PAA Poster 2002: Women in the Great Migration - PowerPoint PPT Presentation

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PAA Poster 2002: Women in the Great Migration

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Jennifer Hook, Department of Sociology, University of Washington. Data and Sample ... of gender equality and specific policy configurations influence household labor. ... – PowerPoint PPT presentation

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Title: PAA Poster 2002: Women in the Great Migration


1
The Difference a State Makes Womens Allocation
of Unpaid Work in the 50 States Jennifer Hook,
Department of Sociology, University of Washington
Results
Research Context
Measures
  • There is considerable variation in the amount of
    time women spend on unpaid work across the United
    States. Estimates, based on the 2003 American
    Time Use Survey, range from 22 hours a week in
    Idaho to over 35 hours in Nebraska. Some of this
    variation is explained by differences in
    demographic composition across the states, but
    some of this variation remains unexplained.
  • This figure shows predicted values of womens
    unpaid work time for varying levels of child care
    costs - set at the minimum, mean, and maximum
    observed values, separately for mothers of
    infants, pre-schoolers, and school-aged children.
    All other variables are set at the mean.
  • I model unpaid work time in minutes per day. The
    measure encompasses most forms of unpaid domestic
    work, including child care.

Table 1. Individual - level variables
Table 2. State - level variables
Figure 2. The effect of child care costs.
Figure 1. Womens mean unpaid work time by state
  • In this portion of the project, I examine the
    influence of state-level conditions on womens
    unpaid work time. Theoretical and empirical work
    in cross-national contexts suggests that both
    levels of gender equality and specific policy
    configurations influence household labor.
  • The positive effect of having an infant,
    pre-school, or school-aged child on womens
    unpaid work time is larger in states where the
    cost of child care is a larger percentage of the
    median household income.
  • The negative effect of womens individual
    earnings is less negative where women have more
    political equality.
  • The positive effect of womens work hours is less
    positive where women have more political
    equality.

Results
Table 3. HLM predicting womens unpaid work time
Hypotheses
  • I hypothesize that women will do less unpaid work
    where child care is less expensive and gender
    equality is greater (Hook 2005).
  • I expect the costs of child care to be relevant
    for mothers, particularly mothers of infants and
    pre-school aged children.
  • I further expect levels of gender equality to
    influence the effect of womens earnings and work
    hours. Where gender equality is greater the
    negative effect of womens earnings and of
    womens work hours on unpaid work time should be
    greater (Fuwa 2004).

Conclusions
  • Both state- level gender equality and specific
    policy conditions influence womens unpaid work
    time across the United States. The effects,
    however, are not direct they work through the
    effects of individual-level characteristics
    including parenthood, earnings and work hours.
  • In contrast to cross-national findings, womens
    macro-level earning equality appears unrelated to
    their unpaid work time.
  • Womens political equality is related, but not in
    the hypothesized way for womens individual
    earnings. It appears that in politically unequal
    states, the negative effect of womens earnings
    on their unpaid work time is actually greater,
    suggesting that where equality is low women are
    better able to use their increased earnings to
    reduce their unpaid workload.
  • Future work on this project will explore the
    intersection of paid and unpaid work in the lives
    of American women.

Data and Sample
  • I utilize the American Time Use Survey (2003).
  • I restrict the sample to working age women (ages
    22 to 59) and to states with more than 30
    respondents in this category. I lose Alaska,
    Delaware, the District of Columbia, Hawaii,
    Montana, North Dakota, South Dakota, Vermont, and
    Wyoming. The state-level N ranges from 38
    respondents in Rhode Island to 762 in California
    for a total N of 7,741 at the individual-level
    and 42 at the state-level.

Methods
  • I estimate hierarchical linear models.

Note All education variables, Other race, and
Hispanic are non-significant and omitted from the
table.
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