Soc Indic Res (2009) 93:147–152 DOI 10.1007/s11205-008-9403-8
Spousal Economic Factors in ATUS Parents’ Time Choices Rachel Connelly Æ Jean Kimmel
Accepted: 1 August 2008 / Published online: 12 December 2008 Ó Springer Science+Business Media B.V. 2008
There remains little consensus regarding the role of that spouses play in parents’ time choices. Although there are theoretical reasons to expect a strong link between a spouse’s economic factors and own non-market time use decisions, the empirical research reveals little such linkage. We focus on three aggregated non-paid time uses: (1) leisure, (2) child care and (3) home production and on two specific spousal economic variables, (1) the spouse’s reported weekly hours of paid work and (2) the relative wage (i.e., the wife’s wage divided by the husband’s wage). The latter spousal factor is particularly important because it has been proposed as a proxy for relative bargaining power within the household. Our findings, using data from the American Time Use Surveys from 2003 and 2004, suggest that spousal economic factors play little role in parents’ non-market time choices except in terms of father’s caregiving time, which is positively related to higher wife’s wages relative to his own on the weekend and to higher wife’s employment hours on weekdays. 1 Previous Literature Time-use research has its origins in traditional studies of labor supply and empirical examination of couples’ time use is no different (Blundell and McCurdy 1999). The couples’ time use research most relevant to ours is found in the household bargaining model literature, in which it is argued that the source of income within a family is an important determinant of consumption patterns, including the consumption of leisure. The relative wage is expected to determine power within the household, possibly due to its relationship to potential income outside the marriage, as in Fortin and Lacroix (1997). R. Connelly (&) Economics Department, Bowdoin College, College Station 9700, Brunswick, ME 04011, USA e-mail:
[email protected] J. Kimmel Economics Department, Western Michigan University, 1903 West Michigan Ave, MS 5330, Kalamazoo, MI 49008, USA J. Kimmel IZA, Bonn, Germany
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There is some empirical evidence regarding bargaining theory in time use research. For example, Hersch and Stratton (1994) show that the share of housework a husband performs in a dual earner couple is related negatively to his share of labor income and to his share of labor market hours. Additionally, Bittman et al. (2003) find that for a wife, the husband’s share of income has a negative impact on her weekly housework time but only up to the point where her share becomes equal. Friedberg and Webb (2006) explicitly link the bargaining model approach to time use research, finding significant but small effects of the relative wage only on TV watching and housecleaning. Our research advances this literature through our (1) separation of weekdays and weekends, (2) use of appropriate instrumentation methodologies to address the potential endogeneity of spousal and own economic factors, and (3) estimation of the parent’s time devoted to three nonmarket time uses jointly using an Seeming Unrelated Regression (SUR) Tobit model.
2 Data Source and Descriptive Statistics Our data come from the 2003 and 2004 years of the American Time Use Survey (ATUS). Our parental samples are comprised of 1,317 weekday father diaries, 1,444 weekend father diaries, 1,284 weekday mother diaries, and 1,454 weekend mother diaries, in households with children age 13 and younger. We utilize the limited spousal data available on the ATUS’ accompanying CPS files on the spouse’s reported usual weekly hours worked for pay and usual weekly earnings. Note that the CPS information refers to employment situations 4 months prior to the ATUS time diary collection. We estimate instrumenting regressions to construct our two spousal economic factors: the relative wage (wife’s wage divided by the husband’s wage) and the spouse’s weekly paid work hours as well as the own wage and own weekly paid work hours. Our three ATUS nonmarket activities include leisure (all leisure activities excluding sleep, grooming, and human capital investment), household production (including all household tasks and the transportation time associated with them) and child care reported as a primary activity. (See Kimmel and Connelly (2007) for the full list of activities included in each category.) On weekdays, mothers report more unpaid work while fathers report more paid work, but the reported work totals including paid work, unpaid household production, and unpaid caregiving are nearly identical, at 611 minutes for fathers and 607 for mothers. Both fathers and mothers report approximately 270 minutes of leisure. The most noticeable difference between weekends and weekdays is that on the weekend, mothers provide less care for their children, but they report more total work minutes than men (377 for fathers versus 425 minutes for mothers).
3 Estimation Methodology Our estimation is based on the underlying theoretical model developed in Kimmel and Connelly (2007) and expanded in Connelly and Kimmel (2008). This utility-maximization model yields three out-of-market time demand equations as denoted below. tij = f ðEjD, SÞfor i ¼ m,f and j ¼ hp, cc, L In the equation above, E denotes economic factors, D denotes demographic factors, and S denotes time/spatial factors. Included in E are the following variables: the individual’s own instrumented wage, the individual’s own instrumented paid weekly work hours, the
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Spousal Economic Factors
149
instrumented relative wage (i.e., the wife’s wage relative to the husband’s wage), the spouse’s instrumented paid work hours, and two child care price instruments, one for children up through age 5 and one for children ages 6 through 12 (estimated using SIPP data and then applied to the ATUS sample). The demographic controls include age, education, race and ethnic dummies (nonwhite, Hispanic), number of children in various ranges, plus a dummy variable for the presence of any other (nonspouse) adult in the household. The time/spatial controls include dummies for survey year, summer diaries, and residence in urban areas or the South. The three time use equations for the mother and the three time use equations for the father must be estimated separately due to the ATUS design of having only one time diary per household.
4 Results Table 1 for mothers and Table 2 for fathers present our empirical results from the estimation of three nonmarket time uses. Our main interest is the effects of the key economic spousal variables of spouse’s predicted weekly work hours and the predicted relative wage of the wife compared to her husband. For mothers, neither spousal variable has any effect on time use on either weekdays or weekends. However, several of the mother’s own economic characteristics do matter, as her own wage increases her caregiving time and decreases her leisure (weekdays only). It is also interesting to note that a mother’s own predicted wage is found to have no significant effect on home production. While other studies have shown that home production declines with earnings, our methodology separates wages from hours worked. Being employed more hours per week does lower her home production time as well as leisure on weekdays, but not on weekends. Table 2 shows the results for fathers. The major finding of this table is that fathers are more affected by their wife’s economic characteristics than vice versa. This is a switch from the findings of Kooreman and Kapteyn (1987), who found using 1970s data that wives were affected by their husbands’ time use but not vice versa. Given the tremendous changes in women’s employment between the timing of these two studies, it is quite credible that being married to a woman whose wage is high relative to one’s own increases the minutes of caregiving that a father performs on the weekend, and that a father whose wife is employed more weekly hours provides more child care time on weekdays and has less leisure. Since higher wage women also spend more of their own time on child care on both weekdays and weekends, our findings imply that high income couples spend more total time on child care and that couples whose incomes are more similar divide their child care time more evenly on weekends. Also notably in Tables 1 and 2, we find no effect of relative wages on household production for mothers or fathers. It is possible that power in the household is determined in ways beyond the survey’s grasp or that power does not affect who does which unpleasant chore or that the aggregate category of home production includes enough pleasant chores to counterbalance the unpleasant ones. Overall, then, using the spouse’s CPS collected variables along with the ATUS time diaries for mothers and fathers whose youngest child at home is under 13 years of age, we find very little evidence of spousal economic factors affecting parent’s non-market time choices except for the effect of the wife’s economic activity on fathers’ caregiving time. Fathers married to women with higher relative wages perform more weekend caregiving and fathers married to women with more usual weekly hours do more weekday caregiving. Not included in the models presented here is spouse’s time in the same non-paid daily activity. This omission is due to the ATUS data problem of having only one time diary per
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3.3915
Predicted price childcare 6–12
3.1623
2003 ATUS
*** Significant 0.01; ** significant 0.05; * significant 0.10
529.1104***
14.3774
Summer time diary
Constant
-6.9783
Presence of other adult
3.3742
30.5657***
17.3596**
Number kids 13–15 years
13.2049
21.7745**
-7.1707
-8.2785
Number kids 6–9 years
Number kids 10–12 years -8.3117
-127.1800*
-7.5814
-30.9757***
-10.7996
319.0413***
-4.3952
1.4478
21.2306
24.5848**
-11.502
7.1514
-4.1356
85.0118*** 22.1975**
-41.9928***
Number kids 0–2 years
Number kids 3–5 years
5.8493
-6.8704
5.9344
-19.3616
222.0348
-327.061
0.4584
3.6229
-3.9265***
0.7353
-22.1420*
21.5028*
3.1497 -2.9189
Southern residence
1.7661
9.7797
2.4906
-62.1794***
Urban residence
Hispanic
7.4855
-153.0299
49.7406
13.2042
Age
-1400.8315***
-0.1102
7.1981***
-1.2993
194.0304***
0.1643
-29.7731
Non-white
1449.4141**
-3.6674
Predicted price childcare 0–5
Education
-2.6222**
Own predicted work hours
-131.0900*
-1.5706
Own predicted ln wage
-26.9011
Relative predicted wage
Husband’s predicted hours
453.1458***
11.6337
20.1579
-22.963
1.0094
-14.1429
-10.2154
-15.511
-37.5106*
7.814
22.5231*
-33.9487*
15.6517
-38.4456
465.0795
7.8735**
0.9013
-0.1906
-82.0728
1.2008
68.6691
Leisure
Home prod’n
Leisure
Child care
Weekends
Weekday
Table 1 Determinants of married mothers non-market time use
-186.5991**
-1.3079
-26.3187**
0.5615
-6.5117
-10.721
17.3607*
21.2411*
94.4315***
13.2891
-3.043
-4.8451
11.2629
101.0482
-219.0065
-6.1155*
4.4313
-1.2064
128.7731*
-0.9327
-65.6514
Child care
261.3194***
-2.3389
4.8345
-15.882
8.143
23.0901**
9.2916
13.0184
13.966
-0.6925
0.9739
10.2508
-22.0924
129.4562
-409.157
2.8536
0.2129
1.3616
37.7931
-1.4854
-102.7985
Home prod’n
150 R. Connelly, J. Kimmel
2.4657
557.2974***
Constant
*** Significant 0.01; ** significant 0.05; * significant 0.10
-8.374
-11.4457
2.6437
0.4844
Num kids 13–15 years
Presence of other adult
Summer time diary
-9.4161
-7.2994
Num kids 10–12 years
2003 ATUS
-1.3512
-4.9384
Num kids 6–9 years
-278.2872***
1.418
-21.0535*
11.6342
19.7226**
98.9324
12.8376
-2.4706
2.1452
-9.2569
-2.9007
6.4778
17.1526
41.1125***
-3.8718
Num kids 3–5 years
-17.0808 15.0575
6.6118
18.6075
-14.3076
-23.0777
146.0178
642.2136
-8.1358**
-4.8124
-0.866
-47.7764
1.4648
-8.334
49.3686***
8.3913
-28.4822*
-2.6007
Num kids 0–2 years
-3.8341
-20.344
-81.2764
-320.55
-3.617
-1.1315
Southern residence
-19.672
Hispanic
20.4305
Urban residence
Nonwhite
-958.7504**
-232.199
Education
Age
-4.0378
Predicted price childcare 6–12
-1.2638
-6.3870**
-5.6979*
Own predicted work hrs
Predicted price childcare 0–5
121.0917**
95.4007
Own predicted ln wage
2.1094**
42.32
3.3454
-1.9751*
Relative predicted wage
Wife’s predicted hours
666.4500***
11.9634
19.6079
8.871
31.2206**
17.0973
-4.0643
-14.7839
0.6127
-28.9008*
-11.6828
-28.574
17.6542
-145.219
1056.4182*
9.4894**
-2.6703
-1.6196
-74.7126
1.7135
-43.2866
Leisure
Home prod’n
Leisure
Child care
Weekends
Weekday
Table 2 Determinants of married fathers non-market time use
-563.6944***
-5.2416
-15.8214
-39.2218*
-24.4847*
-14.8268
24.3650**
20.6639
61.4039***
24.0062
9.7917
-19.6059
-15.9171
40.4387
-166.27
-9.1205**
4.6235
1.2195
156.6699*
-2.0956
103.3210**
Child care
-72.3374
1.108
-16.3606
12.3406
2.4321
-2.6846
6.6267
9.8612
2.572
11.459
-4.22
21.8477
-55.2869***
22.5885
-315.865
1.4022
2.2117
-2.491
117.4774
0.5842
44.9223
Home prod’n
Spousal Economic Factors 151
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household. In ongoing research we develop two statistical methodologies to estimate this potentially important additional spousal variable (Connelly and Kimmel 2008).
References Bittman, M., England, P., Sayer, L., Folbre, N., & Matherson, G. (2003). When does gender trump money? Bargaining and time in household work. American Journal of Sociology, 109(1), 186–214. Blundell, R., & McCurdy, T. (1999). Labor supply: A review of alternative approaches. In O. Ashenfelter & D. Card (Eds.), Handbook for labor economics (Vol. 3A). Amsterdam: Elsevier Science. Connelly, R., & Kimmel, J. (2008). Spousal influences on parents’ non-market time choices. Unpublished manuscript, previous version circulated as IZA working paper No. 2894 (June). Fortin, B., & Lacroix, G. (1997). A test of the unitary and collective models of household labour supply. Economic Journal, 107, 933–955. Friedberg, L., & Webb, A. (2006). The chore wars: Household bargaining and leisure time. Unpublished manuscript (August). Hersch, J., & Stratton, L. (1994). Housework, wages and the division of housework time for employed spouses. American Economics Review, 84(2), 120–125. Kimmel, J., & Connelly, R. (2007). Mothers’ time choices in the United States: Caregiving, leisure, home production and paid work. The Journal of Human Resources, 42(3), 643–681. Kooreman, P., & Kapteyn, A. (1987). A disaggregated analysis of the allocation of time within the household. Journal of Political Economy, 95(2), 223–249.
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