Prior research suggests that child support payments from fathers increase ..... since the father was eligible to pay support for each reporting period at each wave,.
Fathers’ Involvement with Their Nonresident Children and Material Hardship
Lenna Nepomnyaschy Rutgers University
Irwin Garfinkel Columbia University
(forthcoming) Social Service Review.
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Abstract Children living in single-parent families, particularly those born to unmarried parents, are at high risk for experiencing material hardship. Previous research based on cross sectional data suggests that father involvement, especially visitation, diminishes hardship. In this paper, we use longitudinal data to examine the associations between fathers’ financial and physical involvement with their nonresident children and material hardship in the mother’s household. In cross sectional models, we find that fathers’ formal and informal child support payments and contact with their children independently reduce the number of hardships in the mother’s household, controlling for other types of involvement and a rich set of covariates; however, only fathers’ contact with children is robust in models including lagged dependent variables or individual fixed effects. Furthermore, cross lagged models suggest that economic hardship decreases future father involvement, while, except for in kind contributions, father involvement does not decrease future hardship. These results suggest that the relationship between father involvement and hardship is more complex than previously thought and that future research should concentrate on heterogeneity of relationships within the population.
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Today, more than one in four children in the U.S. (26%) lives with only one parent (U.S. Census Bureau 2010). Moreover, it is predicted that half of all children born in the last several decades will spend some portion of their childhood in a single parent family (Bumpass and Sweet 1989). Further, 41% of all births today are to unmarried mothers, and that figure is nearly 70% for black mothers (Hamilton, Martin, and Ventura 2009). While some children in single-parent families live with their fathers, the overwhelming majority (84%) live with their mothers and have a living nonresident father (U.S. Census Bureau 2010). Children growing up in singleparent families, particularly those born to unmarried parents, are much more likely to be poor and to experience more material hardships than those in two-parent families (Lerman 2002; DeNavas-Walt, Proctor, and Smith 2008). Consequently, these children also face disadvantage in a number of important domains including health, development, and educational achievement and attainment (McLanahan and Sandefur 1994; Magnuson and Votruba-Drzal 2009). Nonresident fathers’ involvement in their children’s lives, both through their financial contributions and their physical involvement, can potentially ameliorate some of these disadvantages. Prior research suggests that child support payments from fathers increase income and reduce poverty in custodial mothers’ households (Sorensen and Zibman 2000; Meyer and Hu 1999; Bartfeld 2000); however, other research suggests that payments from poor fathers are either too small or inconsistent to improve financial well-being in the mother’s household (Mincy and Sorensen 1998; Cancian and Meyer 2004). Prior research has also found that child support income is associated with a number of positive measures of child well-being, such as cognitive skills, educational attainment, and child behavior (Knox and Bane 1994; Argys et al. 1998; Hernandez, Beller, and Graham 1995; Knox 1996; Graham, Beller, and Hernandez 1994). Unfortunately, only a minority (approximately 20%) of unwed nonresident fathers pay formal
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child support (Nepomnyaschy and Garfinkel 2007). Yet, an overwhelming majority of these fathers are involved with their children in other ways, through informal and in-kind contributions and through regular contact with their children (Nepomnyaschy 2007; Garasky et al. 2009; Waller and Plotnick 2001; Huang 2006; Nepomnyaschy and Garfinkel In press). Much less research has focused on how these other types of contributions of time, money, and goods impact children’s economic circumstances. In this paper, we examine the effects of these different types of father involvement on their children’s experience of material hardship. Though poverty is the most commonly used indicator of serious economic distress, indicators of material hardship--such as going without food, being evicted from one’s home, having heat, electricity or the phone shut-off, or delaying medical care--are now a commonly used alternative and complementary measure (Beverly 2000, 2001). Such indicators of hardship are not only important mediators of the relationship between poverty and child well-being, but have been found to be directly related to child well-being independent of income (Beverly 2001; Gershoff et al. 2007). For example, children who live with food insecurity have worse health, lower cognitive skills, worse academic performance, and more behavior problems than those who do not, after controlling for household income or poverty status (Alaimo et al. 2001; Alaimo, Olson, and Frongillo Jr 2001; Slack and Yoo 2005; Whitaker, Phillips, and Orzol 2006; Rose-Jacobs et al. 2008; Zaslow et al. 2009; Cook et al. 2004; Ashiabi 2005). Other studies point to the deleterious effects of multiple and cumulative measures of hardship on child well-being, after controlling for other indicators of socioeconomic status (Frank et al. 2010; Yoo, Slack, and Holl 2009; Cook et al. 2008; Ashiabi and O'Neal 2007). The next three sections review previous literature, describe our data and methods, and present results.
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How Father Involvement Affects Material Hardship Low income is obviously one principal determinant of material hardship. Though material hardship disproportionately affects children living in poverty, 65 percent of families living between 100 and 200 percent of the poverty threshold have experienced one or more hardships (Bernstein, Boushey, and Brocht 2001; Gershoff 2003). Furthermore, the correlation between material hardship and income and poverty status is weaker than might be expected (Mayer and Jencks 1989; Sullivan, Turner, and Danziger 2008; Short 2005; Cancian and Meyer 2004). 1 There are at least two reasons for the modest correlation. First, current income (the measure on which poverty status is most often based) is not a comprehensive indicator of a family’s economic circumstances. In-kind transfers are not counted as income, nor is wealth or access to credit, all three of which may enable families to avoid hardship during periods of unemployment or other shocks to income (Shapiro and Wolff 2001; Sullivan, Turner, and Danziger 2008). Similarly, as Edin and Lein (1997) show, low-income mothers use a number of survival strategies, such as relying on social programs, friends, family, and underground employment, to avoid hardship, none of which is usually included in income measures. Second, material hardship may result not only from a lack of resources, but also from difficulty managing those resources (Heflin, Corcoran, and Siefert 2007). For example, families in which there are drug and alcohol problems, depression, and other indicators of poor mental health have been found to experience more material hardship, controlling for income and other indicators of socioeconomic status (Sullivan, Turner, and Danziger 2008; Heflin, Corcoran, and Siefert 2007).
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As compared to using poverty to measure family well-being, material hardship is also superior
because it captures effects on the non-poor. 5
Father contributions of time, goods and money can affect both mother’s resources and her ability to manage them.
Nonresident fathers’ material contributions consists of formal cash support (that paid through the formal child support system), informal cash support (cash that is given outside the formal obligation), and non-cash support (in-kind contributions). Edin and Lein (1997) describe the numerous ways in which mothers use contributions from fathers to improve the economic circumstances in their households. Nonresident fathers’ provision of material support to mothers, whether it be through formal or informal cash payments or through in-kind contributions, can directly impact the level of hardship in the mothers’ house, and could be considered as increased income in the household. Cash contributions supplement the mother’s income and can readily be used to pay rent, utility and other bills; and to purchase food, clothing, and other necessities. Fathers’ in-kind contributions can be used directly to reduce hardship (food or clothing) or could allow the mother to reallocate the income she would have spent on those items towards other necessities. Fathers can also reduce hardship by offering to pay rent, utility or telephone bills directly. While fathers’ provision of material support (formal support, informal cash support, and in-kind support) could reduce hardship in the mothers’ household, these different types of support are not interchangeable and could have different impacts on material hardship. (Nepomnyaschy, 2007; Garsky et al. 2009). Formal support, which usually arrives in the mail at regular monthly intervals, may be more stable than informal support allowing the mother to better plan for expenses and to avoid hardships. However, many low-income fathers have difficulty making regular child support payments through the formal system because of high
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levels of unemployment and prior incarceration (Swisher and Waller 2008; Mincy and Sorensen 1998; Geller, Garfinkel, and Western 2008; Cancian and Meyer 2004). Additionally, women on welfare must sign over to the state their rights to formal child support collected on their behalf and in the majority of states receive none of the support provided by fathers (Roberts and Vinson 2004). Finally, fathers who pay informally may have more control over how their payments are spent (Weiss and Willis 1985). Most likely this would reduce hardship, but if the mothers feel compelled to spend on items that are more visible to the father such as clothes, toys, or furniture as opposed to necessities, such as rent or phone bills—hardship could increase. While it is also possible that fathers’ material contributions could increase hardship if their provision of support leads to reduced support from other people in the mothers’ life--such as friends and relatives, or new boyfriends and partners-- the reduction in other support would have to be greater than the support the father provides, which seems highly unlikely. Fathers’ Visitation and Hardship Fathers’ physical contact with their children can also impact material hardship. Regular visits from fathers may constitute a free source of child care and may substitute for paid child care. Regular visits may also allow mothers to spend more time in the labor force, increasing their income. Visitation may make the father more aware of his child’s needs and may induce him to directly help the mother avoid certain hardships. Informal and in-kind support is often provided when fathers come to see the child (Garasky et al. 2009; Nepomnyaschy 2007). Irregular cash or in-kind support of this sort, for example a father pays a utility bill or the rent for one month, is not likely to be captured by either the informal cash support measure or the in-kind measure in the Fragile Families data. Similarly the fathers may loan the mother money. As theorized by Weiss and Willis (1985), a father’s visitation allows him to monitor how money is
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spent in the mother’s household. Thus fathers’ visits can reduce hardship if mothers are induced to use money in ways that improve the well-being of the child. Finally, fathers’ regular visits and involvement with children can reduce a mother’s level of stress and provide a sense of security and stability which may help her to better manage the financial resources that are available to her. On the other hand, fathers’ visitation could also increase hardship. If the parents’ relationship is conflictual or violent, then his visits could increase stress and contribute to greater hardship. Finally, if fathers consume resources (food) while in the household or if they discourage contributions from other sources, such as friends, relatives or the mother’s new boyfriend or partner, there may be greater hardship. In sum, the effects of fathers’ time with children, whether in the mother’s house or in his, could either reduce or increase material hardship in the mother’s household.
Empirical Evidence of the Effects of Fathers on Material Hardship Edin and Lein (1997) in their landmark ethnographic study of the survival strategies of single mothers find that the overwhelming majority of mothers rely on informal support from their networks, particularly from the fathers of their children. Much qualitative research on lowincome single mothers and fathers confirms these findings (Roy 1999; Waller and Plotnick 1999, 2001; Pate 2002; Pate 2006; Heflin, London, and Scott 2009). Additionally, insofar as nonresident fathers’ involvement can be considered an indicator of social support, there is much evidence of the protective effect of social support and social networks on reducing material hardship (Lee, Slack, and Lewis 2004; Mayer and Jencks 1989; Sullivan, Turner, and Danziger 2008)
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There has been little quantitative research, however, focusing on the impact of nonresident fathers’ involvement on material hardship in the mothers’ household. Only two studies that we are aware of examined this question, and in only one was this the specific focus of the study. Lee, Slack, and Lewis (2004), looking at the effects of welfare receipt and work activities on four measures of material hardship among TANF recipients, controlled for mothers’ receipt of informal and formal child support. They found that neither formal nor informal support was significantly associated with rent, utility, or food hardship; however, provision of formal support was significantly associated with lower levels of perceived hardship (a summary scale based on responses to 4 items asking about feelings regarding one’s own financial situation). Garasky and Stewart (2007), examined the effects of nonresident fathers’ involvement (both financial and physical) on three measures of food insecurity in their children’s households. They found that frequent visits (more than once per week) were consistently protective against food insecurity, while provision of child support was only significantly protective against one measure of insecurity. They hypothesize that perhaps fathers make in-kind contributions while they are visiting and that is the mechanism through which fathers’ visits impact hardship. However, they do not directly measure in-kind support, are not able to distinguish between formal and informal cash support, and their indicators of hardship and fathers’ involvement are measured at the same time period. We build on this work by disaggregating financial support from fathers into formal and informal cash support, including in-kind contributions, incorporating temporal ordering by using panel data, employing eight indicators of material hardship, and including a number of mothers’ individual attributes that may impact her ability to avoid hardships, including physical and mental health, impulsivity, cognitive ability, and access to social support.
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Data & Methods This paper uses the Fragile Families and Child Wellbeing Study, a panel study of approximately 4,000 children born to unmarried parents between 1998 and 2000 in 20 large U.S. cities in 15 states. We take advantage of four waves of panel data, starting from baseline, when the children were born, and following them up to age 5. Mothers, and available fathers, were interviewed at the hospital within a few days of the child’s birth, while fathers who were not at the hospital were interviewed elsewhere. Follow-up interviews with both parents were conducted by telephone when the children were approximately ages 1, 3, and 5 years old. The Fragile Families study is representative of births to unmarried parents in the late 1990’s in all U.S. cities with populations of 200,000 or more (please see Reichman et al. 2001 for a detailed description of the study design). Of the unmarried mothers interviewed at baseline, 89%, 86%, and 84% were reinterviewed at the 1, 3, and 5-year waves, respectively. At each wave of interviews, mothers were asked numerous questions pertaining to fathers’ characteristics, providing detailed information about fathers, even if they were not interviewed. The current study relies on mothers’ reports about fathers’ sociodemographic characteristics and involvement with their nonresident children. Although it would be ideal to have fathers’ reports of their involvement with children, fathers were not asked about their child support payments to mothers at the 3 and 5-year interviews. Additionally, though the Fragile Families survey was able to identify and interview a larger proportion of unmarried fathers than
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any other national survey, there are still many fathers who are missing.2 Fathers missing from the data were more likely to be nonresident (the group on whom this study focuses) and were more disadvantaged on socioeconomic characteristics than those who were interviewed (Teitler, Reichman, and Sprachman 2003). Therefore, relying on fathers’ reports could introduce nonresponse bias as well as substantially reducing sample sizes across waves. The sample in the current study consists of mothers who were not cohabiting with the focal child’s father at each follow-up wave (1-yr, 3-yr, or 5-yr), and who were re-interviewed at least at the 1-year survey, though the majority of mothers (69%) had more than one follow-up interview. Stacking the three waves of follow-up data creates an unbalanced panel of 4,469 repeated observations on 2,180 unique mothers. The sample sizes are: 1,373, 1,478, and 1,618 at the 1, 3, and 5-year surveys, respectively. The increasing sample sizes from wave to wave reflect the trend that unmarried parents’ cohabiting relationships are ending over time; however, there is also a small number of mothers who are lost to attrition from wave to wave3. Besides excluding mothers who were cohabiting with the focal father, those who had missing data on variables of 2
At the baseline survey, 75% of eligible unmarried fathers (those who were associated with an
interviewed mother) were interviewed, and their follow-up response rates were 65%, 63%, and 61% at the 1, 3, and 5-year waves, respectively. 3
Of the 3,711 unmarried mothers in the baseline sample, 3,293 were re-interviewed at the 1-year
follow-up. Of these, 50 percent (1,642) were not cohabiting with the father at that follow-up. At the 3-year interview, 3,009 mothers who were unmarried at baseline were re-interviewed. Of these, 58 percent (1,731) were not cohabiting at that point. At the 5-year interview, follow-up interviews were conducted with 2,921 mothers who were unmarried at baseline. Of these, 66 percent (1,934) were not cohabiting at that time.
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interest at each wave were also excluded. Specifically, at the 1-year, 3-year, and 5-year surveys, respectively: 213, 203, and 257 cases were missing on father involvement variables; 14, 19, and 8 cases were missing on hardship variables; and 63, 57, and 59 cases were missing on covariates. These criteria excluded a total of 207 mothers from the sample who had missing observations at every wave. Supplementary analyses based on balanced panel data, where each mother appears in all 3 follow-up waves, are based on a sub-sample of 2,337 observations of 779 unique mothers. Material Hardship Material hardship, the outcome of interest, is measured using a series of questions that are asked in several national surveys, including the Survey of Income and Program Participation (SIPP), the National Survey of America’s Families (NSAF), and the American Housing Survey (AHS) (Beverly 2001). At all three follow-up surveys, mothers were asked: In the past 12 months, did you do any of the following because there wasn’t enough money: (1) receive free food; (2) not pay the full amount of rent or mortgage payment; (3) not pay the full amount of a gas, oil, or electricity bill; (4) have service turned off by the gas or electric company, or the oil not delivered; (5) have phone service disconnected; (6) be evicted from your home or apartment for not paying the rent or mortgage; (7) stay in a shelter, abandoned building, an automobile, or any other place that was not meant for regular housing, even for one night; (8) anyone in your household need to see a doctor or go to the hospital but didn’t go? Our primary measure of material hardship is based on the number of hardships that a family experienced in the past 12 months at each wave. We added the number of yes responses to the measures listed above, creating a variable with a possible range of 0 – 8: 0 indicating no hardships reported and 8 indicating positive responses to all 8 items. However, prior research
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points to the fact that each of these measures of hardship may have different antecedents, different consequences, and may represent very different types of problems (Heflin, Sandberg, and Rafail 2009; Beverly 2000, 2001; Oulette et al. 2004; Rose, Parish, and Yoo 2009). Therefore, we also analyze each hardship indicator separately. Father Involvement Both fathers’ financial and physical involvement with their children are considered in this study. Several types of financial contributions are examined: formal child support, which is that received through an established child support order; informal child support, which is any cash support received from the father outside of a formal order; and in-kind support, which includes clothes, toys, medicine, food, or ‘other’ non-cash support, provided by the father. Formal and informal cash support are measured as continuous variables for the amount of support provided per month since the father was eligible to pay support for each reporting period at each wave, including those who have zero. For formal support, eligibility is defined as the number of months since the parents had a child support order; and for informal support, as the number of months since the father has not lived with the child at each wave (for fathers who never lived with the child, it is the total reporting period at each wave). We choose to create a monthly amount of support received because the figure reported for the past year is conflated with the length of time that a child support order has been in place or how long ago parents stopped cohabiting. For example, two mothers may report $1000 of formal support received in the past year, but one obtained a child support order two months ago, thus receiving $500 per month; while the other mother has had an order for 10 months, thus only receiving $100 per month. The impact of child support on economic circumstances in the mothers’ households will be very different in these two homes, yet using the yearly report of receipt will mask these differences.
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In-kind support is measured as a dichotomous variable (yes/no) and is positive if the mother indicated that in the past year the father has bought clothes, toys, medicine, food, or other ‘often’ or ‘sometimes’ as opposed to ‘rarely’ or ‘never’. Fathers’ physical contact with children is measured as: the number of days that he has seen the child in the month prior to the interview, including those who had zero. Correlations between father involvement variables are highest between in-kind support and days of contact (0.59), days of contact and informal support (0.34), and in-kind and informal support (0.34); and are lowest between formal support and in-kind (0.06) and formal support and days of contact (0.004). The correlation between formal and informal support is negative and statistically significant (-0.07). Covariates We consider three broad categories of covariates: socio-demographic characteristics of mothers, fathers, and children; measures of the father’s commitment to the mother and child at the baseline survey; and indicators of the mother’s ability to avoid hardship. Also included is the unemployment rate in the city of mother’s interview at each wave, entered as a time-varying covariate. The mean rate of unemployment for the pooled sample is 5 percent. Family Socio-demographic Characteristics. - We include both the mother’s and fathers’ race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, or other), education (< H.S., H.S., or > H.S.), age (< 21, 21-29, 30 +), whether the mother is US-born, whether she reported TANF or Food Stamp receipt in the year prior to the child’s birth, whether the father was working in the week prior to the child’s birth, the sex of the child, and whether the child was low birth weight. All these variables are measured at the baseline survey and do not vary over time. We also include a number of time-varying socio-demographic variables. These are measured at each wave of the survey: age of the child (in months); the number of children under 18 and the
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number of adults in the household; whether the mother has a new married or cohabiting partner; and the average monthly household income minus child support received. Many of these variables have been found in prior research to be associated with both hardship and fathers’ involvement with their children. We expect that children of more advantaged mothers will have more involved fathers (because these fathers are also more advantaged) and their mothers will be more likely to avoid hardship. Father’s Commitment to Mother and Child at Baseline. – This set of variables includes: the parents’ relationship at the baseline survey (cohabiting, romantically involved, just friends, or no relationship); whether the father contributed cash or anything else during the pregnancy; whether he visited the mother and child in the hospital; and whether he intended to contribute to the child in the future. Fathers who exhibited more commitment to the mother and child at baseline may be more invested in the child and are more likely to contribute financially and be involved with the child. These fathers may also have selected mothers who are more likely to avoid hardships. Mother’s Ability to Avoid Hardship. - Though many of the previously described variables have been used in prior research as proxies for the mother’s ability to avoid hardship, because of the rich data in the Fragile Families survey, we are able to include explicit measures of such attributes. From the baseline survey, we include the mother’s access to social support4 and 4
Mothers’ access to social support is measured as the sum of the mother’s (yes=1 or no=0)
responses to three questions about whether in the next year, she could count on someone in her family to: (1) Loan her $200; (2) Provide her a place to live; and (3) Help her with babysitting or child care. Possible scores range from 0-3, with higher scores indicating more access to social support. 15
whether she reports excellent health (vs. very good, good, fair or poor). Next, we include: a measure of the mother’s cognitive ability, based on the Revised Wechsler Adult Intelligence Scale (WAIS-R)5; a measure of the mothers’ impulsivity6; and the number of mental health problems that the mother’s mother (focal child’s maternal grandmother) had as reported by the mother.7 These three variables were only measured at the three-year survey; however, because they are assumed to be fixed over time, we treat them as baseline measures. Finally, we include a
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The WAIS-R is an 8-item word similarities test, with possible scores of 0, 1, and 2 for each
item. Scores are summed across the items for a possible range of 0-16, with higher scores indicating better performance.
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The impulsivity scale was based on the mean of mothers’ replies to 6 items with possible
answers from 1 for strongly disagree to 4 for strongly agree (after reverse-coding the replies) The items are: (1) I often say what comes to my head without thinking; (2) Often, I don’t think enough before I act; (3) I often say/do things without thinking of consequences; (4) I often get in trouble because I don’t think before I act; (5) Plans don’t work out because I don’t go over them carefully; (6) I make up my mind before considering the situation from all angles. The range of this measure is 1 to 4, with higher scores indicating more impulsivity. 7
Grandmother’s mental health problem measure is calculated by adding the number of yes
responses across 4 items: (1) Did biological mother ever have periods of depression that lasted 2 weeks or more? (2) Did she have periods of a month or more when she was nervous or anxious? (3) Did she have problems with drinking or drugs? (4) Did she attempt suicide? The range is 0 – 4, with higher scores indicating more problems. 16
a measure of whether the mother reported a drug or alcohol problem at the baseline survey. Prior research has established a strong link between access to social support (particularly the ability to borrow money) and reduced hardship (Lee, Slack, and Lewis 2004; Mayer and Jencks 1989; Sullivan, Turner, and Danziger 2008). Mothers’ physical and mental health and ability have also been previously linked to hardship (Heflin, Corcoran, and Siefert 2007; Sullivan, Turner, and Danziger 2008; Kalil, Seefeldt, and Wang 2002; Danziger et al. 2000); however, this relationship could be potentially endogenous. For example, experiences of material hardship may lead to poor mental health and poor mental health can impact the ability to manage resources. To minimize this specification problem, we use the grandmother’s mental health as an exogenous proxy for mothers’ own mental health. A mother’s current problem with drugs or alcohol may also be endogenous to material hardship; therefore, mothers’ report from baseline is included. Analytic Strategy First, we present descriptive statistics on all the measures described previously for the full sample and disaggregated by whether the mother reported any hardships. Next, we estimate pooled cross-sectional ordinary least squares (OLS) models of the number of hardships in the mother’s household on measures of fathers’ involvement with multiple observations on mothers across waves. We present nested models by first controlling only for socio-demographic characteristics, then adding indicators of fathers’ commitment to the mother and child, and finally adding measures of mothers’ ability to avoid hardships (some of which have not been available in prior work). Standard errors in all models are adjusted for non-independence of observations due to repeated measures across individuals. Selection Bias. - As with all observational studies, there are a number of potential biases that limit our ability to make causal inferences. Unobserved differences between families with
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fathers who pay and visit their children and those who do not may bias the estimated relationship between fathers’ involvement (either financial or physical) with their children and hardship in the mother’s household. In the extreme case, the estimated relationship could be fully attributed to these unobserved differences and there would be no causal relationship between the two. For example, fathers may contribute more (or less) in time and money to a custodial parent who is in poor mental health, has problems with drugs or alcohol, or has low cognitive skills and is not capable of making better choices for her family. We address this potential bias in three ways. First, as discussed previously, we control for many of these characteristics that have been generally unobserved in many prior studies. Second, taking advantage of the panel structure of the Fragile Families data, we include a lagged dependent variable in the OLS model, the number of hardships at the prior wave. Third, we estimate models including individual fixed effects, which only examine effects within individuals. Inclusion of a lagged dependent variable reduces the possibility that fixed unobserved differences are driving the results because these differences should be reflected in the lagged dependent variable. However, effects are still estimated within and between individuals, and therefore unobserved heterogeneity is still possible. Individual fixed effects models, by relying only on changes within individuals, eliminate the possibility that constant unobserved differences between individuals are driving the results, though this method does not address unobserved differences within individuals that change over time. One drawback of fixed effects analysis is that results are estimated only for those individuals whose values on the dependent variable change over time and for those who are observed in the data at least twice. This leads to a less representative sample and one that is substantially reduced in size. Because all non-time-varying characteristics are held constant (within individuals), these regressions only include those variables that change over time.
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In supplementary analyses, we present results based on a balanced panel of observations, which includes only those cases in which the mother was observed in the sample at each wave. This analysis addresses the possibility that the results are being driven by mothers for whom we have the most number of observations, since these mothers contribute the most data. Next, we examine each type of material hardship separately. Because each indicator of material hardship is a dichotomous variable, we estimate pooled cross-sectional logistic regression models and fixed effects logit models. Reverse Causality. - Another potential source of bias is reverse causality, where material hardship in the mothers’ household impacts fathers’ financial or physical involvement. For example, a mother may call on the father for help because she is having financial problems, and he comes to see the child and provides some financial assistance. This would lead to a spurious positive association between fathers’ involvement and hardship, which could offset or dominate the true negative causal effect (if there was one). Reverse causality could also lead to a spurious negative association between involvement and hardship. For example, a mother’s experience of hardship (phone disconnected or eviction) may make it more difficult for the father to visit the child.
One potential way to disentangle the temporal ordering of effects is to measure fathers’
involvement and hardship at the prior wave and to explicitly test whether hardship at the prior wave impacts fathers’ involvement at the current wave and whether involvement at the prior wave impacts hardship at the current wave. We estimate these cross-lagged models within a structural equation modeling (SEM) framework using Mplus software (Version 4). In these models, we use the mean of father involvement at the 1 and 3-year surveys to predict hardship at the 5-year survey; and mean hardships from the 1 and 3-year surveys to predict father involvement at the 5-year survey,
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controlling for baseline characteristics. The advantage of using an SEM framework to explore these relationships is that the reciprocal effects are estimated simultaneously, allowing for the estimation of the effect of earlier father involvement on future hardship over and above its effects on future father involvement and vice versa.
Results Sample Description Outcomes. - Table 1 presents descriptive characteristics of our full sample of mothers with nonmarital births who are not residing with the father of the focal child at the time of each survey. Nearly half (49 percent) of mothers reported at least one hardship of the eight included in these analyses, with an average of 0.99 hardships in the previous year. The most commonly reported hardships were not paying all utility bills owed (27 percent of mothers) and having phone service turned off (23 percent). Less frequently reported hardships were not paying full rent or mortgage payment (15 percent) and receiving free food (12 percent). The least commonly reported hardships were having gas, electricity or water shut off (9 percent), not seeing a doctor or going to the hospital (6 percent), and being evicted or staying in a place not meant for housing (3 percent each). Mothers reporting at least one hardship (2nd column of table 1) reported 2.04 total hardships and much greater likelihoods of each individual hardship. More than half (56 percent) did not pay all utility bills that were due, and 46 percent had phone service shut off. Nearly onethird (30 percent) of these mothers reported not paying all of the rent or mortgage and one quarter reported receiving free food.
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Father Involvement. - Since they’ve lived apart from their children, nearly half of fathers (48 percent) made in-kind contributions. Slightly fewer (42 percent) made informal cash contributions, averaging $53 per month across all fathers, while only 21 percent of fathers made formal payments, averaging $39 per month across all fathers. Not reported in the table is the shift over time from in-kind and informal support to formal child support. As the time from the child’s birth (and the length of time that parents are no longer cohabiting) increases, informal support (which is initially high) declines and formal support (which is initially low) increases. These amounts become approximately equal at 36 months after the child’s birth after which point formal support becomes greater than informal support. (For an analysis of the effects of child support enforcement over tine on informal and formal support, see Nepomnyaschy and Garfinkel In press). Well over half (57 percent) of fathers have seen their children in the past month, with an average of 7.5 days in the past month for all fathers. Children living in families that experienced at least one hardship were less likely to receive in-kind support from fathers (46% vs. 50%), received less informal and formal support per month, and saw their fathers fewer days in the past month (6.9 days vs. 8.1 days) than children living in families with no hardships. These differences were statistically significant. Family Socio-demographic Characteristics. - The mothers in our sample were mostly non-white (64 percent non-Hispanic black and 21 percent Hispanic), had low education (39 percent had not completed high school), were relatively young at the time of the focal child’s birth (38 percent were less than 21 years old), and were mostly U.S.-born (93 percent). Fathers had similar characteristics but were older on average than mothers (80% were 21 or older vs. 62% in this group for mothers). Only 59% of these fathers were reported to have been employed in the week prior to the child’s birth. Nearly half of the mothers (48 percent) were receiving
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either Food Stamps or TANF at the time of the child’s birth, and more than one in ten (12 percent) reported that the focal child was low birth weight (
