Intrahousehold Specialization in Housework

- A Cross-Country Application to Time Diary and Questionnaire Data

By

Jens Bonke+, Mette Deding+ Mette Lausten+, and Leslie Stratton*

+The Danish National Institute of Social Research, DK

*Virginia Commonwealth University, US

Draft version: January 2006 Please do not quote

Abstract. We test Stratton’s model of intrahousehold specialization by first replicating her results using similar US data, then performing comparable analysis using both questionnaire- and time diary-based data on a similar set of housework activities from the 2001 Danish Time Use Survey. This analysis provides evidence of both cross-country and cross-data type differences in the measurement of and the factors related to intrahousehold specialization. The two data sets are the 1992-94 wave of the US based National Survey of Families and Households (NSFH), and the 2001 Danish Time Use Survey (DTUS). We choose here to focus on specialization by task rather than by time performed in order to more closely mimic the type of specialization captured by questionnaire data. One key difference observed between the Danish and US results is in the impact of children on intrahousehold specialization. These cross-country differences are likely attributable to the substantial cross-country differences in the availability of affordable, high quality day care. The Danish social welfare system provides subsidized childcare services that are only available at high cost in the private sector in the US. Thus, the impact of children on households is likely to be greater in the US than in Denmark and so affects intrahousehold specialization more in the US than in Denmark.

1

1. Introduction

One of the key advantages to multi-person households is the ability to gain from the

division of labor and specialization. Even within the set of home production tasks like food

preparation, laundry, and cleaning, there is significant evidence of specialization - with

women contributing substantial time to some housework tasks and men to others. Most of

this evidence, however, is based off time use data from only one household respondent. To

truly examine intrahousehold specialization within couple households, it is necessary to have

data from both partners and to measure specialization in a manner that is gender neutral. We

are able to accomplish this using data from both the US and Denmark that allow us to also

look for both cross-country and cross-data type differences in the measurement of and the

factors related to intra-household specialization.

We begin by replicating previous results regarding intrahousehold specialization and

the relation demographic and household characteristics have to such specialization using

questionnaire data from couples in the US National Survey of Families and Households. We

then perform comparable analysis using questionnaire data from the 2001 Danish Time Use

Survey. A comparison of these US and Danish data provides credible evidence of cross-

country differences in intrahousehold specialization. These Danish data also provide 48 hour

diary-based information on couple housework time. Diary-based time use measures are

generally considered more reliable than questionnaire-based measures. Constructing another

measure of intrahousehold specialization using the time diary data yields substantially

different results. After discussing the extant literature, our data, our gender-neutral measure

of specialization, and our results, we offer several explanations for the cross-country and

cross-data type differences we observe.

2. Literature review

2.1. On measurement

To measure the degree of intrahousehold specialization in housework requires

measurement of housework time. Yet the measurement of housework time is fraught with

difficulties.1 The activities that constitute housework are often not clearly delineated. Some

surveys leave it up to the respondents’ discretion. For example, the Panel Study of Income

Dynamics asks respondents “About how much time do (you or your spouse) spend on

1 Shelton and John (1996) provide a review of several of the following measurement issues.

2

housework in a given week? I mean time spent cooking, cleaning, and doing other work

around the house.” Whether this includes time on auto repair, paying bills, or grocery

shopping is not clear and respondents may differ on their interpretation. Other surveys try to

list specific activities and in the process may fail to capture all housework activities. Still

others handpick a subset of housework activities (for example, Twiggs, McQuillan, and

Ferree 1999 have no data on home repairs or outdoor maintenance and explicitly exclude bill

paying; Gupta 1999 uses only ‘female type’ activities that must be performed on a regular

basis, hence excluding home repair but also such routine tasks as lawn care). While we use

data from different sources, the housework tasks we examine are relatively clearly defined.

The method by which housework time is measured also differs across studies. Data

can come from time diary studies or questionnaires. Time diary studies typically ask

individuals to record information on all their activities during a 24 hour period, but may also

include separate weekday and weekend diaries, information on secondary activities (such as

doing laundry while also performing child care), or even tertiary activities, see Eurostat

(2000). Time use data may alternatively be collected by asking respondents to report what

they are doing several times a day (or week) at the moment a randomly timed beeper goes off.

Questionnaire data may take the form of queries about how much time is spent on housework

in the average week or on several more narrowly defined housework activities (like meal

preparation and laundry). Alternatively, in multi-person households, respondents may be

asked to identify who performs a particular activity (husband, wife, or both) without

identifying the amount of time involved.

Each data collection method is subject to its own peculiar biases. Comparisons of

questionnaire and time-diary data suggest that questionnaire data overstate all time spent

(Robinson 1985, Shelton and John 1996, Lee and Waite 2005), or overstate time spent on

frequent but understate time spent on infrequent activities (Bonke 2005). Certainly estimates

of housework time in particular are greater when derived from questionnaire versus time diary

sources. One reason for this differential that is peculiar to housework is that housework tasks

are often performed as a secondary activity (Robinson 1985, Kitteroed 2001, Floro and Miles

2003, Lee and Waite 2005).2 Questionnaire measures of time use appear to incorporate this

secondary time; primary time diary records do not.3 How these errors may affect

measurement of intrahousehold specialization is uncertain. If all time is overstated equally, 2 This is not the only reason for the differential as Robinson (1985) reports that time spent sleeping is also higher from questionnaire data than from time diary data even when sleeping is not a secondary activity. 3 There is not yet a consensus regarding how to quantify secondary time use from time diary data (Ironmonger 2003).

3

then there may be no bias, but substantial gender differences in reported housework time

could also mask gender biases in reporting. There exists some evidence of gender bias in

questionnaire-based measures of time use (Davis and Greenstein 2004, Batalova and Cohen

2002, Winkler 2002, Lee and Waite 2005) and some evidence that women provide more

accurate estimates than men (add cites – I have some, just not with me at the moment).

Time diary methods by contrast are believed to provide an accurate accounting of time

spent, but only capture those activities performed during the period for which the diary is

collected. As discussed by Juster (1985), 24 hour time diary data provide an accurate estimate

of population distributions of time use, but good data on individual time use would require

many more diaries per individual in order to capture activities that occur only infrequently.

While meal preparation and cleaning dishes are likely daily activities, laundry and shopping

are not and so are likely to be missed by single day diaries.4 Data such as that available from

the Netherlands that collect diary information on a weekly basis (Van den Broek and

Breedveld 2004) are the exception rather than the rule. The direction of bias introduced by

the time diary method depends on a number of factors: what tasks are not captured, who

performs these tasks, and even the manner in which time is allocated to those tasks that are

not observed. Diary data from a single day are certainly more likely to indicate specialization

than questionnaire data on usual weekly activities because the short time frame indicated by

the diary data captures specialization by day as well as by task. Thus, while each individual

may spend the same amount of time doing dishes, they may specialize by doing dishes on

alternate days. Time diary data are more likely to reflect such specialization.

Studies such as this examining intrahousehold specialization of household labor within

couple households have some additional data requirements. First, intrahousehold

specialization measures require information on both partners within a couple. Such data are

relatively rare. Second, in the case of questionnaire data some researchers have reported

evidence of gender bias in the reporting of time use. Winkler (2002), for example, finds that

men and women agree on the time women spend on housework, but disagree on the time

spent by men, with men reporting more time than do their partners. Lee and Waite (2005)

find similar results with different data. Third, both questionnaire data and time diary data

may be differentially biased by respondent. Different individuals may perceive time or the

scope of activities included in some time use category differently or may report primary and

secondary time use in a different manner. By using questionnaire data collected from a single

4 Bryant et al (2002) also discuss biases due to the classification of activities and to the nature of the data collection (telephone versus in-person interviews).

4

respondent we should minimize respondent-specific bias in using the questionnaire data. By

examining data with and without secondary measures of time use, we can gauge the degree of

bias using time diary data.

2.2. On specialization

Those studies that do focus on intrahousehold housework time often focus on the

division of household work by gender. There exists a substantial sociological literature in this

area (Shelton and John 1996 provide a review). Some theories developed to explain the

division of household labor focus on relative resources, time availability, and ideology.

Relative resource theory says that individuals with the most resources negotiate their way out

of housework. This is akin to bargaining theory in economics which suggests that those

household members with the most power will do less housework. Power is often measured in

terms of earnings, though Pollak (2005) provides a strong argument that hourly earnings

potential is a better measure of each individual’s threat point and so better captures their

power. Alternatively, the time availability approach posits a negative relation between the

time spent on employment and the time spent on housework driven by the fixed time

constraints all people face. This approach typically assumes that time is allocated to

housework only after employment decisions are made and so fails to recognize that decisions

about time use may be jointly determined. Ideological explanations for the division of

household labor emphasize the importance of individual beliefs regarding the role of men and

women in couple households.

All of these theories imply that housework is a necessary but unpleasant task. This is

not necessarily the case. Some individuals enjoy cooking or sewing or auto repair as a hobby.

Other theorists have proposed that housework is a means of ‘constructing’ or ‘doing’ gender

and that women in particular derive pleasure out of being able to provide household services

within their household (see Bittman et al 2003 for empirical evidence).

A discussion of intrahousehold specialization does not, however, necessarily revolve

around the division of labor as measured by one partner’s share of housework. The economic

notion of specialization suggests that when individuals join together in a group, tasks can be

allocated in such a way as to increase utility for all parties. If housework were a single

activity, then the appropriate measure of specialization would be the share of housework

contributed by a given individual.5 But housework comprises a heterogeneous set of tasks

5 Economics emphasizes the importance of comparative advantage in determining who should specialize in what activity. Unfortunately, while hourly earnings would provide a measure of productivity in the market sector, we

5

which require different skills and so may be more ably performed by different persons.

Aggregating across tasks to construct a single share measure understates the degree of

intrahousehold specialization if different individuals perform different household tasks. A

few studies use shares for disaggregated data (Twiggs, McQuillan, Ferree 1999) but face the

problem that these decisions must be jointly determined. Still others construct a measure that

tries to account for the gender typing of tasks as well as heterogeneity across households in

the allocation of activities (Blair and Lichter 1991; Stratton 2005). We take the latter

approach, constructing different measures of specialization using different types of time use

data to see how sensitive the measures of intrahousehold specialization are to the use of

different time use data.

3. Data

Two data sets with three different types of housework measures are used in this

analysis. The first is the 1992-94 wave of the US based National Survey of Families and

Households (NSFH). These data contain questionnaire-based responses regarding usual time

spent on nine different housework tasks by both partners in a household during an average

week. The second is the 2001 Danish Time Use Survey (DTUS). This data set includes both

simple ‘who done it’ measures of housework (Self, Partner, or Both) and more detailed time

diary data.

The 1992-94 NSFH survey consists of interviews from 10,005 households first

interviewed in 1987-88. We focus on data from the second wave because there were

significant problems with the reported housework measures from the first wave.6 The

analysis was necessarily restricted to couple households for intrahousehold analysis (6270

households). We also eliminated couples in which either partner was enrolled in school full-

time, enlisted in the military, or over the age of 60. School, military service, and retirement

are all major time commitments. See Szinovacz (2000) for evidence that retirement causes a

reallocation of time. These restrictions reduce the sample size to 4863.7 All estimates

have no measure of home sector productivity. Thus, analysis must focus on measured inputs to home production - time spent. 6 Correspondence with NSFH staff suggests that many respondents may have left blanks rather than filled in zeros at the time of the first wave interview to indicate no time spent on an activity. Interviewers were instructed to check for this problem during the second wave. Most researchers using the first wave data (Hersch and Stratton 2000, South and Spitze 1994) assume at least some of these values are zero. By using the second wave data, we reduce the possible error-in-variables bias introduced by such assumptions. 7 Also excluded were 34 couples missing age, education, household composition, or home ownership information.

6

presented below are weighted to adjust for the oversampling of recently married and

cohabiting households, but the results from unweighted analysis are substantially similar.

The approximate number of hours spent per week on various housework tasks is

reported separately by each partner in the NSFH for both themselves and their spouse/partner.

The nine different housework activities for which time use is reported are: meal preparation

(“meal preparation”); washing dishes and cleaning up after meals (“dishes”); house cleaning

(“cleaning”); washing, ironing and mending (“laundry”); shopping for groceries and other

household goods (“shopping”); outdoor and other household maintenance tasks (“outdoor

maintenance”); auto maintenance and repair (“auto repair”); paying bills and keeping other

financial records (“paying bills”); and driving other household members to work, school, or

other activities (“driving others”). As the Danish questionnaire data do not include

information on auto repair or paying bills, information on these activities is excluded from the

housework specialization measure constructed here. However, we do require either the

primary respondent or the partner to provide complete and reasonable reports on each of the

remaining seven housework activities for both partners.8 By using one respondent’s report for

both partners, we avoid calculation of an intrahousehold specialization measure that relies on

data from two individuals with possibly distinct notions of time. However, the data are still

subject to a gender-specific reporting bias which we handle by analyzing the data as reported

by men separately from the data as reported by women.

A remarkably small fraction of our sample lacks complete information on these seven

housework tasks. Information on the primary respondent’s housework time is available in all

but 235 or just under 5% of the cases. Restricting the sample to those couples for whom

information is available on both partners, eliminates an additional 155 couples.9 These

selection restrictions favor married couples somewhat over cohabiting couples, but it seems

likely that the cohabiting couples not captured are more often those experiencing troubles

within their relationship so this bias is more likely to obscure differences between married and

cohabiting households than to aggravate them. In total 4474 couples have a complete record

of housework time as reported by at least one person. As 2865 households provide complete

records for both partners, there are a substantial number of reports provided by both men

(3559) and women (3675) even after limiting the sample to those reporting on all other

explanatory variables. As discussed above, to allow for possible gender bias in reporting we

8 We deem unreasonable any report suggesting that an individual spent more than 70 hours a week or more than 10 hours a day on housework. 9 One household is excluded for reporting no time on housework.

7

analyze these samples separately. As there is some evidence that women provide more

accurate reports (CITES are in my office), results for the data reported by women are

presented in the text with those for men (available upon request) discussed only where they

are substantially different.

The Danish data come from the Danish Time Use survey (DTUS) conducted in 2001,

where a representative sample of the entire Danish adult population (16-74 years) was drawn

from the administrative registers in Statistics Denmark. These data provide both questionnaire

and time diary-based information on spousal contributions to housework. In total, 2739

respondents or 66% of those contacted completed a questionnaire. Only 49% completed a

time diary, but these response rates are close to those obtained in the time-use surveys for the

other Nordic Countries (Rydenstam, 2003; Vaage, 2002). A non-response analysis (Bonke,

2002) shows no significant skewness with respect to civil status, sex, or age. This sample,

too, was necessarily restricted to couple households (1820).10 The exclusion of couples with a

partner less than age 20, over age 60, or enrolled in school further reduces the questionnaire-

based sample to 1326.

The Danish time-use survey is relatively unique in obtaining information on

household work from both questionnaire and time diary surveys. It is this characteristic of the

data which allows us to compare whether the two types of time use data (questionnaire and

time diary) yield similar results in an analysis of intrahousehold specialization.11

The questionnaire data are derived from the question, “Who does the following

activities in your household?” where the activities include: Meal Preparation, Dishes,

Cleaning, Laundering, Gardening, House Maintenance, Driving to School/Day Care, Picking

up from School/Day Care, Driving to/from other activities, and Shopping. This definition of

household work is in accord with that used in other time-use surveys and follows the

recommendations for future European time-use surveys (Eurostat, 2000). Here, Gardening

and House Maintenance are combined to more closely match the ‘outdoor maintenance’

activity from the NSFH. Likewise the three activities involving transportation are combined

to match the ‘driving others’ activity from the NSFH.

Respondents identify who performs the activity self and/or spouse (see Appendix A

for an illustrated example). If only one partner is identified as performing the task, there is

specialization in that task. If both are identified as performing the task, there is no 10 One respondent was excluded due to lack of information on the partner and two were excluded for having same sex partners. 11 Unfortunately, the recently fielded American Time Use survey provides time diary information for only one respondent per household and hence can not be used for this analysis.

8

specialization in that task. If neither partner is identified as performing the task, this activity

does not enter into our specialization measure. Overall, 1318 persons provide complete

questionnaire-based information on time use. In general, the DTUS and NSFH activity

classifications are very similar. We believe cross-country comparison of intrahousehold

specialization is possible with these data.

The diary data obtained from this survey consist of a weekday and a weekend day

diary for each partner within the household. The diary includes questions on primary and

secondary activity, as well as a location question and a “with-whom” question. The activity

questions are open-ended, the respondent being asked to use his/her own wordings. These

descriptions are then coded into standardized activities. A substantial fraction of the

respondents who completed a questionnaire failed to complete any time diary (over 30%).

Others completed fewer than four diaries or failed to completely fill out the diaries.12 Our

final diary-based sample consists of 711 households. As the decision to complete four diaries

may not be a random one, but may be correlated with household income and value of time, we

experiment with sample selection controls in estimating our formal model of intra-household

specialization on the Danish time diary data.

4. Intrahousehold Specialization

4.1. Definition

Aggregated measures of housework done by men and women or of the share of

housework done by the male partner do not accurately identify the degree of intrahousehold

specialization. A man and a woman in a couple, spending the same amount of time on

housework, but on different tasks, would share time equally by such a measure when in fact

they are wholly specialized by task. Specialization within a household occurs when members

divide up tasks and individually allocate their time to only a subset of activities, rather than

dividing their time more evenly across all tasks. The ‘traditional’ two-person household with

one wage earner and one housekeeper is an extreme case of specialization by activity. In fact,

the measure of specialization we construct is gender neutral. It says nothing about equal

sharing of housework, or who is specializing in what (the usual suspects: women do the

cleaning and laundering and men do the gardening and outdoor maintenance). Instead the

measure concentrates on identifying the degree of intrahousehold specialization observed for

the seven housework tasks identified in each survey.

12 We only use those diaries that include activity reports for at least 23 of 24 hours.

9

10

The specialization measure we use is an index measure that takes a value of 0 when

there is no intrahousehold specialization in these seven housework tasks and a value of 1

when there is complete intrahousehold specialization. A value of zero means that each

individual contributes (equally where measured) to each task. A value of one means that each

task is performed by only one partner. Where the amount of time spent is reported, the tasks

are weighted by the amount of time spent. Where the amount of time spent is reported, the

measure is equivalent to a measure of the degree to which household housework time would

have to be increased to achieve equal sharing (thus a value of 1 implies that the household

would have to double its housework time with the nonparticipating partner adding equal time

to the participating partner on each activity).

In the case of the NSFH and DTUS Diary Data, the Specialization Index has the

following form:

where HWiM and HWi

F indicate the time spent on housework task i by men and women

respectively. The NSFH provides information on usual weekly time for each partner. The

DTUS diary data provide information on both weekday and weekend days for each

respondent. We use a weighted sum of these diaries that assigns a weight of 5 to the weekday

and a weight of 2 to the weekend surveys, to take the difference between weekdays and

weekend days into account. Overall, we evaluate specialization for only seven tasks. The

numerical adjustments simply scale the index to fall between 0 and 1.

The intrahousehold specialization measure calculated using the DTUS questionnaire

data is much more limited in its nature. The arguments in the numerator take a value of one

for those single activity tasks (meal preparation, dishes, cleaning, laundry, and shopping) that

the respondent indicates are performed by only one partner, else zero. An average value of

specialization is constructed across activities when a task comprises more than one activity

(Outdoor Maintenance and Driving Others). The denominator consists of the number of

different tasks that are performed within the household. Because HW has only a small

number of possible values using these data, this index is not as ‘smooth’ as those constructed

from the NSFH or the DTUS Time Diary data. For comparison purposes, we use the NSFH

( )

( )25.0

,SI 7

1

7

1 ×

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

−+

=

∑

∑

=

=

i

Fi

Mi

i

Fi

Mi

HWHW

HWHWMax

data to construct a similar measure. To this end, we use the NSFH time reports to determine

if each of the seven tasks is performed by one partner or by both and give the tasks equal

weight in the construction of the index. This index allows for a clearer cross-country

comparison of intrahousehold specialization.

4.2. Measurement

Below we compare the specialization index values stemming from the US and the

Danish questionnaire information as well as the Danish time diary surveys. A comparison of

the US and Danish questionnaire-based indices will reveal the sensitivity of these indices to

different types of questionnaire data and be suggestive of cross-country differences in

intrahousehold specialization. A comparison of the Danish questionnaire and time diary data

will reveal differences due to time use measurement. A comparison of the questionnaire-

based data for those who complete and those who do not complete a diary will reveal if those

completing four diaries are observationally different from those who do not. This descriptive

analysis of the intrahousehold specialization measure will be followed by a more formal

multivariate analysis of the factors associated with intrahousehold specialization.

The questionnaire-based and diary-based specialization indices (SI) are identified with

a Q for questionnaire and a D for diary. The US and Danish indices are identified with the

initials US and DK respectively. We keep in mind that the US measures are reported by

women, but abstain from identifying it in the variable names. On the contrary, we distinguish

between the US based measures that use all the time reports versus those that mimic the

extreme reports available from the Danish questionnaire by appending an A for “all” and an

“M” for “modified”. Thus, the variable name US SIQA indicates the US questionnaire-based

specialization index as calculated from women’s reports using all available time measures.

4.2.1. Comparing the US and Danish indices

The questionnaire-based specialization indices are substantially different. The US

measure that uses all the time reports (US SIQA) has a mean value (0.62) that is almost twice

that obtained from the Danish data (0.34). This difference is clearly reflected in the

distributional analysis. While fewer than 5% of the US sample reports less than 20%

specialization, almost 40% of the Danish sample reports less than 20% specialization.

Conversely, while about 26% of US households have an index value of at least 0.80, only 4%

of the Danish households report such complete specialization.

11

Much of this differential is driven by differences between the questionnaire data

available in Denmark and the US. Whereas the US data includes estimates of time spent on

housework by each partner, the Danish data include only a simple participatory response for

each activity. This creates two key differences between the indices. First, the Danish index

gives equal weight to each of the housework activities because there is no data in the

questionnaire about relative time use. The US index is constructed by weighting each of the

seven activities based on the reported household time spent on that activity. Total household

time spent on each activity varies from a mean of almost eleven hours a week for meal

preparation to a mean of only three hours a week driving others. If households are more

likely to specialize in activities that take up more time, failing to take into account such time

differences may bias the Danish index DKSIQ towards zero.

Table 1 US versus Danish Questionnaire-Based Specialization Index Values

US SIQA US SIQM DK SIQFull Sample Mean 0.623 0.438 0.349 Distributional Analysis 0.00 – 0.19 4.76% 28.11% 39.23% 0.20 – 0.39 14.07% 19.32% 27.85% 0.40 – 0.59 24.84% 23.43% 16.54% 0.60 – 0.79 29.90% 12.05% 12.59% 0.80 – 1.00 26.42% 17.09% 3.79% # of Observations 3675 3675 1318 US data as reported by Women.

Second, the availability of only a simple participatory response in the Danish data

means that for most of the seven activities the specialization measure for the activity is either

0 or 1 – either both partners contribute or only one does.13 The availability of time use

measures in the US data allows the specialization measure for each activity to take a much

broader range of values. If both partners contribute time but one contributes 75% of the

13 To construct activities comparable to those available in the US data, one activity (outdoor maintenance) combines information on two Danish categories and so the specialization measure for this activity can take on three values: 0, 0.5, or 1. Another activity (driving others) combines information on three Danish categories and so can take on additional values.

12

household time, the Danish data are likely to show no specialization (both participate)

whereas the US data will show some specialization. When the US index is modified to mimic

the Danish data by characterizing any time spent by a partner on an activity as participation

and by weighting each of the seven activities equally in constructing the total specialization

index (US SIQM), the US and Danish indices have much more similar means (0.44 versus

0.35) and distributions. About two-thirds of the total difference is accounted for by this

transformation. Further analysis indicates that it is the availability of only a simple

participatory response not the equal weighting of activities that drives the differential. When

the weights are forced to be equal, but the participatory responses more detailed the mean US

specialization index value is 0.636 or slightly higher than that observed with non-equal

weights – suggesting that households are not more likely to specialize in activities that take

more time. When the weights are allowed to be a function of household time but the

participatory responses for each of the seven activities are forced to take 0/1 values, the mean

US specialization index value falls to 0.369.

While much of the cross-country difference is attributable to differences in the

questionnaire data, however, there is reason to believe that these data show US households

engaging in more intrahousehold specialization than Danish households. The mean index

value remains higher for the US even when constructed to more closely resemble the Danish

measure (US SIQM). This is true even though the modified US measure should be biased

towards zero as compared with the Danish measure because, in the case of the Danish data,

participation in two of the activities was calculated by aggregating over several activities and

so has a higher chance of showing more specialization.14 The simple fact that a greater

fraction of US households report complete specialization (7%) than the fraction of Danish

households reporting an index value of 0.8 or higher (3.8%) also provides evidence of greater

intrahousehold specialization within the US. Such complete specialization should be

similarly reported in either questionnaire.

An analysis of the US time use data as reported by men demonstrates the same

sensitivity to the form of the questionnaire data, particularly the same sensitivity to the nature

of the participatory responses. Men in the US, however, report spending more time on

housework (particularly those activities frequently dominated by women) than their partners

report them spending and so the specialization index has a lower value when based on men’s 14 For example, “gardening” and “house maintenance” activities are combined in the Danish data to construct a measure of “outdoor maintenance” comparable with the US data. If one partner were to specialize in gardening and the other in house maintenance, the Danish data would indicate complete specialization while the US data would not.

13

time reports than women’s: Male US SIQA is 0.561 versus 0.623 for the Female US SIQA.

The modified US specialization index based on men’s time reports is almost identical to the

Danish measure: Male US SIQM is 0.334 versus 0.349 for the DK SIQ. It is of some interest

to note that there is no comparable differential by the gender of the Danish respondent. The

means of DK SIQ as reported by the sample of men and women are both 0.349. Still, the

fraction of US men reporting complete specialization is the same as the fraction of Danes

reporting specialization of 0.8 or higher: 4%. Thus, even though men in the US report less

intrahousehold specialization than women in the US, there is still some reason to believe that

the more egalitarian minded Danes specialize even less.

4.2.2 Comparing the Danish indices

The Danish diary data provide the time use measurements that are so sorely missing

from the Danish questionnaire data. Indeed, these time use measurements are likely more

precise for the 48 hours for which they are measured than those available from the US data

because they are diary rather than questionnaire-based and so not as subject to recall error or

bias. As they are based on only a particular 48 hours rather than a ‘normal’ seven day week,

the diary-based specialization index is not directly comparable to the US index. However,

differences between the Danish questionnaire-based and diary-based specialization indices, at

least for those observations for which both are reported, must be attributable to differences in

the time use measurements off which they are calculated. In total, there are 1318 households

for which the questionnaire-based index can be calculated and 711 households for which both

the questionnaire and the diary-based indices can be calculated. Table 2 presents summary

information for each of these three indices.

The first two columns present summary statistics for the questionnaire-based index

from the full sample and the diary sample. There are no substantial differences between the

samples in either the average or the distribution of the index and the differences by other

characteristics are modest at best and not significant at the 5% level. This table presents little

evidence that sample selection is an issue in the reporting of the diary data.

14

Table 2 Danish Questionnaire versus Diary-Based

Specialization Index Values

DK SIQ DK SID 1318 obs. 711 obs. 711 obs. Full Sample Mean 0.349 0.348 0.628 Distributional Analysis 0.00 – 0.19 39.23% 39.80% 1.55% 0.20 – 0.39 27.85% 27.29% 14.49% 0.40 – 0.59 16.54% 16.32% 29.96% 0.60 – 0.79 12.59% 12.94% 30.94% 0.80 – 1.00 3.79% 3.66% 23.07% Q Reported by Men 0.349 0.351 0.636 Q Reported by Women 0.349 0.344 0.621 No Children 0.385 0.388 0.626 Children 0.321 0.314 0.630 Children 0-2 years old 0.310 0.276 0.601 Cohabiting 0.319 0.308 0.634 Married 0.360 0.361 0.626

By contrast, there are substantial differences between the index as calculated from the

questionnaire data and the index as calculated from the diary data, as observed by comparing

columns 2 and 3 of Table 2. The diary-based measure (DK SID) indicates 62.8%

specialization, whereas the questionnaire-based measure (DK SIQ) indicates only 34.9%

specialization. Whereas only about 4% of the households are highly specialized (> 80%) as

measured using the questionnaire data, over 20% are using the time diary data. This

differential persists even when we condition on the gender of the respondent, the

presence/absence of children, or the marital status of the couple. This is a real difference

driven by differences in the type of time use data employed. As discussed earlier, time diary

data are likely to miss less frequent activities (in this case of the 7 activities whose time use is

reflected in our specialization measure, an average of 5.4 activities are reported in the diary

data as compared with 6.3 in the questionnaire data) and to overstate specialization by task

because the diaries may reflect specialization by day as well as by task. Given the simple

participatory nature of the Danish questionnaire data, the diary data also have the potential to

demonstrate more intrahousehold specialization by providing more information on relative

15

time use. Where in the case of the questionnaire data we assume partners who ‘share’ an

activity contribute equal time to that activity, the diary data will typically reveal some

specialization (a 70/30 split, for example). Thus, it is not surprising that the diary-based index

indicates more intrahousehold specialization than the questionnaire-based index.

The two indices are correlated, but only weakly (their correlation coefficient is 0.2).

Finally, because many studies argue that questionnaire responses on housework

incorporate time spent on both a primary and secondary level, we conduct sensitivity analysis

on a measure of intrahousehold specialization calculated using diary data on both primary and

secondary time use. Both the time spent on housework and the number of different tasks

reported increase by this measure, but not appreciably. Average household housework time

increases from 16.6 to 17.5 hours per week and the average number of tasks performed

increases from 5.4 to 5.5. Not surprisingly, the average specialization index does not

substantially change either, going from 0.63 to 0.62. (See Appendix B for further details.)

The diary-based measure of intrahousehold specialization in housework is still significantly

larger than the questionnaire-based measure.

5. Results

The analysis of sample statistics is suggestive of the sensitivity of this intrahousehold

specialization measure to the type of time use data used in its construction. We proceed now

to see how sensitive multivariate analysis of intrahousehold specialization is to the particular

specialization measure employed. As the specialization index is designed to run from 0 to 1

and clearly has some massing at the extreme values, we employ a 2-sided tobit specification.

Following the literature, we include controls for a variety of individual, partner, and

household characteristics. The male partner’s age and years of education are incorporated in

the model. Older men may have more traditional images of the division of household labor

that may tend to increase the degree of intrahousehold specialization. More educated men

tend to share housework tasks more than their less educated counterparts and this more

egalitarian outlook could reduce intrahousehold specialization. The difference between the

man’s age and education and that of his partner is also incorporated in the model. Men who

have much younger partners may need to accommodate the more egalitarian norms of their

partners or otherwise pay a price in housework time in order to attract a younger partner.

Households in which the age difference between the man and the woman are large may

engage in less intrahousehold specialization. Conversely men whose partner’s are

substantially less educated may feel that their household is better off if they put forth more

16

effort in the labor market and less in home production and also increase the degree of

intrahousehold specialization. Age and education also serve as proxies for each partner’s

market value of labor. We recognize that intrahousehold specialization may take place in the

market sphere as well as the home, but due to sample size concerns, especially with the

Danish data, we did not wish to limit our analysis by employment status nor did we wish to

fully specify a model endogenizing market time allocations. Thus, ours is a reduced form

specification from the perspective of market time analysis.

Further controls are included to capture major demands on household time. We would

expect, given the benefits of intrahousehold specialization, households with greater time

demands to specialize more. To this end we include a dummy variable to identify households

with children, a second dummy variable to identify households with more than one child, and

a dummy variable to identify households with children younger than school age (six in the US

and seven in Denmark). These measures should capture in a fairly flexible manner the

increased time demands imposed by children. We also identify those households residing in

single family dwellings with a dummy variable. Outdoor maintenance tasks are hardly

necessary for those residing in apartments, thus those living in single family dwellings may

have greater time demands than those living in apartments. Similarly we control for residence

in an SMSA (in Copenhagen, in the case of the Danish data) and residence in a rural area in

order to control for different types of dwellings and potentially different access to purchased

alternatives to household labor. Unfortunately these measures are not comparable across

countries and so are not reported in our results tables. Additional controls for region of

residence and race of the respondent are incorporated in the US analysis in order to control for

other differences in demand and tastes. Full model results are available upon request.

Following Stratton (2005) we control for the type and duration of the relationship.

Married couples may behave differently than cohabiting couples. Certainly, Batalova and

Cohen (2002) found evidence of greater egalitarianism amongst cohabitors than amongst

married couples. In addition, as posited earlier, the benefits associated with intrahousehold

specialization will be greater the greater the expected duration of the relationship. We do not

know the expected duration, but control for it by including a measure of the completed

duration and the relationship type. These duration measures are self-reported (but cross-

checked against partner reports) in the US data and obtained from annual registry data in the

case of the Danish data. As these registry data go back only to 1980, relationship duration is

truncated in the Danish data. Those observations with truncated values are identified with a

dummy variable in the estimation process to help minimize bias.

17

Finally, each specification includes controls for the total time spent by the household

on the seven identified housework activities and the number of different housework activities

to which time is contributed. The more time a household spends on housework, the greater

the time constraints the household faces and the greater the household’s likely benefit to

intrahousehold specialization. Holding the total number of housework activities constant,

however, the greater the total time spent on housework the more different options there are for

distributing that time in a manner that is not consistent with intrahousehold specialization.

Variable Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.Questionnaire-based Specialization Index 0.623 0.236 0.349 0.249 0.348 0.249Modified Specialization Index 0.438 0.296Diary-based Specialization Index 0.628 0.215Married 0.929 0.257 0.736 0.441 0.754 0.431Years in Relationship 15.032 10.146 13.250 7.790 13.585 7.716Dummy for Truncated Duration Measure 0.322 0.467 0.340 0.474Hours per Week Couple Spends on Housework 42.523 18.669 27.281 15.335 27.717 15.723 - Diary Based 28.663 13.865# of Housework Activities Reported 6.463 0.663 6.313 0.587 6.304 0.567 - Diary Based 5.366 1.126Living in a Single Family Dwelling 0.743 0.437 0.826 0.379 0.844 0.363Child in Household 0.630 0.483 0.561 0.496 0.544 0.498Dummy for 2+ Children in Household 0.416 0.493 0.347 0.476 0.331 0.471Child Younger than School Age 0.280 0.449 0.299 0.458 0.273 0.446Man's Age 41.510 9.344 42.884 10.069 43.790 9.978Man's Age - Woman's Age 2.185 4.294 2.184 4.254 2.283 4.335Man's Years of Education 13.738 2.890 12.583 2.754 12.848 2.709Man's Education - Woman's Education 0.247 2.437 -0.097 2.853 -0.101 2.839

Sample Selection Variables: aRespondent is Male 0.481 0.500Dummy Stress Indicator 0.651 0.477Household Income 12.595 0.357

Number of Observations 3675 1318 711

a: The sample selection variables are observed for only 1273 observations.

Table 3Sample Statistics

US Questionnaire DataWomen

DK Questionnaire Data DK Diary Data

Thus, the net effect of total household housework time upon intrahousehold

specialization is uncertain. Holding total time spent on housework constant, the greater the

number of housework activities over which it is spread, the greater the opportunity for

specialization. Thus, we expect the number of housework activities to positively affect

specialization.

18

Given the substantial fraction of Danish questionnaire respondents who failed to

complete the diaries, we analyze the Danish time diary sample both with and without sample

selection controls. The particular instruments we employ to identify those who complete a

diary are the gender of the respondent filling out the questionnaire, household net income, and

a measure of respondent stress. We hypothesize that households with a greater value of time

(as indicated by household income) and under greater time pressure (stress) would be less

likely to complete the diaries. Data availability for these variables further limit the sample

selection controlled sample to 1273 respondents of whom 691 complete the time diaries.

Sample means (and standard deviations) for the primary samples used in the analysis

are presented in Table 3. The first two columns present statistics for the US questionnaire

data as reported by women.15 The remaining columns present statistics for the Danish data.

The second two columns show statistics for the full questionnaire-based Danish sample and

the last two columns show statistics for the diary-based sample. Also presented in the second

two columns are statistics for the three variables used to adjust for possible sample selection

bias. These indicate that 48% of the questionnaire respondents were male, 65% were stressed,

and average household net monthly income was about 12,600 DKK (app. 2,054 US dollars, or

1,688 Euro). The two Danish samples not surprisingly have similar means. As we have

already discussed the specialization index measures, we focus here on the differences between

the other variables in the Danish and US samples.

The table reveals both substantial differences and striking similarities between the

countries. Within the US sample, only about 7% of the couples are cohabiting. This contrasts

sharply with about a 25% cohabitation rate in the Danish samples. While Years in

Relationship appears larger for the US sample, this is largely the result of truncation at 22

years in the Danish data. When a similar constraint is imposed on the US sample, Years in

Relationship for that sample declines to 12. While about one-third of the Danish sample has

been in a relationship for over 21 years, this is true for only about 28% of the US sample.

Thus, relationships appear to be somewhat more enduring in Denmark as well as less likely to

involve formal marriage. Time spent on housework differs markedly cross-country.

American couples report spending almost 43 hours a week on the seven housework activities

measured here. Danish couples report spending about one-third less time at these chores.

This is true whether questionnaire or time diary measures are used to construct the time

15 The US data are everywhere weighted to control for oversampling of certain populations – such as cohabitors.

19

measure16 and is rather surprising as the greater tax burden imposed on market purchases in

Denmark would suggest that Danes should spend more not less time on housework than

Americans. The number of these seven housework activities on which time is reportedly

spent is, however, quite similar between countries. Danes are more likely to live in a single

family dwelling and less likely to have children – though not less likely to have children who

are not yet in school. US men are somewhat younger and have more years of schooling than

their Danish counterparts. In both Denmark and the US, women are about two years younger

than their partners. While the difference is not statistically significant, it is interesting to note

that in the US, women are a little less well educated while in Denmark they are a bit better

educated than their partners.

Table 4 presents coefficient estimates from the two-limit Tobit model of

intrahousehold specialization. The first two columns present the results based on the US

questionnaire data (as reported by women) for the full and the modified measure of

intrahousehold specialization respectively. The second two columns present the coefficient

estimates for the Danish questionnaire-based intrahousehold specialization. The first of these

columns uses all the data available; the second uses only the sample of respondents who also

provided time diary data. The last two columns present the results using the Danish time

diary data, uncorrected and corrected for possible sample selection bias. Estimates of the

sample selection model are presented in Appendix C. These reveal that while the gender of

the respondent and the dummy variable to identify stress were not statistically significant

determinants of which households completed the diaries, household disposable income was.

Wealthier and more educated households were significantly more likely to complete diaries,

perhaps because they felt a greater social obligation. In general, however, there does not

appear to have been a need to correct for sample selection.

16 The questionnaire asks how much time is spent by each partner on these activities as a whole, but not for each activity separately.

20

Variable SIQ FA SIQ FM SIQ SIQ SID SID - SSMarried 0.0073 0.0133 0.0016 0.0088 -0.0524 ** -0.0568 **Years in Relationship 0.0057 *** 0.0043 * 0.0158 ** 0.0173 * -0.0065 -0.0101 Years in Relationship Squared/100 -0.0080 * -0.0005 -0.0560 * -0.0626 0.0440 0.0596 Truncated Duration Measure 0.0426 0.0837 -0.0382 -0.0512 Hours/Week Spent on Housework -0.0013 *** -0.0042 *** -0.0521 *** -0.0777 *** - Diary Based 0.0239 ** 0.0254 ***# of Housework Activities -0.0131 * -0.0222 ** -0.0015 *** -0.0014 ** - Diary Based -0.0034 *** -0.0034 ***Single Family Dwelling 0.0137 0.0021 0.0054 -0.0018 0.0275 0.0211 Child in Household 0.0653 *** 0.0718 *** -0.0083 0.0117 0.0090 0.0131 2+ Children in Household 0.0050 -0.0056 -0.0093 0.0061 0.0173 0.0168 Child Younger than School Age 0.0451 *** 0.0452 *** 0.0308 -0.0123 0.0135 0.0231 Man's Age 0.0021 *** 0.0031 *** 0.0029 ** 0.0010 0.0017 0.0020 Man's Age - Woman's Age -0.0016 -0.0018 0.0016 0.0027 -0.0008 -0.0016 Man's Years of Education -0.0210 *** -0.0363 *** -0.0238 *** -0.0169 *** -0.0099 *** -0.0122 **Man's Education - Woman's Education 0.0163 *** 0.0249 *** 0.0151 *** 0.0124 *** 0.0041 0.0058

Standard Error 0.2387 0.3236 0.2598 0.2577 0.2178 0.2178Lambda -0.1512

Number of Observations 3675 3675 1318 711 711 711# left censored 14 430 96 53 0 0# right censored 266 266 50 26 44 44

(a) These specifications also include dummy variables to identify blacks, non-black/non-whites, those residing in an SMSA, those residing in a rural area, and those residing in the West, South, and Midwest (Eastern residence is the base case). (b) These specifications also include dummy variables to identify those residing in Copenhagen and in rural areas. Asterisks indicate statistic significance: *** at the 1% level ** at the 5% level * at the 10% level

Table 4Two-Limit Tobit Results

US Data (a) Danish Data (b)

The correction term, lambda, in the last column is not statistically significant at conventional

levels. These results are similar to those observed in the US, where Abraham, Maitland, and

Bianchi (2005) found that more educated persons were more likely to complete the time diary

component of the American Time Use Survey but that ‘busier’ people were not, and that there

is no evidence of selection bias in the time estimates. Thus, we focus on the non-sample

selection corrected estimates for the time diary data in the discussion that follows.

There are remarkable cross-country similarities in the intrahousehold specialization

models that rely on questionnaire-based measures of time use. This is true despite the

significant differences observed between the specialization indexes constructed from the

questionnaire data. It is also true for the US results using data as reported by men (results

available upon request).

Longer relationships are associated with greater intrahousehold specialization (though

with diminishing returns) in all four specifications.17 This result is as predicted if current

17 “Years in relationship” is significant at the 1% level when only a linear measure is included in the equation modeling the modified US specialization index.

21

duration is a reasonable proxy for expected duration. Indeed, the fact that shorter

relationships are more heterogeneous (because they include both relationships that will be

short-lived and relationships that will be long lived) suggests that the impact of relationship

duration may be understated here. Expected duration was predicted to positively impact

specialization because the expected returns to specialization will be greater and the expected

costs lower for more enduring relationships. The magnitude of the duration measure is

similar across countries in a linear specification, but appears to have greater diminishing

returns in Denmark. The dummy variable identifying households for whom the duration of

the relationship is over 22 years takes on the expected positive sign for the Danish sample,

though it is not statistically significant.

Households with older men engage in more specialization, but households in which

the women are younger than the men do not engage in significantly less specialization. It may

be that relative comparative advantages become clearer over time and encourage further

specialization. Alternatively this result may be brought about by generational differences in

social norms. As the Danish sample shrinks to that for which the time diary data are

available, this effect diminishes in magnitude. This can be a spin-off from the sample

selection, despite the fact that it is not significant, where wealthier and more educated couples

are more likely to complete the diaries.

More educated couples are found to engage in less intrahousehold specialization.

Again social norms may play a role here as there is evidence that more educated men

contribute more time to housework and have more egalitarian views regarding tasks

(CITES…). However, we also find that there is more specialization the lower the woman’s

education relative to the man’s within the household. This suggests that couples with

different education levels may benefit more from specialization not only in the market but

also in the home.

Contrary to expectations, we find in all four specifications that the more time spent on

housework, the less intrahousehold specialization. We had expected that the greater the time

demands, the greater the possible benefits from specialization and so the greater the

specialization. We also find that the greater the number of distinct housework activities for

which time is reported, the lower the degree of specialization. The amount of time spent has a

particularly large impact in Denmark; the number of activities has a particularly large impact

in the US.

One key difference observed between the Danish and US results is in the impact of

children on intrahousehold specialization. Children do not appear to have much impact on

22

specialization in Denmark, but do in the US. The presence of children, particularly young

children, is associated with a large increase in intrahousehold specialization in the US.

While marital status and residence in a single family dwelling are typically associated

with greater intrahousehold specialization using the questionnaire-based measures of time use,

neither of these factors is statistically significant in any specification using questionnaire

based data. It is of some interest, however, that when a dummy variable to identify those

marriages that began as cohabitations is incorporated in the US model, the coefficient to

marriage increases by a factor of four and has a p-value of 0.14, while the coefficient to the

dummy variable is negative, statistically significant, and of about the same magnitude as the

marital coefficient. This suggests that as in Batalova and Cohen (2002), there may be

differences between married couples whose relationship began as cohabitors and those that

did not.

Results using the diary-based measure of intrahousehold specialization are quite

different. While the education of the male partner and the number of distinct housework

activities still have a similar negative association with specialization, the effect of marital

status, years in the relationship, time spent on housework, and age changes markedly.

Marriage now has a significant negative relation and relationship duration has no significant

relation to specialization. Time spent on housework by the couple now has the previously

expected positive relation to specialization – with more housework increasing specialization.

As before, the impact of children on household specialization within Denmark is not

significant. As was the case when using the questionnaire-based measure for the smaller

Danish sample, men’s age is not significantly associated with intrahousehold specialization,

although the magnitude of the effect is more similar to that observed with the full

questionnaire sample and thus the difference may be attributable to the smaller sample size of

the diary-based sample.

6. Conclusion

The specific focus of this paper is to test Stratton’s model of intrahousehold specialization

using both cross-country and cross-data type differences in the measurement of and the

factors related to intra-household specialization. First, we replicate her results using similar

US data, and then we perform comparable analysis using both questionnaire- and time diary-

based data on a similar set of housework activities from the 2001 Danish Time Use Survey.

The two data sets are the 1992-94 wave of the US based National Survey of Families

and Households (NSFH), and the 2001 Danish Time Use Survey (DTUS). The first data set

23

contain questionnaire-based responses regarding usual time spent on nine different housework

tasks by both partners in a household during an average week. The second data set includes

both simple ‘who done it’ measures of housework (Self, Partner, or Both) and more detailed

time diary data.

Much of this differential is driven by differences between the questionnaire data

available in Denmark and the US. Whereas the US data includes estimates of time spent on

housework by each partner, the Danish data include only a simple participatory response for

each activity.

We further model the relation between intrahousehold specialization and household

characteristics to see how these results differ by country and by time use measure. Following

Stratton (2005), we posit that the degree of intrahousehold specialization in housework will be

a function of the costs and benefits associated with such specialization. Thus, the market

earnings potential of each partner will be important as this determines their alternative value

of time. While we focus here on intrahousehold specialization in housework, specialization

within the marketplace is also possible and will be related to specialization within the home

due to common time constraints. The presence of children, particularly pre-school aged

children, and home ownership impose serious time constraints that may affect the degree of

intrahousehold specialization. Further, Stratton (2005) argues that marital status and the

duration of the relationship are also related to the degree of intrahousehold specialization. If

there are costs associated with changing one’s activities, then the longer the expected period

of specialization the lower will be the costs and the greater will be the specialization. Married

couples tend to be together longer than cohabiting couples – at least in the US – and thus

should be more specialized. Her results suggest that the duration of the relationship is

important, but having controlled for the duration, marital status is not. Batalova and Cohen

(2002) do not control for relationship duration but find that couples who have cohabited

together are more likely to share housework time equally. Although they attribute their

division-of-labor results to the more egalitarian preferences of cohabiting couples, their

results may be related to intrahousehold specialization in that their measure of housework is

limited to only a few tasks, most of which tend to be female dominated.

Evidence of cross-country differences in the allocation of housework time is

widespread (see Juster and Stafford 1991 for a partial review). Batalova and Cohen (2002)

find cross-country differences related to the fraction of cohabiting couple households in the

country at large – suggesting differences possibly based on social norms. Cross-country

differences in the degree to which childcare is available or state subsidized may also affect the

24

degree of intrahousehold specialization and its association with household composition.

Similarly differences in taxation levels can cause significant cross-country differences in the

relation between net-earnings and the market prices of goods and services that may substitute

for intrahousehold production services. There exist substantial differences in social norms,

childcare subsidies, and taxes between the Scandinavian Welfare Regime observed in

Denmark and the Liberal Welfare Regime observed in the US that make a comparison of

intrahousehold specialization between these two countries of particular interest.

There are advantages and disadvantages to capturing specialization by time. While

such specialization is real and does represent an opportunity to gain, we choose here to focus

on specialization by task rather than by time performed in order to more closely mimic the

type of specialization captured by questionnaire data. Ideally we would have diaries covering

an entire week’s worth of activities against which to check the accuracy of the questionnaire-

based measures of intrahousehold specialization. What we have are 48 hour time diary data.

These data will mask some but not all specialization by day and will capture a broader range

of activities than a 24 hour time diary. To further mitigate any bias from failure to report an

activity, we perform sensitivity analysis examining both primary and secondary time use

activities.

One key difference observed between the Danish and US results is in the impact of

children on intrahousehold specialization. Children do not appear to have any impact on

specialization in Denmark, whereas US children seem to increase specialization in American

households. These cross-country differences are likely attributable to the substantial cross-

country differences in the availability of affordable, high quality day care. The Danish social

welfare system provides subsidized childcare services that are only available at high cost in

the private sector in the US. Thus, the impact of children on households is likely greater in

the US than in Denmark and so affects intrahousehold specialization more in the US than in

Denmark.

Overall, analyzing both cross-country and cross-data type differences in specialization

has shown interesting differences and similarities, both across countries and across data type.

Further analyses are scheduled and will hopefully shred more light on both intrahousehold

specialization and the differences in data.

25

Bibliography

Abraham, K. G., A. Maitland, and S. Bianchi. 2005. “Nonresponse in the American Time Use Survey: Who is Missing from the Data and How Much Does It Matter?” Presented at the American Time Use Survey Early Results Conference in N. Bethesda, MD. December 2005.

Batalova, J. A. and P. N. Cohen. 2002. "Premarital Cohabitation and Housework: Couples in Cross-National Perspective." Journal of Marriage and Family, 64: 743-755.

Bittman, M., P. England, L. Sayer, N. Folbre, and G. Matheson. 2003. “When Does Gender Trump Money?: Bargaining and Time in Household Work.” American Journal of Sociology, 109: 186-214.

Blair, S. L. and D. T. Lichter. 1991. Measuring the Division of Household Labor: Gender Segregation of Housework Among American Couples, Journal of Family Issues, 12: 91-113.

Bonke, J. 2002. Tid og velfærd. (Time and Welfare). Report 02:26. The Danish National Institute of Social Research.

Bonke, J. 2005. Paid Work and Unpaid Work: Diary Information versus Questionnaire Information. Social Indicator Research, 70: 349-368.

Bryant, W. K., H. Kang, C. D. Zick, and A. Y. Chan. 2002. “Measuring Housework in Time Use Surveys.” Review of Economics of the Household, 2: 23-47.

Davis, S. N. and T. N. Greenstein. 2004. “Cross-national Variations in the Division of Household Labor.” Journal of Marriage and Family, 66 (5): 1260-1271.

Eurostat. 2000. Guidelines on Harmonised European Time Use Surveys. European Commission & Eurostat. Luxembourg.

Floro, M. S. and M. Miles. 2003. “Time Use, Work and Overlapping Activities: Evidence from Australia.” Cambridge Journal of Economics, 27(6): 881-904.

Gupta, S. 1999. “The Effects of Transitions in Marital Status on Men’s Performance of Housework.” Journal of Marriage and the Family, 61: 700-711.

Hersch, J. and L. Stratton. 2000. Household Specialization and the Male Marital Wage Premium. Industrial and Labor Relations Review, 54(1): 78-94.

Ironmonger, D. 2003. “There are only 24 Hours in a Day! Solving the Problematic of Simultaneous Time.” Paper presented at the IATUR Conference in Brussels, Belgium.

Juster, F. T. 1985. “Conceptual and Methodological Issues Involved in the Measurement of Time Use.” In: Time, Goods, and Well-Being, eds. F. T. Juster and F. P. Stafford. Ann Arbor, Michigan: Survey Research Center, Institute for Social Research, University of Michigan: 19-31.

Juster, F. T. and J. P. Stafford. 1991. “The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement.” Journal of Economic Literature, 29(2): 471-522.

Kitteroed, H. 2001. Does the recording of parallel activities in Time Use Diaries affect the way people report their main activities? Social Indicators Research, 56(2): 145-178.

Lee, Y. and L. J. Waite. 2005. “Husbands’ and Wives’ Time Spent on Housework: A Comparison of Measures.” Journal of Marriage and Family, 67: 328-336.

Pollak. R. A. 2005. Bargaining Power in Marriage: Earnings, Wage Rates and Household Production. NBER Working Paper 11239.

Robinson, J. P. 1985. “The Validity and Reliability of Diaries versus Alternative Time Use Measures..” In: Time, Goods, and Well-Being, eds. F. T. Juster and F. P. Stafford. Ann Arbor, Michigan: Survey Research Center, Institute for Social Research, University of Michigan: 33-62.

Rydenstam, K. 2003. Tid för vardagsliv (Time for Everyday Life). Statistiska centralbyrån.

26

Shelton, B. A. and D. John. 1996. “The Division of Household Labor.” Annual Review of Sociology, 22: 299-322.

South, S. J. and G. Spitze. 1994. Housework in Marital and Non-Marital Households. American Sociological Review, 59: 327-347.

Stratton, L. 2005. Specialization in Household Activities within Cohabiting versus Married Households. Mimeo.

Szinovacz, M. E. 2000. “Changes in Housework after Retirement: A Panel Analysis.” Journal of Marriage and the Family, 62: 78-92.

Twiggs, J. E., J. McQuillan, and M. M. Ferree. 1999. “Meaning and Measurement: Reconceptualizing Measures of the Division of Household Labor.” Journal of Marriage and the Family, 61: 712-724.

Van den Broek, A. and K. Breedveld. 2004. Trends in Time. The Use and Organization of Time in the Netherlands, 1975-2000. SCP, Social and Cultural Planning Office of the Netherlands.

Vaage, O. 2002. Til alle døgnets tider. Tidsbruk 1971-2000 (All over the day. Time Use 1971-2000). SA 52. Oslo: Statistisk Sentralbyrå.

Winkler, A. E. 2002. “Measuring Time Use in Households with More than One Person.” Monthly Labor Review, 125(2): 45-52.

27

Appendix A

2001 Danish Time Use Survey

Questionnaire data on household housework time Question 85: Who is doing the following activities in your household?

Respondent Partner 1 Meal preparation X 2 Dishes X X 3 Cleaning X 4 Laundering X 5 Outdoor maintenance Gardening X House maintenance X 6 Driving others Driving to school / day care X X Picking up after school / day care X X Driving to/from activities 7 Shopping X

The respondent fills out this question by marking who does the task. There are four possibilities: the respondent does the task but not the partner, the partner does the task but not the partner, both the respondent and the partner do the task, neither the partner nor the respondent do the task. If both or neither of the partners spend time on the housework task, there is no specialization in this task. If only one of the partners – no matter which– spends time on this task, this is evidence of specialization.

28

Appendix B (to be abbreviated) Analysing secondary time use from the diaries The following are – for convenience – made on the 704 couples having both a specialization index from the diaries and a specialization index from the questionnaire. First table shows that next to all couples are using the column, included in the diary, on secondary time use. Secondary time is mostly used on watching television or listening to the radio/music (giving on average 10½ hours more time use per week), or as stating that they are joining convivial (el. social) gathering while they are doing other things as primary activities (which is stated as app. 9½ hours for women and 7½ hours for men per week). The interesting part, the housework, gives on average the women 2 more hours of housework per week, while the men are noting a little more than half an hour per week on additional housework, done as a secondary activity. Secondary time use by women # using it % using it Mean

Changed into hh:mm

Personal care 399 56.68 1.81 01:48 Market work / education 286 40.63 1.28 01:17 Housework 428 60.8 2.03 02:02 Childcare 298 42.33 2.09 02:05 Leisure time 481 68.32 2.33 02:20 Radio / TV 610 86.65 10.47 10:28 Social relations 607 86.22 9.34 09:20 Transportation 77 10.94 2.04 02:03 Total time 701 99.57 31.51 31:31 Secondary time use by men Personal care 373 52.98 1.63 01:38 Market work / education 339 48.15 1.69 01:41 Housework 255 36.22 0.63 00:38 Childcare 171 24.29 0.82 00:49 Leisure time 418 59.38 2.02 02:01 Radio / TV 563 79.97 10.63 10:38 Social relations 526 74.72 7.70 07:42 Transportation 62 8.81 1.67 01:40 Total time 688 97.73 26.85 26:51 Total time use in the family 703 99.86 58.36 58:21 The totals on housework in this table above, cannot be compared with the sum of the seven tasks of interest in the analyses below, as the housework above includes every little bit of

29

housework (except childcare, which is separated out), whereas the seven tasks below do not cover all housework tasks. Table showing the time use for the 704 couples having both indexes, calculated only on secondary time use Digging into the seven tasks of interest, we see that 52% of the women and 29% of the men are noting time use on the specific tasks as secondary time use. Women uses more time on meal preparation, cleaning and laundering than stated in the primary time use, and men uses a bit more time on meal preparation and cleaning.

# using it % using it MeanChanged into

hh:mm Secondary time use by women 1 Dishwashing 86 12.22 0.11 00:06 2 Meal preparation 173 24.57 0.28 00:17 3 Cleaning 130 18.47 0.21 00:12 4 Laundering 193 27.41 0.42 00:25 5 Home maintenance 21 2.98 0.03 00:02 6 Driving others 2 0.28 0.00 00:00 7 Shopping 55 7.81 0.08 00:05 Total housework 366 51.99 1.12 01:07 Secondary time use by men 1 Dishwashing 40 5.68 0.05 00:03 2 Meal preparation 88 12.5 0.14 00:08 3 Cleaning 43 6.11 0.09 00:06 4 Laundering 28 3.98 0.04 00:02 5 Home maintenance 10 1.42 0.02 00:01 6 Driving others 1 0.14 0.00 00:00 7 Shopping 65 9.23 0.07 00:04 Total housework 202 28.69 0.41 00:25 Total time use in the family 451 64.06 1.53 01:32

30

The following table show the difference in time use, whether we only uses primary time use, or we pool the primary and secondary time use. Total time used by: Women Men

Primary time use

Both primary and secondary

time useSignifi-cant

Primary time use

Both primary and secondary

time use Signifi-cant

dishwashing 1.67 1.77 * 1.08 1.13 meal preparation 5.43 5.72 * 2.68 2.82 Cleaning 3.24 3.44 1.45 1.54 Laundering 2.19 2.6 *** 0.32 0.36

home maintenance 1.36 1.38 3.15 3.16

driving others 0.93 0.93 0.49 0.49 Shopping 2.82 2.9 1.87 1.94 total housework 17.64 18.76 ** 11.03 11.44 Total time use in the family 28.67 30.2 ** Specialization index on diaries 0.6281 0.6246 Note: Time use is counted in hours * = significant at 10% level, ** = significant at 5% level *** = significant at 1% level From the table we see that including secondary time use has no significant effect on time use of the men, whereas it has an effect on the time use of women, through additional time use on laundering (significant difference at 1% level), and dishwashing and meal preparation (significant difference at 10% level). Nevertheless, the specialization index made on the information from the diaries does not show any significant difference in the mean. On top of this, we see no difference (or at least only difference at the 3rd or 4th digit) in the estimation results (see the two following tables, the first with a tobit specification and the second with an OLS), although they are not justified at the final estimation results.

31

DK SID Tobit only primary time primary and secondary time Coef Std err Coef Std err Years of relationship 0.0053 0.0020 *** 0.0053 0.0020 *** Married 0.0090 0.0303 0.0091 0.0302 # of housework activities -0.0226 0.0059 *** -0.0250 0.0059 *** Hours/week spent on Housework 0.0019 0.0009 ** 0.0020 0.0008 ** Single Family Dwelling 0.0003 0.0308 0.0039 0.0308 Child in household -0.0049 0.0286 -0.0019 0.0285 2+ children in household -0.0314 0.0276 -0.0308 0.0275 Child younger than school age -0.0206 0.0304 -0.0234 0.0302 Man’s age 0.0012 0.0016 0.0012 0.0016 Man’s age – Woman’s age 0.0025 0.0024 0.0025 0.0024 Man’s years of education -0.0147 0.0043 *** -0.0140 0.0043 *** Man’s education – Woman’s education 0.0111 0.0040 *** 0.0107 0.0040 ** Residence in Copenhagen 0.0465 0.0249 * 0.0469 0.0247 * Rural residence 0.0475 0.0240 ** 0.0472 0.0239 ** Intercept 0.5015 0.0835 *** 0.5114 0.0830 *** R-squared 0.2660 0.2780 Number of Observations 702 703 DK SID OLS only primary time primary and secondary time Coef Std err Coef Std err Years of relationship 0.0051 0.0018 *** 0.0050 0.0018 *** Married 0.0032 0.0275 0.0032 0.0274 # of housework activities -0.0216 0.0054 *** -0.0237 0.0053 *** Hours/week spent on Housework 0.0018 0.0008 ** 0.0019 0.0007 ** Single Family Dwelling 0.0040 0.0280 0.0074 0.0279 Child in household -0.0107 0.0260 -0.0078 0.0260 2+ children in household -0.0242 0.0251 -0.0238 0.0250 Child younger than school age -0.0197 0.0276 -0.0225 0.0275 Man’s age 0.0010 0.0014 0.0010 0.0014 Man’s age – Woman’s age 0.0023 0.0022 0.0024 0.0022 Man’s years of education -0.0120 0.0039 *** -0.0114 0.0039 ** Man’s education – Woman’s education 0.0091 0.0036 ** 0.0086 0.0360 ** Residence in Copenhagen 0.0419 0.0226 * 0.0422 0.0225 * Rural residence 0.0386 0.0218 * 0.0385 0.0217 * Intercept 0.4881 0.0759 *** 0.4967 0.0754 *** R-squared 0.1065 0.1116 Number of Observations 702 703

32

CoefficientRespondent was Male 0.0973

(0.0726)Log of Household Disposable Income 0.3152 ***

(0.1135)Stress Dummy 0.0614

(0.0763)Years in Relationship 0.0371

(0.0333)Years in Relationship Squared/100 -0.2172

(0.1519)Truncated Duration Measure 0.2181

(0.1968)Married 0.0209

(0.1049)# of Housework Activities 0.0548

(0.0809)Hours/Week Spent on Housework 0.0044 *

(0.0025)Single Family Dwelling 0.1528

(0.1100)Child in Household -0.0315

(0.1108)2+ Children in Household -0.1041

(0.1065)Child Younger than School Age -0.2234 *

(0.1174)Man's Age 0.0075

(0.0061)Man's Age - Woman's Age 0.0114

(0.0094)Man's Years of Education 0.0477 ***

(0.0166)Man's Education - Woman's Education -0.0335 **

(0.0149)Residence in Copenhagen 0.1639 *

(0.0946)Rural Residence 0.0545

(0.0866)Constant -5.5034 ***

(1.4485)

Number of Observations 1273Log Likelihood Value -850.533

Standard errors are reported in parentheses.Asterisks indicate statistical significance: *** at the 1% level ** at the 5% level * at the 10% level

Appendix CProbit Model of Availability of Four Complete Diaries

33