commuting, Activity patterns, 2017–2020). The authors would like to thank three anonymous reviewers for their meticulous, thoughtful, and constructive comments and suggestions on the original manuscript. References Barlen, V., Bogedan, C., 2012. Mind the gap! Arbeitszeiten von Frauen und Männern zwischen Wunsch und Wirklichkeit. Im Fokus spw-1, 25–29. Beck-Gernsheim, E., 2012. From rights and obligations to contested rights and obligations: Individualization, globalization, and family law. Theor. Inq. Law 13, 1–14. https://doi.org/10.1515/1565-3404.1283. Beck, M.J., Hess, S., 2016. 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