Abstract
This chapter focuses on the extent to which women combine housework with simultaneously minding children. Given that housework can be done along with child caregiving, but presumably at a cost, this characteristic of home production time constitutes another margin in women’s lives where the balancing act of their many roles plays out. After exploring the existing literature and a simple conceptual model, the authors analyze data from the American Time Use Surveys, 2003–2011. The results indicate systematic differences in doing housework alone or with or without children present according to a number of characteristics of women and their households. Women with more minutes in employment that day are more likely to engage in household chores alone and are less likely to have children present while doing housework.
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- 1.
We use the terms “home production” and “housework” interchangeably to refer to doing household chores; it does not refer to child care. The term non-market work encompasses both home production and the care of children.
- 2.
See Connelly and Kimmel (2013) for a detailed summary of the literature on these trends in the United States.
- 3.
An exception is Foster and Kalenkoski (2015) who, using experimental data, examine the effects of multi-tasking on productivity in the context of doing either a household chore or childcare activity only, versus engaging in both activities simultaneously.
- 4.
We do not attempt to establish empirical evidence to support this assumption, however, see Foster and Kalenkoski (2015) for experimental evidence on the negative effect of children’s presence on efficiency in home production.
- 5.
It is widely recognized that the response rate for the ATUS, while higher than for most time use diary surveys, is lower than ideal (approximately 54–58%). Abraham et al. (2006) analyze the pattern of non-response and conclude that it is largely due to failure to contact respondents (as opposed to refusal) which appears to be relatively randomly distributed across the pool of possible respondents. Therefore, meaningful bias due to sample selection is unlikely to be present.
- 6.
The detailed listing of time use designations of the ATUS can be found at the Bureau of Labor Statistics website (www.bls.gov/tus/lexicons.htm).
- 7.
- 8.
We use Stata for all estimations.
- 9.
Because of the complexities of differing functional forms in Eq. (2), we do not allow for the possibility of correlated error terms across time use categories as in, for example, Kalenkoski et al. (2005) and Kimmel and Connelly (2007). If such correlation is present, which is reasonable to assume, not accounting for it reduces the statistical efficiency of Eq. (2), resulting in larger standard errors for the estimated coefficients. However, the estimates maintain the property of unbiasedness. Given that our primary purpose in estimating (2) is to derive unbiased instruments to use in the estimation of (1) rather than to test hypotheses within (2), the loss of efficiency is not a cause for concern.
- 10.
- 11.
Wages are estimated using the Heckman sample selection model. The wage equation includes the following variables that are not included in Eq. (2): age-squared and education-squared, the state unemployment rate, the unemployment rate interacted with the pre-2008 dummy, and an indicator of whether the state minimum wage is higher than the federally mandated minimum wage.
- 12.
As is common in this literature, we treat women’s marital status as exogenous. See Blau and Kahn (2007) for one study that controls statistically for the possible endogeneity of marriage in a model of women’s labor supply and finds that results are generally not sensitive to selection into marriage.
- 13.
Full results for the sub-samples are available upon request.
- 14.
Approximately 10% of observations are missing information on income and, therefore, are dropped. An alternative to dropping these observations would be to use spouse’s earnings to proxy for exogenous income. Because we include unmarried women in the sample, this measure seems more problematic due to the systematic nature of the missing information, and the much larger portion of the sample affected. Nonetheless, we check for sensitivity to this alternative specification. Also, the time gap between household income data (from the CPS), and the data used to calculate women’s labor market earnings (from the ATUS collected several months later), results in the latter being larger than the former for a small percentage of observations. We therefore also estimate two versions of the model, one setting negative values to zero and one treating them as missing. Results are not sensitive to these alternatives; reported results set negative values to zero.
- 15.
The F values for joint significance in the non-market work and leisure equations are 16.39 and 13.35, respectively, and the corresponding chi-squared value for the employment equation is 69.24.
- 16.
We also estimated Eq. (1) using a more limited sample, based on women with children younger than age 13. The results are generally highly consistent across samples, especially with respect to the explanatory variables of greatest interest to us.
- 17.
Simulations are conducted for prototypes based on marital status and education level, and using the modal or mean value within each prototype group for other explanatory variables. Detailed simulation results are available upon request.
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DeGraff, D.S., Centanni, R.M. (2017). Double Shift, Double Balance: Housework in the Presence of Children in the United States. In: Connelly, R., Kongar, E. (eds) Gender and Time Use in a Global Context. Palgrave Macmillan, New York. https://doi.org/10.1057/978-1-137-56837-3_13
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