Institutional Settings, Power, and Time Use by Couples: A Cross-National Comparison

By Nabanita Datta Gupta* Leslie S. Stratton**

PRELIMINARY & INCOMPLETE DRAFT Do Not Quote September 2007

JEL Code: J22 Keywords: Time Use, Decision Making by Couples, Social Welfare System, Power

* Research Professor, CIM, IZA, The Danish National Center for Social Research, Herluf Trolles Gade 11, DK-1052 Copenhagen K, Denmark. Phone +45 3348 0985, Fax +45 3348 0833, [email protected] ** Associate professor, CIM, IZA, Virginia Commonwealth University, PO Box 844000, Richmond VA, 23284-4000, USA. Phone: (804) 828 7141, Fax: (804) 828 8884, [email protected]. Corresponding Author. Acknowledgement: We are grateful to Camilla Østerballe Pedersen and Philip Røpcke for very helpful research assistance. We gratefully acknowledge financial support from the Danish Social Research Council, FSE.

Institutional Settings, Power, and Time Use by Couples: A Cross-National Comparison

ABSTRACT We explore cross-country differences in the impact standard power measures have on couples’ time use, hypothesizing that different institutions, in particular different social welfare systems, will alter the intrahousehold distribution of power. A standard collective model of household decision making in which household utility is a weighted average of the utility of the individuals is employed. Individual utility is posited to be a function of private goods consumption, private leisure time, and a household public good produced through time spent on housework. These models typically assume that power is a function only of each individual’s current or long-run earnings potential relative to the household’s current or long-run earnings potential. While this power measure is meant to incorporate each individual’s threat point, cross-country differences in the national welfare system may also affect the salience of the balance of power within households by altering the individuals’ alternative opportunities. National attitudes regarding income distribution may also be relevant. We explore this possibility using US and Danish time use data. The US social welfare system is generally less supportive than that observed in Denmark, which follows the more egalitarian Scandinavian model. Our results indicate that standard measures of individual power do have a more significant impact on leisure time in the US than in Denmark.

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Institutional Settings, Power, and Time Use by Couples: A Cross-National Comparison

Couples’ time use is likely a complex function of household needs, abilities, preferences, and individual bargaining power. We explore cross-country differences in the impact standard power measures have on couples’ time use, positing that different institutions, in particular different social welfare systems, will alter the intrahousehold distribution of power. Individuals living in countries with more generous welfare systems, particularly those at a disadvantage with respect to earnings power, will credibly derive more influence over household allocation decisions than similar individuals living in countries with less generous systems. We empirically investigate this hypothesis using US and Danish time use data. The US social welfare system is generally less supportive than that observed in Denmark, which follows the more egalitarian Scandinavian model. We find some evidence that standard measures of individual power do have a more significant impact on leisure time in the US than in Denmark.

LITERATURE REVIEW As the study of the allocation of resources, economics has a lot to say about individuals’ allocations of time and money. Modeling household allocation decisions is substantially more complicated. One class of models employs a household utility approach, positing that household members act together to maximize a joint household utility function subject to the usual time and income constraints. In its strictest form, all goods are jointly consumed. More complex economic models have employed game

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theoretical approaches in which individuals continue to have separate utility functions and bargain over household choices either cooperatively or non-cooperatively. ‘Caring’ can be incorporated in such models when one individual’s utility function includes as an argument the utility of others. The sociology literature (see the theories reviewed in Geist, 2005) tends to diverge from the assumption of rational agents maximizing common household utility, envisioning instead the intrahousehold bargaining problem as a power struggle in which the partner with the greater share of material resources is able to reduce his or her share of the housework (Brines, 1993). As males typically command greater relative resources, some view the unequal division of power within the household as reflecting the ‘dependency ‘of women on their husbands (Sørensen and McLanahan, 1987), or by another view, as the outcome of men and women being influenced by societal norms which dictate gender typical roles with respect to market and home production. Some sociologists point to the observation that women who earn more than their husbands may compensate for this atypical pattern by ‘doing gender’ at home i.e. taking on a greater share of the housework (Bittman et al., 2003). Still, a study by Geist (2005) comparing different welfare state regimes finds that the gender division of labor remains more unequal in conservative regimes than in liberal or socio-democractic regimes even after controlling for time availability, relative resources and gender ideology, suggesting that macro institutional features also influence the household division of labor..

(1)

θ U1 + (1-θ) U2

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More recently much of the literature has focused upon collective models of household decision making (Chiappori 1992). These models recognize that individuals have distinct utility functions (U1 and U2) but suggest that individuals cooperate when coming together to form a joint household by adopting a sharing rule (θ) that determines the relative weight each individual’s preferences will receive in the joint household. The nature of this sharing rule is highly flexible. It may be based upon tradition or be determined by the relative power of the household members. ‘Power’ can be influenced by many factors. Relative earnings ability may be important because individuals with higher earnings potential have the capability of bringing more resources to the household. This ability may give them the power to allocate a greater share of the household resources. Similarly, bargaining models posit that those with greater earnings potential have a higher utility operating as independent units and so may need additional incentives to induce them to enter a joint household – a higher θ. Whether actual earnings or potential earnings are the appropriate yardstick for measuring this relative power is unclear, though Pollack (2005) makes a strong argument that wages rather than actual earnings should be used because hours worked during marriage are likely to differ from hours worked at the threat point. Conditions in the marriage market may be important because if there are many men for every woman, then women will likely have more bargaining ‘power’ because they are relatively scarce. Likewise the ease with which relationships can be ended and the rules employed to divide up household resources in the event of a breakup may influence θ. Chiappori, Fortin, and LaCroix (2002) discuss marriage market conditions and divorce law considerations as “distributional factors” that influence bargaining power but not preferences or the budget constraint. Other

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government-regulated conditions may have a similar effect. For example, just as divorce laws may favor one party over the other, welfare regulations may favor one parent over the other. Alternatively, welfare regulations may provide a better or worse safety net for individuals.

MODEL Following the collective utility approach, we model household utility as a weighted average of the utility of the two partners in the household (denoted by the subscripts M for male and F for female). Individual utility is modeled as a function of individual consumption levels (c), individual leisure (L), and the level of the household public good that is produced. This household good is produced by combining labor inputs from each partner (H) according to a production function P. UHH = θ UF(cF, P(HF,HM), LF) + (1-θ) UM(cM, P(HF, HM), LM) The weights (θ) are a function of the earnings ability of each partner (w) and other distributional factors (S). As in Chiappori, Fortin, and Lacroix (2002), these distributional factors influence the weights but do not themselves influence utility. θ = θ(wF,wM,S) Households act to maximize their utility subject to income and time constraints. Income Constraint:

cF + cM + wF HF + wM HM + wF LF + wM LM ≤ Y + TwF + TwM

Time Constraint: Ha + La + Ea = T where goods prices are normalized to one, T is the total amount of time available, E is the time employed in the market, and the subscript a denotes the partner F or M.

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A higher θ means that the preferences of the woman receive greater weight when resources are allocated within the household. In this case, cF and LF should both increase or at least not decrease as they enter directly into the household utility function. Although there are numerous studies looking at the impact bargaining power has upon time spent on and share of household chores, the theoretical impact of an increase in θ on HF is not clear. If the woman cares more for the household good than the man, total household production should increase. To do so, at least one of the inputs, HF or HM, must increase. However, if the man cares more for the household good, then total household production may decrease. Thus the effect of θ on the time either partner spends on household chores is not clearly predicted by the theory. This suggests that an analysis of leisure time will provide clearer feedback on the nature of θ and the balance of power than an analysis of housework time. Our focus in this analysis is upon the role of welfare as a form of safety net that acts as a distributional factor (S) influencing θ. Specifically we focus on comparing how partners in couple households allocate their time in American as compared to Danish households. Our hypothesis is that because the Danish welfare system provides a much better safety net than the American system, relative earnings power will be more strongly associated with time allocation in the United States than in Denmark. The association is also likely to differ across households. For example, welfare is a safety net primarily for those with low earnings potential, thus, relative earnings may be less highly associated with time use for lower income households than for higher income households. In the US, welfare is primarily a safety net for households with children and so the impact of

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the welfare system may be felt more strongly in households with children. Even so, the benefits for children are better in Denmark than in the US (Bradshaw and Finch, 2002). Each individual’s bargaining power may also be influenced by the costs associated with ending a relationship. These costs are likely higher for married than for cohabiting couples, particularly in the US where cohabitation is only marginally recognized by the law. If these costs fall disproportionately on the higher earner in the household, then his/her bargaining power may be reduced.

DATA Our data consist of the 2001 Danish Time Use Survey (DTUS) and 2003-2005 waves of the American Time Use Survey (ATUS). The Danish sample consists of a representative sample of the entire Danish adult population (16-74 years) drawn from the administrative registers at Statistics Denmark. We exclude those over age 64, those not living in simple heterosexual couple households, and those for whom years of education can not be ascertained. The American sample derives from the Current Population Survey. Given the weights provided, it is representative of the US population. Again we exclude older persons (those over age 62), those not living in simple heterosexual couple households, and those missing information on key demographic variables. Both surveys asked respondents to complete time diaries in which they identify in their own words what they were doing over the course of a 24 hour period. One household member was chosen at random to complete a single diary in the US. Each partner was asked to complete two diaries in Denmark, one for a weekday and one for a weekend day. These diaries were completed orally using a fully flexible time frame in the case of the US

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survey, while the Danish respondents were asked to provide a written record of their activities in ten minute intervals. In both cases we restrict our analysis to those diaries missing no more than one hour’s worth of activity. Though our focus is upon leisure time, we distinguish between five general uses of time: leisure, housework, care giving, employment, and other. Leisure time includes time engaged in socializing, entertaining or being entertained, playing sports, hobbies and games, and volunteer activities as well as time spent on pet care. Housework includes time spent preparing food; cleaning house, yard, and clothes; doing projects around the home; shopping; and arranging services. Care giving includes all time spent caring for own household children and adults. The vast majority of this time is, of course, spent on own children. Employment time includes time on the job (whether primary or secondary) and in the US time spent in other income generating activities. Time spent commuting to work is not easily identified in the US and that is included along with time spent searching for work, education, sleep, and personal care in the ‘other’ time category. The top panel of Table 1 reports sample mean time use in minutes by country, by gender, and by type of day. As time use is bounded below by zero, it is of some interest to also identify the fraction of the sample reporting no time in the activities of interest. These measures are reported in the bottom panel of Table 1. A cross-country comparison reveals both surprising similarities and surprising differences in reported time use. Danish men report just under 20 minutes more leisure time on both weekends and weekdays, while Danish women report almost 20 minutes more leisure time on weekends than their US comparison groups. However, these differences constitute no more than 3 to 8% of total leisure time, which is remarkably

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similar cross-country. Time spent on the job is for women also quite similar crosscountry for women (though US women are more likely to work on weekends). Danish men, by contrast, report substantially less time on the job than American men: 10% less on weekdays and fully 40% less on weekends/holidays. Reported time spent on housework is universally higher in Denmark, particularly on weekdays, while reported time spent on caregiving is universally higher in the United States. These differences virtually cancel each other out as time spent on ‘other’ activities is again quite similar cross-country. Also of interest in the analysis of time use is the fraction of the sample reporting any time in an activity. There has been some heated debate regarding how to model reported time use: OLS, Tobit, generalized Tobit, CLAD and other estimation techniques have all been employed. At issue is how to handle individuals who report no time on an activity in a given day. Is this because they never spend time on the activity or because they do not engage in that activity daily and the interview happened to capture a day when they did not engage in that activity. Theory suggests a stronger link between power (θ) and leisure time than between power and time spent in home production. As defined here, very few individuals report spending no time in leisure activities and only in the case of men in the United States do more than 10% report spending no time on housework. Thus, it would appear that an OLS specification will be a very reasonable first approach for an analysis of either intrahousehold allocation of leisure or housework time. Gender based differences in time use are as expected. Women spend more time than men on housework and childcare, and less time than men on employment in each

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country. Women in each country also report on average less leisure time than men, particularly on weekends/holidays. Only women in the United States on weekday days report having more leisure than men and then only by less than two minutes. In both countries women report spending more time in ‘other’ activities. In our analysis of intrahousehold time allocations, a key explanatory variable is relative power (θ) within the household. We experiment with several alternative measures of power. Our primary focus, however, is on a measure of own share of couples education (Own/(Own + Partner’s) years of education). This measure is bounded below by zero and above by 1. While much of the extant literature focuses on two earner couples in order to construct a measure of earnings or wage share, we do not initially impose such restrictions. Though relative wage information is not available for every respondent, years of education is both highly correlated with wages and readily available.1 Furthermore, wages and housework hours would be more easily influenced by common unobservables implying potential endogeneity than relative education. A variety of other controls are included to capture demographic, household, seasonal, and locality based differences in time use. The marital status of the couple, the education of the respondent, and a quadratic in his/her age are included for both samples. We further incorporate dummy variables to identify African American, Asian, and Hispanic respondents in the United States and immigrants in Denmark. As household size is likely to influence time use, we control for the number of other adults present and the presence of children of various ages in both countries. Those age 15-17, age 10-14, and age 0-2 are identified with dummy variables in both countries. We employ 1

Years of education is actually encoded based on the level of schooling completed in both countries.

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somewhat different indicators for children between the ages of 3 and 9. Since children begin school full-time at age 6 in the US and at age 7 in Denmark, we control for the presence of children age 3-5 and 6-9 in the US and 3-6 and 7-9 in Denmark. While we estimate time use equations separately for weekday and weekend/holiday days, activities also vary by time of year. Seasonal dummies are included in both samples and year dummies are included to distinguish between ATUS data collected in 2003, 2004, and 2005. Unemployment rates are included as an indicator of local economic conditions. Finally, residence in Copenhagen is indicated by a dummy variable in Denmark as is residence in an SMSA in the United States.2 Three regional dummies are also included in the US model. Table 2 reports the sample means for the full sample of respondents and the common set of explanatory variables. Further details are available from the author upon request. The sample wide power measure has a mean value of 0.5 in both the US and Denmark. This is not surprising given the high degree of marital homogamy typically observed in terms of education. However, values do range widely within the population at large, particularly in the US. The spread is lower in Denmark as the education measure in Denmark has a lower mean and a lower variance than the education measure in the United States. This is caused in part by the fact that the lowest value in Denmark is 9 years whereas the lowest value in the US is 0 (as reported by less than 0.2% of the population). A low value of zero allows a power measure of 0 in the US, whereas the lowest level possible in Denmark is 0.36.

2

Unfortunately the coding of SMSA status changed about half way through 2004. We use separate dummies to identify SMSA status before and after the change and to identify missing SMSA status.

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A few other cross-country differences are noticeable. Households in general are smaller in Denmark as they are less likely to include children or other adults. As cohabitation is widespread in Denmark, only about half of Danish households are married compared to 94% in the US case. The unemployment rate is also somewhat lower in Denmark. While observations in the US are evenly spread across the seasons, most of the Danish data were collected in the fall and the spring. Similarly while diaries days in the US are pretty evenly weighted by day of week (meaning that 2/7ths of the observations are likely weekend days), each respondent in the DTUS completed both a weekday and a weekend survey hence yielding a sample of about half weekend observations.

RESULTS Given the substantial differences observed between weekdays and weekends and men and women in terms of time use, we model time use separately by gender and day of week. Table 3 presents the results from our basic specification using leisure time as the dependent variable. Table 4 presents similar results for a specification using housework time as the dependent variable. The US specifications also include controls for race/ethnicity, region, metro status, and year. The Danish specifications include controls for immigrant status and residence in Copenhagen. What we expect to find is a stronger positive relation between power (as measured by relative education) and leisure time use in the US as compared to Denmark. A weaker relation is predicted in Denmark because the more generous welfare benefits in that country provide a better safety net for those with less individual power in the household, thus giving them more bargaining power overall. There may be a negative

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relation between power and housework time, but this effect is not as clear as it depends as well on relative preferences for home produced public goods and relative productivity producing this public good. The impact of marital status is not expected to be significant or substantial in Denmark given the social acceptance accorded nonmarital relationships, but may have an impact in the US. The results are somewhat mixed with regard to leisure time. We find that power while positively related to leisure time for all persons and days in Denmark has as expected no statistically significant association with leisure time in Denmark. By contrast, for women on weekends and men on weekdays in the US there is not only a positive relation between reported leisure time and power, but a significant one. This effect does not, however, carry over to women on weekdays or men on weekends for whom more power is associated with less leisure time, albeit the relation is not statistically significant. Marital status meanwhile has no significant or substantial impact on leisure time in Denmark, while married persons in the US report significantly less leisure time on weekdays (20 minutes less for women and 60 minutes less for men) than their unmarried counterparts. This finding suggests that married persons in the US perhaps obtain less leisure than their unmarried counterparts because the latter can more credibly threaten to end the relationship if they receive less than they expect. In other respects, the results with respect to leisure are as expected. Couples with children in both countries report less time on leisure, particularly when younger children are present. The effect of young children is particularly large in Denmark on the weekends, when leisure time falls by almost an hour and a half for couples with children age 0-2. We also observe leisure time decreasing with age, but at a decreasing rate in

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both countries. The unemployment rate is weakly associated with more leisure time, particularly on weekdays but the impact is significant only for men on weekdays. The most substantial seasonal difference occurs in Denmark on weekends in spring when less time is reported on leisure. Interestingly, holidays are associated with significantly and substantially less leisure time in Denmark (2 to 3 hours less) while holidays are associated with significantly more leisure time in the US (just over 1 hour more). The relation between relative education (or power) and reported time spent on housework is theoretically less clear but would be negative if those with less power were forced by their partner to engage in more housework. Indeed we observe a negative relation for all but women in Denmark. However, only for women in the US on weekends and for men in Denmark is this relation statistically significant. As women with more power in Denmark are observed contributing more time or at least no less time on housework, the results for Denmark suggest that Danish men value the household produced public good less than Danish women so that if they have more power, not only they but to some extent their less powerful partner also performs less housework. In the US by contrast, housework appears to be more generally negatively related with power, but generally not significantly so. The impact of the other variables also differs significantly between countries. Married partners are observed contributing insignificantly more time to housework, except married women in Denmark on weekends who spend 5 minutes less per day than their unmarried counterparts. More educated women spend significantly less time on housework, perhaps because they are more productive at the activity and perhaps because their comparative advantage lies elsewhere. Education is not significantly associated

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with men’s housework time in Denmark, but reduces US men’s time on weekdays while increasing it on weekend days. Whereas age was negatively related to leisure time but at a decreasing rate, age is positively related to housework time at a decreasing rate. Leisure hits a minimum for US women around age 35, US men around age 39, Danish women around age 42, and Danish men around age 44. By contrast, housework done on weekends rises till about age 50 for almost everyone and rises on weekdays for virtually everyone over age 20. The presence of children increases American women’s housework time, particularly on weekdays, but has little impact on US men’s housework time. The effect of children on housework time in Denmark is generally small and where significant (for women with infants and older teens on weekends and for men with infants and older teens on weekdays as well as men with 10-14 year olds on weekends) the relation is negative. Older adults are associated with insignificantly more housework in the US and significantly though not substantially less housework in Denmark. Seasonal effects vary with the most persistent pattern being that less time is spent on housework in Denmark in the summer. Holidays reduce time spent on housework in both countries, relative to regular weekend days.

CONCLUSION In general we find weak evidence in support of power, as measured by own share of couples’ education, as a determinant of time allocation within couple households. As predicted by theory, we find that in six of eight cases more power is associated with more leisure time. Predictions regarding housework time are not as clear cut, however we again find that in six of eight cases, more power is associated with less housework time.

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We further hypothesized that power as measured by an earnings-related measure would have less influence in Denmark than in the US because of the more generous social welfare system in Denmark that strengthens the bargaining position of those with lower earnings power in that country. Our finding of significant positive relations between power and leisure time only in the US lends some support to this hypothesis. While we find a significant and substantial negative effect of power on housework time for men in Denmark, the fact that we find a positive effect of power on housework time for women in Denmark suggests that couples in Denmark may somehow be sorting such that less housework is favored in households where the man has more power, while more is favored in households where the woman has more power. There is also some evidence that married persons in the US either have somewhat less power than their unmarried counterparts or place a lower value on leisure time. More work is needed. Different subsamples should be analyzed, specifically a subsample of two-earner couples and subsamples with and without children. As social welfare systems offer different benefits to households with and without children, this sample division may be valuable as a tool for evaluating the relation between power and social welfare. To better test our hypothesis that the social welfare system alters the balance of power within households, we also propose to test whether power has a different impact on persons with lower absolute levels of education. These are the individuals most likely to benefit from more generous social welfare systems and so be less likely to experience a power based differential in time use. Alternative power measures should be examined, including one based on the difference in the years of education and another based on share of potential hourly

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earnings. The very detailed information on education available in the Danish sample allows us to construct a power measure for this sample based on expected lifetime earnings. Given the sociological theory that women with more ‘power’ than their husbands act to ‘do gender’ by increasing their time on household production (see Bittman et al 2003 for an empirical example and a discussion of the literature), we plan to test for a nonlinear relation between power and housework and leisure time. The role of ‘power’ may also differ by relationship type with married and cohabiting households negotiating differently. Finally, different measures of the dependent variable deserve investigation as well. Leisure time is currently broadly defined for the respondent alone. Distinguishing between leisure time with and without the partner present may be more informative still as pushing more employment and housework activities upon the partner will limit such opportunities. In addition, the housework time measure currently employed does not include time spent on care giving to any household member. Time spent on child care is clearly significant for some households and likely to influence the time available for other activities. We find that the presence of children, particularly young children is significantly negatively related to leisure time. Given the well known tendency of women to spend more time than men in child care, it is of some interest to note that children are strongly positively associated with women’s housework time in the US. This correlation may arise because mothers in the US are more likely to be out-of-the-labor force than mothers in Denmark and so more likely to take on a greater role in household production. Analysis of time spent in employment and in caregiving activities may shed further light on this relation.

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References

Bittman, Michael, Paula England, Liana Saver, Nancy Folbre, and George Matheson. “When Does Gender Trump Money? Bargaining and Time in Household Work.” American Journal of Sociology, 109 (1), July 2003, pp. 186-214. Bradshaw, Jonathan and Naomi Finch. “A Comparison of Child Benefit Packages in 22 Countries,” Department of Work and Pensions Research Report no. 174, 2002. Brines, J. “The Exchange Value of Housework.” Rationality and Society 5, 1993, 302-340. Burda, Michael, Daniel S. Hamermesh, Philippe Weil. “Total Work, Gender and Social Norms,” March 2007, NBER Working Paper No. 13000. Chiappori, Pierre-André. “Collective Labor Supply and Welfare.” Journal of Political Economy, 100 (3), June 1992, pp. 437-467. Chiappori, Pierre-André, Bernard Fortin, and Guy Lacroix. “Marriage Market, Divorce Legislation, and Household Labor Supply.” Journal of Political Economy, 110 (1), 2002, pp. 37-72. Geist, Claudia. “The Welfare State and the Home: Regime Differences in the Domestic Division of Labour”. European Sociological Review, 21 (1), 2005, 23-41. Pollak, Robert A. “Bargaining Power in Marriage: Earnings, Wage Rates and Household Production.” NBER Working Paper No. 11239. March 2005. Sørensen, A. and S. McLanahan, “Married Women’s Economic Dependency, 1940-1980,” American Journal of Sociology, 93, 1987, 659-687.

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Table 1

Time Use by Gender and Type of Day United States Women Time Use (Minutes) Leisure Housework Services Shopping Care Employment Other % Reporting No Time Leisure Housework Services Shopping Care Employment Number of Observations

Denmark Men

Women

Men

Weekday 264.4 196.5 13.9 43.8 80.3 264.7 634.1

Weekend 379.2 247.0 6.1 69.5 56.8 59.2 697.8

Weekday 254.7 96.8 8.3 23.2 34.5 429.6 624.4

Weekend 437.9 178.6 4.4 51.3 39.3 112.6 671.6

Weekday 262.5 231.8 23.4 25.6 53.8 264.5 627.4

Weekend 397.8 252.4 15.4 23.8 44.8 43.5 701.4

Weekday 273.1 140.3 17.0 15.2 30.6 384.0 612.1

Weekend 452.1 193.7 17.4 20.1 28.6 66.9 698.7

2.8% 6.0% 81.4% 50.9% 48.6% 40.6%

1.7% 6.3% 91.6% 45.8% 58.4% 79.3%

3.5% 27.7% 89.5% 66.6% 64.8% 17.2%

2.2% 19.2% 94.3% 55.2% 68.1% 67.3%

0.9% 2.0% 51.5% 42.7% 53.9% 34.1%

0.4% 2.6% 59.8% 57.3% 59.4% 83.3%

1.3% 10.1% 62.9% 62.2% 60.7% 18.1%

0.4% 8.4% 60.4% 59.0% 65.1% 75.3%

4708

4897

4306

4453

1141

1136

1015

983

US Statistics are weighted.

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Table 2

Sample Means Explanatory Variables United States Variables Power Married Education (years) Age Age Squared/100 Children age 0-2 Children age 3-5 in US, 3-6 in DK Children age 6-9 in US, 7-9 in DK Children age 10-14 Children age 15-17 Number of Other Adults Unemployment Rate Fall Winter Spring Summer Male Weekend or Holiday

Mean 0.50 0.94 13.76 41.86 18.56 0.16 0.16 0.20 0.23 0.14 0.27 5.53 0.24 0.25 0.25 0.25 0.51 0.29

Number of Observations

18364

US Statistics are weighted.

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Std. Dev. 0.05 0.23 2.79 10.20 8.53 0.36 0.37 0.40 0.42 0.35 0.61 0.96 0.43 0.43 0.43 0.43 0.50 0.45

Denmark Mean 0.50 0.51 12.40 42.75 19.61 0.12 0.15 0.11 0.20 0.11 0.17 5.14 0.46 0.04 0.46 0.03 0.47 0.50 4275

Std. Dev. 0.05 0.50 2.22 11.57 9.94 0.32 0.36 0.32 0.40 0.32 0.45 1.58 0.50 0.19 0.50 0.18 0.80 0.50

Table 3 The Impact of Power on Leisure Time By Country, Gender, and Day of Week United States Women

Men

Weekday Weekend Power -40.84 104.36 * Married -20.38 * 4.88 Education (years) -6.16 *** -3.00 ** Age -12.48 *** -8.89 *** Age Squared/100 17.41 *** 12.39 *** Children age 0-2 -38.61 *** -53.66 *** Children age 3-5 in US, 3-6 in DK -23.75 *** -45.85 *** Children age 6-9 in US, 7-9 in DK 3.34 -21.10 *** Children age 10-14 -17.13 *** -20.58 *** Children age 15-17 -16.46 ** -14.62 * Number of Other Adults -9.56 * -6.04 Unemployment Rate 3.97 -0.39 Winter -0.42 5.25 Spring 17.75 ** -3.89 Summer 1.82 8.31 Holiday 67.25 *** Constant 586.91 *** 529.85 *** Number of Observations R-Squared

4708 0.0655

Denmark

4897 0.0635

Women

Weekday Weekend 193.82 *** -15.16 -60.09 *** -0.28 -9.50 *** -3.48 ** -9.25 *** -17.54 *** 12.37 *** 21.17 *** -38.62 *** -55.40 *** -24.50 *** -35.14 *** -22.07 *** -12.20 -21.66 *** 6.04 -1.53 2.19 -9.93 * -4.06 7.10 ** 0.18 -10.97 18.40 * -9.27 -17.76 * 0.51 10.23 83.31 *** 488.23 *** 804.96 *** 4306 0.0655

4453 0.0514

Men

Weekday Weekend 96.10 127.22 1.56 4.17 -6.00 *** -2.76 -16.33 *** -7.08 * 20.52 *** 8.00 * -14.88 -88.98 *** -26.31 ** -51.43 *** -29.67 ** -21.10 -2.51 -28.64 ** -7.36 10.84 4.37 -21.54 * 4.32 4.40 -6.01 -48.34 * 5.48 -29.27 *** -34.81 * -0.38 -198.08 *** 574.04 *** 533.80 *** 1138 0.0978

1133 0.0875

Asterisks indicate statistical significance: *** significance at the 1% level, ** at the 5% level, and * at the 10% level. The Danish models also include a dummy variable to identify immigrants and a dummy variable to identify those residing in Copenhagen. The US models also include controls for Black, Hispanic, and Asian race/ethnicity; 3 regional dummies; 4 metro status indicators; and 2 year dummies.

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Weekday Weekend 48.54 6.02 -9.90 -9.75 -4.86 * -2.74 -16.68 *** -16.93 *** 19.41 *** 18.01 *** -54.88 *** -99.28 *** -31.73 ** -25.06 -12.43 -35.25 * 2.67 -0.78 -20.84 -28.40 16.80 -16.49 -0.18 -6.22 -8.97 -36.05 -25.06 -33.83 *** -35.81 -13.11 -120.11 664.83 *** 937.16 *** 1008 0.0767

976 0.0734

Table 4 The Impact of Power on Housework Time By Country, Gender, and Day of Week United States Women

Men

Weekday Weekend Power -136.46 *** -50.56 Married 6.34 14.24 Education (years) -5.39 *** -2.67 ** Age 0.54 6.19 *** Age Squared/100 2.73 -5.75 ** Children age 0-2 54.60 *** 3.89 Children age 3-5 in US, 3-6 in DK 28.70 *** 5.84 Children age 6-9 in US, 7-9 in DK 29.21 *** 19.80 *** Children age 10-14 26.92 *** 17.79 *** Children age 15-17 33.93 *** 14.82 * Number of Other Adults 5.51 1.58 Unemployment Rate 3.18 -1.46 Winter 2.41 0.67 Spring 23.02 *** 0.87 Summer 0.99 -2.47 Holiday -40.54 *** Constant 224.88 *** 141.46 ** Number of Observations R-Squared

4708 0.0670

Denmark

4897 0.0386

Women

Weekday Weekend -36.88 -10.43 13.71 16.48 -2.85 *** 2.23 ** -0.93 7.70 *** 2.28 -8.14 *** -2.95 -1.30 6.50 -0.83 -0.39 3.45 -1.63 2.64 -8.89 0.22 0.22 4.87 -0.54 -3.69 -0.58 15.94 ** 8.55 2.10 1.96 -7.27 -26.77 * 140.07 *** -21.80 4306 0.0179

4453 0.0355

Men

Weekday Weekend 72.26 9.22 9.70 -4.55 *** -6.14 *** -2.32 *** -2.24 *** 13.31 6.23 -13.28 *** 39.62 -6.23 *** 14.41 16.71 19.14 13.02 7.66 4.03 20.61 -1.20 *** -1.09 *** -7.32 *** 3.83 -0.91 *** 2.54 6.53 11.57 6.50 -3.45 *** 36.71 -51.28 *** 156.19 -74.75 *** 1138 0.1062

1133 0.0676

Asterisks indicate statistical significance: *** significance at the 1% level, ** at the 5% level, and * at the 10% level. The Danish models also include a dummy variable to identify immigrants and a dummy variable to identify those residing in Copenhagen. The US models also include controls for Black, Hispanic, and Asian race/ethnicity; 3 regional dummies; 4 metro status indicators; and 2 year dummies.

23

Weekday Weekend -78.64 *** -214.96 *** 5.65 14.04 1.44 7.79 -0.45 *** 9.10 1.23 -8.95 *** -1.21 *** 25.93 15.78 9.26 9.21 41.40 1.92 -7.06 *** -5.38 *** 8.96 -15.38 *** -9.06 *** 5.71 2.13 14.30 1.07 27.53 -26.47 *** -10.46 *** -0.35 *** -56.56 *** 87.12 -62.10 *** 1008 0.0260

976 0.0517