Gender Effect on Housework Allocation: Evidence from

Spanish Working Couples

Begona Alvarez Daniel Miles∗

Abstract

Empirical evidence from developed countries consistently shows that, despite the

increasing female participation in paid labor, women remain responsible for most of

household duties. The aim of this paper is to investigate the extent to which this

gender-effect explains the unequal distribution of housework between working spouses

in Spanish. Data come from the Work Situation and Time Use Survey carried out by

the Spanish Instituto de la Mujer in 1991. We model housework allocation between

spouses assuming wives’ and husbands’ housework times are generated by a bivariate

negative binomial distribution, conditional on a set of observable characteristics, such

as paid labor conditions, education or the presence of children at home. To go further

the gender-effect, we carry out estimations that amount to an Oaxaca decomposition

performed on the proposed bivariate specification. Our results highlight the lack of

symmetry in partners’ housework structures. This suggests that an important part of

the division of labor between spouses is independent of the differences in their observable

characteristics and that it depends on gender specific effects.

∗Depto. de Economia Aplicada. Universidade de Vigo. Lagoas Marcosende s/n. 36200 Vigo (Ponteve-

dra). Spain. E-mail: alvarez@uvigo.es

1

1. INTRODUCTION

There is a widespread belief, at least in developed countries, that traditional gender roles

division have dramatically changed in the last quarter of the twentieth century. The higher

educational levels attained by most members of Western countries, the increasing female

labour force participation, the diminishing wage gap, the impact of non discriminatory or

positive discrimination policies, or the presence of women in every stage of social activity

supports this belief. However, empirical evidence suggests that changes in traditional gender

roles division at home are still insignificant (Hartmann, 1981; Van der Lippen and Sieger,

1994; Bittman and Pixley, 1997).

Empirical findings show that, in most Western countries, working women spend about

20-30 hours per week in housework, whilst working men spend less than a half that amount

of time, i.e. 6-14 weekly hours (e.g. Gronau, 1977, Juster and Strafford, 1991, Hersch

and Stratton, 1996). In addition, the observed increase in husbands’ share of housework is

usually the result of a total reduction in the time couples engage in housework activities,

due to women’s reduction in housework time, rather than to men’s increase in domestic

work time. Therefore, married working women continue to be in an unbalanced situation

in which they still bear most of the household duties and husbands seldom increase their

hours of housework to help compensate (Bittman and Matheson, 1996).

In general, the challenge for economic research on this issue is to determine whether the

differences between male and female housework time can be explained by a common model

of economic behavior, in which differences in paid labor conditions and other forces lead to

differences in the allocation on housework time.

From the theoretical side, human-capital models consider differential of spouses’ produc-

tivity in the production of household commodity determines the couple’s allocation of time

between paid work and housework (Becker, 1981). From this point of view, women will have

higher domestic skills and capacity to take responsibility for housework. Alternatively, bar-

gaining models have recognized that intrahousehold time allocation reflects power relations

and strategic interactions in households, e.g. a power element is the market wage of each

2

partner (McElroy and Hourney, 1981; Mahoney, 1995). In terms of traditional labour mod-

els, wife’s decision to work is taken conditionally on the husband being working, i.e. the

couple faces a two-stage decision process. As a consequence, wife’s labour market hours are

a fully divisible good, while those of the husband are indivisible. Hence, is the wife who

adjusts market hours to housework needs.

From the empirical side, different specifications had been followed to characterize house-

work allocation between the spouses. A first alternative is to focus on the share on house-

work of one of the partners. However, as Hersch and Stratton (1994) pointed out, changes

in the husband’s share do not identify whether it is a result of a change in his housework

time or from a change in his wife’s time. A second alternative is to focus on the housework

time conditional means for wives’ and husbands’ separately, assuming interrelation between

decisions are due to unobservable factors, e.g. correlation of error terms (e.g. Hersch and

Stratton, 1994 and Van der Lippe and Siegers, 1994). However, findings in empirical re-

searching do not offer too much evidence on the relevance of economic related variables on

spouses’ housework allocation (Juster and Stratton, 1991).

In this paper we are concerned with studying some empirical regularities on housework

time allocation for Spanish working couples. Characterizing empirical regularities is funda-

mental for drawing inference for theoretical models and for the discussion of policy issues

(Manski, 2000). In particular, our goal consist of determining to which extent gender con-

tributes to explain the asymmetric distribution of housework between spouses.In contrast

to previous work, we characterize the joint decision process of housework time allocation in

terms of its probability distribution. That is, we model the husband’s and wife’s housework

hours allocation in terms of a bivariate probability distribution. The advantage of this ap-

proach are, first, the possibility of characterizing every point on the housework allocation

bivariate support, no only the conditional mean of each of the spouses separately. Second,

the joint modelisation of housework allocation by means of a bivariate count data process

implicity takes into account the interdependence of spouses’ decisions, which is something

that has been widely claimed in theoretical models.

We find that the probability of an equal distribution of housework hours between working

3

couples is very small, conditional on actual characteristics. There is a high probability that

wives bear mostly all of the house duties.

In order to isolate gender-effects in housework allocation, we perform estimations that

amount to an Oaxaca decomposition applied on a bivariate count data model. These calcu-

lations reveal that assymmetries in wives’ and husbands’ burden of housework are mainly

explained by the way household members value male and female observed characteristics,

while differences in such characteristics seem to matter less. Thus, if the domestic prices

paid to women characteristics are replaced by those paid to husbands, then there is a sig-

nificant increase in the probability of an equitable distribution of housework as well as an

overall reduction in time allocated on unpaid activities.

The paper is divided in four sections. In section two we discuss the sample selection and

we briefly describe the data. In section three we present the estimation of the bivariate

probability model. Section four analyzes how gender effects affect housework allocation.

2. DATA

The data used in this paper was obtained from the 1991 Work Situation and Time Use

Survey (WSTUS), carried out by the Spanish Women’s Institute (Ministry of Labour and

Social Affairs). The original target of this survey was to recover information to allow a com-

parison between male and female performance in paid and unpaid activities. For reducing

as much the unobserved heterogeneity, the sample design was focused to retain representa-

tiveness of sectors and occupations where men and women have similar participation rates.

The total sample size of the survey is of 2,054 employees, from which 1,049 are women and

1,005 are men.

The WSTUS offers information on socio-demographic and economic characteristics as well

as the allocation of time between paid and unpaid work. In this paper, and following Hersch

and Stratton (1994), we restrict the analysis to married couples in which both members are

in the labor market. The reasons behind this sample selection are first, to compare spouses

in similar conditions and, second, to minimize reported housework time inconsistencies that

4

may arise from the tendency of any task to fill the amount of time available.

The variable of interest is the average number of hours per day spent in housework, which

is obtained as response to the question: “About how many hours do you (and your spouse)

spend on housework in an average day?” The individual responds for both him/herself and

her/his spouse. The question explicitly excludes child care time. The final subsample we

use in our study comprehends 559 couples.

Table 1 presents mean values of housework time (in hours) and standard deviations

for the couples in our sample. For the sake of comparison, we also include descriptive

statistics corresponding to one-earner couples. Consistent with other studies, there are

large disparities in time spent on housework between husbands and wives. Overall, the

husbands average about 1.2 hour per day, nearly eight hours a week, on housework while

the wives average 4.5 hour per day, about 25 hours per week. This differential persists when

subdividing couples in terms of their labour participation.

Insert Table 1

We observe that mis-reporting of wives’ housework times by their husbands does not

appear to be a significant problem1, however there are significant differences among average

husband’s times reported by themselves and those reported by their wives. Figures 1a-1b

display these differences.

Insert Figures 1a-1b

From these figures it seems as if husbands overstate their housework dedication.

Nonetheless, the raw comparison of men and women in terms of housework may overstate

the effect of gender since men and women in the labour force may not be comparable in

terms of acquired human capital or paid labor conditions. In order to make comparisons,

we have to correct for the effect of these observed characteristics. In Table 2 we present

the means and deviations of the main variables that could help to explain the allocation

of hours on housework. We also show the average hours on housework on the cells defined

by discrete variables or the correlation between those variables which are continuous and

1Hersch and Stratton (1996) also find the irrelevance of misreporting wives’ times by their husbands.

5

housework hours. The selection of this variables was according to previous theoretical and

empirical papers.

Insert Table 2

In first place, it is usually accepted that wives dedicate more time on housework partly

because they earn less, on average, on market activities than their husbands. In our sample,

the mean female/male wage ratio is about 0.72 -e.g. working wives earn 30% less than

their husbands- which is in accordance with Spanish official figures for 1991 (see also Blau

and Kahn, 2000). Market wages represent the opportunity cost of housework, implying

an inverse relation between time on unpaid and paid works. Therefore, we could expect

that market wage increase would negatively affect housework time, basically women’s time.

What it is not clear is the effect of own wage on the spouse’s housework time.

In second place, the hours in market activities should negatively affect the time spent

in house duties, given that it affects the time constraint. In Table 2, we observe that men

and women in our sample are quite similar in this respect, thus men work, on average, 3

hours more than women per week. Also, the correlation between hours at home and at the

market is negative for both spouses. Clearly, leisure time is more unevenly distributed and

hides an underlying pattern of systematic housework overload on employed women (Jacobs

and Gerson, 1998).

In third place, other variables affecting the time dedicated to house duties could be

related to age, education or children, as well as the fact of living in the south or north

of the country. Observe that men and women in our sample do not differ significantly

with respect to education, particularly at a higher level. It is commonly accepted that

schooling and age (through experience) raise marginal productivity in both market and

non-market activities. But these variables are also related to expectations and attitudes

that condition the acceptance of gender roles at home. In this sense, it is expected that

younger and highly educated couples would exhibit a more equal division of paid labor

and housework resulting from either an increase on husbands’ contribution or a decrease

in their wives’. Also, although the question on housework explicitly excludes child care

6

time, it is unlikely that respondents deducted from total time spent on housework some

additional work created by children, such as extra laundry, cooking and cleaning (Hersch

and Stratton, 1996). To allow for of this possibility, children enter the specification through

three variables indicating the number of sons/daughters under age 3, aged 4-14 and aged

15 or more. At last, regional dummy variables were included and of household help (hired

or from relatives) are presented.

Finally, there are several variables which do not appear in our final model although

they were initially included. Among these are the occupation or the degree of individual’s

responsibility at job. We found the effects of these variables to be insignificant in our initial

specification of the model. Since the addition of each variable reduces the sample size due

to missing values, we decided to exclude them from the analysis without compromising the

integrity of our theoretical framework.

In the next section we present the bivariate econometric model we use to estimate this

allocation.

3. ECONOMETRIC MODEL

3.1. A bivariate model

Let the data observed for household i be {(Hwi, Hhi,Xwi, Xh,i)} , for i = 1, ...N and

where Hji, j = w,h, denotes the number of hours spent on housework by the wife and the

husband, respectively, whileXji is a (kj×1) random vector of explanatory variables. Notice,in first place, that housework hours can be described in terms of count data processes, e.g.

non-negativity, discreteness and assume only integers values. In second place, hours on

housework by wife and husband are jointly determined, conditional on the explanatory

variables. That is, a bivariate count data process is needed to characterize the probability

distribution of housework time.

Estimation of multivariate count data processes is not usual in applied economic literature

(see Cameron and Trivedi 1998; Gurmu and Elder 1998). Recent applications are based on

Poisson bivariate models, although this distribution suffers the same equidispersion prob-

7

lems as the univariate Poisson process (see Winkelmann, 1997; Jung and Winkelmann,

1993 or King 1989). Gorieroux et al. (1984) suggested a more flexible Poisson specification

which break with the equidispersion assumption. However, an empirical problem with this

method is found in the second step variance covariance matrix, which is commonly not pos-

itive definite (see Cameron and Trivedi 1998). In this paper, we apply a bivariate negative

binomial model, given that, on the one hand, it allows a much more flexible approximation

to overdisperion and, on the other, it includes the other cases as particular cases. Recent

applications of multivariate negative binomial are Gurmu and Elder (2000) develop semi-

parametric estimations methods for multivariate models of health care utilization; Miles

(2001) models the number of purchases of different sorts of bread using a trivariate negative

binomial specification; and Bauer et al. (1999) analyze workplace accidents using bivariate

count data models. In this paper we follow the models developed by Arbous and Kerrich

(1951) and Marshall and Olkin (1990)2.

Before considering the estimation of the bivariate model, we had tested the correlation

between Hwi,Hhi. In order to test for zero correlation between the counts, we had imple-

mented the conditional moment test proposed by Cameron and Trivedi (1993) which is

based on the idea that a joint probability distribution function factorizes into a product of

marginals, which in turn can be expressed as orthogonal polynomial sequences. The test of

independence requires to test for zero correlation between all pairs of orthonormal polyno-

mials. Results show that zero interdependence can be rejected at a 5 % significance level

(Table 3).

Insert Table 3

To model the bivariate hours at housework, we followed the approach of Marshall and

Olkin (1990). Consider the count dependent variables are Poisson distributed which respec-

tive parameters

λji = λjiui j = w,h

where ui denotes the unobserved heterogeneity component that generalizes the Poisson

2For a complete description of the model see Cameron and Trivedi, 1998 or Miles, 2000.

8

distribution to allow for overdispersion. Assuming ui is gamma distributed with shape

parameter α and scale parameter τ = 1, it can be shown that the mixture bivariate density

has negative binomial marginals and joint distribution given by

Pr(hwi, hhi | λwi,λhi,α) = Γ(hwi + hhi + α)

hwi!hhi!Γ(α)

µλwi

λwi + λhi + 1

¶hwi µ λhiλwi + λhi + 1

¶hhi×µ

1

λwi + λhi + 1

¶α

.

Parametrization of these models follows what is usual in empirical literature, by assuming,

λji = exp³xji

0βj´, j = w,h, i = 1, ..., n (Lawless, 1987).

3.2 Estimation results

As stated before, the main target of this paper is to discuss empirical regularities of Span-

ish housework allocation. As a consequence, our interest is on the probabilities of observing

different allocations of hours on housework between husbands´and wives´. However, to

obtain the predicted probability we previously need to estimate the bivariate negative bi-

nomial model. In this section we briefly describe the estimation results of the bivariate

model.

In Figure 2 we present the observed and predicted marginal densities of the housework

hours by husbands and wives. Observe that the husbands’ marginals are much more concen-

trated to the left than the wife’s marginals. That is, there is a significantly higher probability

to observe a husband working zero or one hour at home than observing a woman working

the same time, when ignoring interrelations between spouses.

Insert Figure 2

In addition, the fitness of the model to the observed frequency is not too bad. Despite

some discrepancies, the model reproduces rather well the behaviour of spouses observed in

the original data.

In Table 4 we present the estimated parameters for the bivariate negative binomial model.

Insert Table 4

9

From an overall view of the results from the table we infer that they coincide with what

would be intuitively expected: for husbands, what basically determines the amount of hours

is its identity, its cultural background -there are not too many significant variables-, and

this finding is similar to the conclusions of Hersch and Stratton (1996). For wives, their

educational level as well as the labour market characteristics-number of hours and hourly

wages- play a special role in determining the amount of time devoted to housework.

Considering some particular parameter estimates, observe, first, the incidence of educa-

tion in the time spent on house duties. These coefficients highlight the lack of symmetry

between male and female housework structures. Estimations show that the lower the wife’s

educational level, the higher the amount of housework she provides and the lower the house-

work provided by her husband. However, the only significant effect of men’s education is the

increase in wife’s housework observed in couples in which the husband has less than primary

school education. Therefore, the expected movement of more educated couples towards an

egalitarian housework distribution is mainly due to a decrease in wife’s housework time but

not to an increase in husband’s time.

In the second place, we find a significant inverse relation between those variables defining

the employment characteristics -working hours per day and hourly wage- and the allocation

of hours on housework activities. Considering these variables separately, the increase in

working hours per day has a slightly higher negative impact for husbands’ than for wives.

The impact of changes in hourly wages on hours at home duties is similar for both, husbands

and wives. This fact could be explain by the characteristics of the sample, which tries to

diminish the labour heterogeneity of the individuals sampled.

Observe also that neither the husband nor the wife is significantly affected by spouse’s

working time, though its effect is positive. Furthermore, own wage reduces the number of

hours spent on housework. The effect is slightly higher for husbands. Estimations however

reveal that housework allocation decisions are independent of the earnings of partners, which

has been previously shown in literature (Maasen and Groot, 1996).

In third place, estimations show a significant effect of the presence of children on wives’

housework. In particular, the presence of pre-school children and children aged 15 or more

10

increases significantly the time wives spend on housework. Consistently with other studies

(e.g. Kooreman and Kapteyn, 1987) we do not obtain a significant effect of these variables

on husbands’ housework. This finding suggests that it is women who afford extra domestic

tasks -other than specific child care- generated by children.

In fourth place, a considerable negative impact on time spent on housework is the presence

of any sort of domestic help. More precisely, the number of housework hours spent by

husbands in households with domestic help fall by approximately one third, while wives’

housework hours in those households fall by one fifth with respect other households without

this sort of help.

Finally, the dummy variable recalling the hours dedicated by the other spouse on house-

work reflects an important husbands overstating, while is positive but insignificant for

women. That is, husbands then to declare they dedicate much more hours in housework

than they really do.

In the next section we analyze try to characterize the probability of different allocations

of housework hours between spouses.

4. GENDER EFFECTS ON HOUSEWORK ALLOCATION

What is the probability of spouses halving domestic duties? Or, stated in another way,

what is the probability of an egalitarian distribution of housework hours between spouses?

Are women characteristics the ones that define the unbalanced distribution of housework

duties? Or is it the value household members give to this characteristics that explains

these differences? In this section we will try to answer this questions based on the bivariate

probability distribution estimated in the last section. In particular, we are interested in

analyzing to which extent eliminating gender specific differences would lead to role-changes

towards an egalitarian distribution of housework between spouses.

Before discussing the points stated above, we present in Table 5 the housework hours

predicted probabilities derived from the bivariate distribution estimated in the last section.

The predictions are based on

11

Pr(hw, hh | xw, xh) = 1n

nXi=1

Pr(Hw = hw,Hh = hh | λwi, λhi, α)

where hw, hh = 1, ...8 or more, λwi = exp(x0wiβw), λhi = exp(x0hiβh) are the conditional

means for wife and husband respectively, and βw, βh are the maximum likelihood coefficient

estimates obtained in the last section. We will call this prediction the original situation. In

what follows we omit the reference of the fact that we are making predictions conditional

on husbands’ and wives’ characteristics.

Insert Table 5

In the first place, observe that the higher predicted probability is given in the situation where

the husband works one hour per day in house duties while its wife works 2-3 hours per day.

In the second place, the joint probability of a husband houseworking two or less hours while

his wife is working four or less amounts to nearly the 50% of the total joint distribution.

Finally, looking at the marginal densities, the probability of a husband working at most

two hours a day is nearly 80 percent, e.g. 4 of each 5 husbands work two hours per day or

less on house duties. For the case of wives to accumulate the same marginal distribution we

should go up until 5 hours per day on housework. That is, the predicted probability of the

original situation suggest that the probability of finding a household where spouses evenly

share housework is negligible.

In order to study the allocation of hours between spouses we have considered three mea-

sures for the probability of this allocation. First, the egalitarian distribution of housework,

which is given by the diagonal elements of the table above, i.e. the probability that wife

and husband dedicate the same amount of hours on housework, Pr(h, h | xw, xh). Second,the wife’s exploitation, which is measured by the lower diagonal shows the probability that

a wife bears more housework than its husband, Pr(hw, hh | xw, xh, hw > hh). Third, the

husband’s exploitation, which is Pr(hw, hh | xw, xh, hh > hw). This measures are summa-

rized in Table 8. Observed that, for the original situation, there is a 0.14 probability of

finding an egalitarian housework distribution, i.e. one of every ten household in our sample

12

tend to share their house duties; on the other hand, in 7 of every 10 household, housework

is responsibility of wives- there is a probability equal to 0.73 of wife exploitation.

In order to identify the reasons that explain these differences in housework allocation,

we carry out an empirical exercise that is in the spirit of Oaxaca (1973)-Blinder (1973)

decomposition. Our modification accounts for the idiosyncratic nature of housework data

by analyzing difference in the probability distribution of counts, following Belman and

Heywood (1990).

According to this methodology, there two broad sources of gender differences on house-

work allocation: one due to differences in observable characteristics: education, age -

experience-, market wages, etc.. The second is related to the different weights assigned

to these observable characteristics on the determination of the dependent variable. When

studying gender market wage discrimination, these weights, which are the value of the esti-

mated parameters that determine the wage for each gender, are associated to the price the

market pays for each of these observable characteristics. In our case, unpaid work, these

weights can be understood as a the value the household members assign to the character-

istics in terms of the determination of housework hours, i.e. we call them domestic prices.

Therefore, in what follows we study whether different in housework allocation could be

explain by observable characteristics and or domestic price.

In the first place, to approximate the effects of the observable characteristics on housework

allocation we built the predictions from the bivariate negative binomial specification but

sustituting the husbands characteristics by those of his wife,

Pr(hw, hh | xw, xw) = 1n

nXi=1

Pr(Hw = hw,Hh = hh | λwwi, λhwi, α)

where λwwi = exp(x0wiβw), λhwi = exp(x0wiβh) are predicted using wives characteristics

and leaving βw and βh, are wives’ and husbands’ maximum likelihood coefficient estimates

obtained in the last section, i.e. the domestic prices are left unchanged. This prediction is

presented in Table 6.

Insert Table 6

Observe that the probabilities in Table 6 are very similar to those in Table 5. That is, when

13

using wife’s characteristics for both members of the marriage and use the corresponding

domestic prices for each member, the probability distribution does not significantly changes

with respect to the original situation. In particular, the egalitarian distribution as well as

the wife exploitation situation, as observe from Table 8, remains practically the same as

in the original situation. Therefore, it seems as if wife observable characteristics do not

explain the differences in housework allocation, a similar conclusion to that presented by

Juster and Sttraton (1991) in a different setting.

For taking into account the effect of domestic prices on housework allocation, we predicted

the joint probability assigning the husband’s domestic prices to his wife. The predicted

probabilities in this case are obtained from

Pr(hw, hh | xw, xw) = 1n

nXi=1

Pr(Hw = hw,Hh = hh | λ∗wwi, λhwi, α)

where λ∗wwi = exp(x0wiβh), λhwi = exp(x0wiβh), e.g. characteristics are those of the wife’s

and estimated parameters are those of the husband’s. The predictions are in Table 7, where

we can observe that the probability distribution has changed significantly with respect to

the original situation.

Insert Table 7

Observe from the table above that there has been a significant increase of the probability

in the diagonal of the distribution. This means an increase of the proportion of households

with an egalitarian allocation of housework. In addition, the off diagonal probabilities

are much more uniformly distributed, meaning a similar probability of finding a husband

working more hours than his wife or viceversa. Finally, observe that the housework hours

have diminished in probability for both members, i.e. there is higher probability for zero,

one or two housework hours. This suggests that there is a more egalitarian situation with

a reduction on total hours dedicated to housework.

The discussion of this last paragraph is summarized in Table 8, where we present the

three measures of allocation described before, and Figure 3 we present the probability of

14

the egalitarian housework allocation in each of the situations discussed above.

Insert Table 8

First, observe from Table 8 that the original situation significantly changes only in the case

where we value the wife’s characteristics with the husband’s domestic prices, i.e. when the

household members value the wife’s characteristics as those of her husband when analyzing

the allocation of hours on housework. Second, observe from Figure 3 that, in this case, there

as an increase in the probability of halving domestic duties between spouses but also, the

total hours allocated for housework diminishes. It seems as if working women are pushing

towards a more egalitarian distribution of house duties by diminishing the number of hours

engaged in this activity.

Insert Figure 3

Therefore, what the result above suggest is that a more egalitarian situation on housework

allocation will be attained if the way household member value wives characteristics changes.

In other terms, an important factor in housework allocation is the acceptance of gender

roles on part of individuals, which is intimately related to values and normative views of

people and their social network, i.e. conservative values that support traditional gender

roles division are expected to rise among aged people and people with lower educational

attainments. Similar findings are presented by Juster and Sttraton (1991) or Bittman and

Matheson (1996).

This result have important implications on social policies targeting the attitudes of men,

given that there is no expectation that men will assume the domestic burdens of women.

What is needed is a redirection of policies towards the reduction of women’s unpaid work

and of inducing a change of values within the household.

15

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17

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18

TABLE 1 : Average Hours of Housework Per Day and Husbands’ Share (standarddeviations in brackets)

Average value Husband’s Number of

Sample Wives Husbands share observations

Total 4.543 1.259 0.229 782

(3.341) (1.552) (0.221)

Working husband and 7.863 0.863 0.110 198

not working wife (4.051) (1.483) (0.181)

Working wife and 3.760 1.920 0.326 25

not working husband (1.786) (1.631) (0.247)

Both spouses working 3.402 1.370 0.267 559

(2.110) (1.547) (0.218)

19

TABLE 2 : Descriptive Statistics of Explanatory Variables

*Mean/**Correlation

Mean Std Wife’s housework Husband’s housework

Age 37.8 8.08 0.07** -0.04**

Number of children

no children 0.27 0.46 2.89* 1.42*

0-3 years 0.25 0.48 3.50* 1.00*

4-14 years 0.31 0.57 3.71* 1.82*

>15 years 0.47 0.96 4.01* 1.45*

Educational level

primary, wife 0.37 0.48 3.94* 1.26*

universitary, wife 0.35 0.48 2.84* 1.36*

primary, husband 0.33 0.47 3.96* 1.30*

universitary, husband 0.35 0.47 3.05* 1.41*

Household help

yes 0.42 0.49 2.97* 1.10*

no 0.58 0.49 3.72* 1.56*

Working hours per day

wife 38.13 8.46 -0.09** -0.002**

husband 41.24 8.72 0.02** -0.11**

Hourly wage

wife 0.84 0.57 -0.03** -0.01**

husband 1.04 0.55 -0.04** -0.01**

Region

South 0.08 0.28 3.02* 1.59*

other 0.92 0.28 3.44* 1.35*

Respondent

wife 0.60 0.49 3.36* 1.17*

husband 0.40 0.49 3.48* 1.67*

20

TABLE 3 : Independence Tests

Distribution Polynomial order

j=1, k=1 j=1, k=2 j=2, k=1 j=2, k=2

Poisson 6.68 2.51 3.43 2.32

Negative binomial 6.69 2.99 4.50 3.63

Note: The test statistic is asymtotically χ2(1) distributed; j, k denote the polynomial

order corresponding to HM and HF , respectively.

21

TABLE 4: Bivariate Negative Binomial Estimations

Husbands Wives

Coefficient Standard Coefficient Standard

error error

Const. -1.014 0.549 -0.865 0.382

Age -0.034 0.083 0.031 0.040

Number of children

0-3 years 0.074 0.088 0.142 0.048

>15 years 0.070 0.055 0.098 0.029

Educational level

universitary 0.165 0.127 -0.201 0.060

Spouse’s educational level

primary -0.199 0.130 0.132 0.062

universitary -0.097 0.123 0.065 0.066

Household help -0.313 0.108 -0.207 0.055

Working hours per day -0.083 0.032 -0.066 0.015

Spouse’s working hours per day 0.009 0.034 0.018 0.012

Hourly wage (in miles) -0.315 0.175 -0.314 0.107

Hourly wage2 (in miles) 0.044 0.022 0.044 0.014

Spouse’s hourly wage -0.028 0.114 -0.049 0.051

Living in the South (Andalucia) 0.154 0.163 -0.265 0.087

Anwered by spouse -0.269 0.097 0.032 0.051

1/δ 13.25 3.75

log-lik -1966.20

22

TABLE 5 : Estimated Distribution of Hours of Housework

Husband

Wife 0 1 2 3 4 5 6 7 8+ Marg.

0 0.021 0.020 0.011 0.004 0.002 0.000 0.000 0.000 0.000 0.059

1 0.047 0.048 0.028 0.012 0.005 0.001 0.000 0.000 0.000 0.142

2 0.058 0.063 0.039 0.018 0.007 0.003 0.001 0.000 0.000 0.190

3 0.052 0.061 0.041 0.020 0.008 0.003 0.001 0.000 0.000 0.187

4 0.039 0.049 0.034 0.018 0.008 0.003 0.001 0.000 0.000 0.152

5 0.026 0.034 0.025 0.014 0.006 0.003 0.001 0.000 0.000 0.108

6 0.015 0.021 0.016 0.009 0.004 0.002 0.001 0.000 0.000 0.070

7 0.008 0.012 0.010 0.006 0.003 0.001 0.001 0.000 0.000 0.042

8+ 0.009 0.014 0.012 0.008 0.004 0.002 0.001 0.000 0.000 0.050

Marg. 0.275 0.323 0.217 0.110 0.047 0.018 0.007 0.002 0.001 1.000

23

TABLE 6 : Hypothetical Distribution of Hours of Housework Equalizing ObservableAttributes and Weights

Husband

Wife 0 1 2 3 4 5 6 7 8+ Marg.

0 0.056 0.064 0.041 0.020 0.008 0.003 0.001 0.000 0.001 0.192

1 0.073 0.092 0.065 0.034 0.015 0.006 0.002 0.001 0.000 0.287

2 0.053 0.073 0.057 0.032 0.015 0.006 0.002 0.001 0.001 0.240

3 0.028 0.043 0.036 0.022 0.011 0.005 0.002 0.001 0.000 0.148

4 0.012 0.021 0.019 0.012 0.007 0.003 0.001 0.001 0.000 0.076

5 0.005 0.009 0.008 0.006 0.003 0.002 0.001 0.000 0.000 0.034

6 0.002 0.003 0.003 0.003 0.002 0.001 0.000 0.000 0.000 0.014

7 0.001 0.001 0.001 0.001 0.001 0.000 0.000 0.000 0.000 0.005

8 0.000 0.001 0.001 0.001 0.000 0.000 0.000 0.000 0.000 0.003

Marg. 0.230 0.306 0.231 0.130 0.062 0.026 0.010 0.004 0.002 1.000

24

TABLE 7: Hypothetical Distribution of Hours of Housework Equalizing ObservableAttributes

Husband

Wife 0 1 2 3 4 5 6 7 8+ Marg.

0 0.018 0.020 0.012 0.006 0.002 0.001 0.000 0.000 0.000 0.059

1 0.040 0.047 0.031 0.015 0.006 0.002 0.001 0.000 0.000 0.142

2 0.049 0.061 0.043 0.022 0.010 0.004 0.001 0.000 0.000 0.190

3 0.044 0.058 0.043 0.024 0.011 0.004 0.002 0.001 0.000 0.187

4 0.032 0.046 0.036 0.021 0.010 0.004 0.002 0.001 0.000 0.152

5 0.021 0.032 0.026 0.016 0.008 0.003 0.001 0.001 0.000 0.108

6 0.012 0.020 0.017 0.011 0.006 0.003 0.001 0.000 0.000 0.070

7 0.007 0.011 0.010 0.007 0.004 0.002 0.001 0.000 0.000 0.042

8+ 0.007 0.012 0.012 0.009 0.005 0.003 0.001 0.001 0.000 0.050

Marg. 0.230 0.306 0.231 0.130 0.062 0.026 0.010 0.004 0.001 0.999

25

TABLE 8 : Gender Effect on Housework Distribution

Original estimates Female base Gender effect

(1) (2) (2)-(1)

βw = βw;βh = β

hβw = β

h;βh = β

h

Yw=Yh 0.140 0.146 0.236 0.090

Yw>Yh 0.726 0.693 0.423 -0.270

Yw<Yh 0.134 0.161 0.341 0.180

26

FIGURE 1.A: HOUSEWORK TIME USE (HUSBANDS)

0

5

10

15

20

25

30

35

40

45

0 1 2 3 4 5 6 7 8 9 10+

Hours

% o

f hus

band

s

Reported by husbands Reported by wives

FIGURE 1.B: HOUSEWORK TIME (WIVES)

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10+

Hours

% o

f wiv

es

Reported by wives Reported by husbands

0 1 2 3 4 5 6 7 8 9

Hours per Day

0.0

0.1

0.2

0.3

0.4

Pred

icte

d Pr

obab

ility

Predicted wife's marginal frequency

Predicted husband's marginal frequency

Figure 2Observed and Predicted Housework Hours Marginal Frequencies

Observed husband's marginal frequency

Observed wife's marginal frequency

0 2 4 6 8 10 12 14

Hours per Day

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

Pred

icte

d Pr

obab

ility

(2)

Note:(1): Prediction with original coefficients and characteristics(2):Prediction with original coefficients and imputing wife's characteristics to both spouses(3):The same as (2) but imputing husband's coefficients to both spouses

Figure 3

Gender effects on Equal Allocation of Housework Hours

(3)

(1)