schneider, daniel, sara mclanahan, and kristen harknett ... · child’s age-year source:...

© The Russell Sage Foundation

To download additional chapters in this book, please go to:https://www.russellsage.org/children-great-recession

Schneider, Daniel, Sara McLanahan, and Kristen Harknett. 2016. “Parents’ Relation-ships.” In Children of the Great Recession, edited by Irwin Garfinkel, Sara McLanahan, and Christopher Wimer. New York: The Russell Sage Foundation.

https://www.russellsage.org/children-great-recession

Chapter 5

Parents’ RelationshipsDaniel Schneider, Sara McLanahan,

and Kristen Harknett

In previous chapters, we saw that the Great Recession generated a good deal of economic upheaval in the lives of families with young children.

Transfers from the government and family members helped stem some suffering but did not fully make up for the recession’s economic effects. These economic effects, in turn, are likely to have spilled over into other areas of family life. This topic is the focus of the rest of the volume. One of the ways economic upheaval can affect families is by generating fam-ily stress, which may in turn destabilize some relationships and lower the quality of those that remain intact. In this chapter, we examine both out-comes. We focus on two domains: relationship status—whether the mother is living alone or with a partner—and relationship quality—how support-ive mothers and their partners are of one another as well as the overall quality of their relationship. These domains are critical to understanding family and child well-being, given the wealth of research documenting the importance of stable, supportive, high-quality parent relationships on children’s well-being and eventual life chances.

Specifically, this chapter focuses on three questions: Did high levels of unemployment during the Great Recession reduce the likelihood that a mother was married or living with a partner? Did high levels of unemploy-ment during the Great Recession reduce the quality of parental relationships? If so, did these effects differ by mothers’ education? Our goal throughout is to understand whether the high levels of unemployment generated by the Great Recession spilled over to affect the relationships between parents of young children—one mechanism through which poor macroeconomic conditions might eventually compromise children’s development.

Like the previous chapters, we begin by describing trajectories of parents’ relationship status and quality over the nine-year follow-up period. Our goal here is primarily descriptive—to establish whether parents’ relation-ships change much over time and how these patterns may differ by social class background. For relationship status, we examine variation over time and across education groups in whether a mother is living with a partner (child’s biological father or a new partner) or no partner. For relationship quality, we examine the relationship between either biological mothers and

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fathers or mothers and their new partners. We then estimate the effects of the Great Recession on relationship status and quality. We find that the recession led to modest declines in two-parent families, and some declines in relationship supportiveness and the overall quality of mother-father rela-tionships. These declines are most pronounced among families in which the mother has less than a college education.

RECESSIONS AND ROMANTIC RELATIONSHIPS

A large body of work dating back to the turn of the twentieth century shows that more people get married when macroeconomic conditions are favor-able.1 Studies spanning the 1970s, 1980s, and 1990s find that unfavorable economic conditions lower rates of marriage, whereas favorable conditions raise marriage rates.2 Why would this be the case? In general, people are likely to feel more secure entering into a lasting commitment such as marriage when they feel secure about their economic fortunes. Marriage can also be costly, making such unions more likely when families’ budgets are not strained.

A few studies examine the effects of more recent economic downturns, including the Great Recession, and tend to support the idea that negative macroeconomic conditions suppress the likelihood that couples marry.3 These studies, however, tend to average results for parents and nonparents, making them less useful for assessing effects on children. In this chapter, we focus on parents with children, which allows us to assess how the Great Recession affected the living arrangements and relationship contexts in which children are raised.

Of course, poor macroeconomic conditions may cause couples to end relationships as much as they dissuade couples from entering them. A second set of studies thus examines the association between macro-economic conditions and divorce. Here the evidence is more mixed, reflect-ing the offsetting theoretical effects recessions have.4 On the one hand, job loss and economic hardship are expected to create financial strain and marital conflict, which should increase the breakup of existing relationships; on the other hand, economic hardship makes it more difficult for couples to afford the legal fees associated with divorce and the costs of establishing separate households, which should work in the opposite direction. In the late 1800s and early 1900s, divorce rates were lower during recessions, sug-gesting that the costs of divorce outweighed the stress associated with finan-cial hardship.5 In the post–World War II period, divorce rates have been higher during hard times, a phenomenon attributed to the declining costs of divorce and the increasing generosity of welfare state benefits.6 However, the most recent studies of unemployment and divorce tend to find that higher unemployment is associated with a decline (or at least a delay) in divorce.7 For example, a recent study using census data finds the expected negative effect of state-level unemployment on the divorce rate.8 Another

120 children of the great recession

study finds no association between divorce and state-level economic condi-tions, but does suggest a reduction in divorce during the Great Recession relative to before the recession.9 As with studies of marriage, the studies of the macro economy and divorce typically combine parents and non-parents and, with one exception, average results across several decades.10 Thus, these studies do not tell us how the Great Recession affected parental relationships and children’s family settings.

A third set of studies focuses on how economic conditions impact mari-tal and relationship quality. Studies dating to the Great Depression show that job loss lowers marital quality.11 The family stress model, which is based on studies of the Great Depression and the 1980s farm crisis, argues that economic crises lead to reductions in marital quality by increasing per-ceived financial strain, depression, and hostility and reducing warmth and emotional supportiveness.12 Other studies show that economic strain is associated with decreases in partner supportiveness and increase in intimate partner violence.13 In addition to increasing financial strain and depres-sion (as described in the family stress model), poor macroeconomic condi-tions may also reduce marital quality by undermining men’s economic role in the family in the family. Both Shirley Hatchett and her colleagues and Richard Patterson attribute conflict and distrust among African American couples to black men’s attempt to seize authority to compensate for their weak economic position in the family.14 A similar pattern was observed among white families during the Great Depression.15

In sum, both theory and previous research give us reason to expect that the economic shock of the Great Recession may have affected parents’ rela-tionship status and quality. In the case of relationship status, the net effects are ambiguous because the recession could have reduced new partnerships, but either destabilized other couples or inhibited them from separating because of the cost of divorce. In the case of relationship quality, we expect to find deterioration during economic upheaval. Our analysis weighs in on these general questions, focusing on adults with children and the house-hold settings in which children are raised. We are also attentive to how the effects of macroeconomic conditions vary across education groups and thus contribute to class stratification.

TRENDS IN RELATIONSHIP STATUS AND QUALITY

We present information about the trends in relationship status and quality in the nine-year follow-up period over which Fragile Families parents were interviewed. The initial waves of the survey took place in the early 2000s, and the year nine wave often coincided with the Great Recession. The descriptive patterns we present in figures 5.1 through 5.5 are useful for providing a broad backdrop before turning to whether the Great Recession led to changes in relationship status and quality.


Figure 5.1 shows the distribution of mothers across three types of rela-tionship status. About 77 percent were married to or cohabiting with their child’s biological father one year after the child’s birth, declining to 56 percent by the time the child was nine years old. Two percent were living with a new partner one year after the birth of the child, increasing to about 16 percent by the time the child was nine years old. The proportion who were single—that is, not in a coresidential romantic relationship—increases from 21 percent at year one to 28 percent at year nine.

The next two figures (figures 5.2 and 5.3) show mothers’ relationship status over time by her educational background. Figure 5.2 shows the share of mothers married to either the child’s biological father or a new partner at each year. The marriage gap across education groups is large: college-educated mothers are the most likely to be married one year after their child’s birth (about 97 percent), whereas mothers with less than a high school diploma are the least likely to be married (about 35 percent). These gaps persist over the next eight years. College-educated mothers show somewhat larger declines in marriage and the least-educated mothers show slight increases. Nevertheless, the marriage gap between college-educated and less-educated mothers remains substantial by the time their children are nine years old.

Figure 5.3 shows the share of mothers married or cohabiting with either the biological father of the focal child or a new partner. As before, educa-tion differences in the share of mothers living with a partner during the first nine years of their children’s lives are stark and persistent. College-educated

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Figure 5.1 Mothers’ Relationship Status


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mothers are nearly all living with partners one year after their child’s birth, though a downward trend over time is evident. Mothers with less education are less likely to be married or cohabiting one year after the birth, and also experience a slight downward trajectory. Significantly, although mothers with some college education are somewhat more likely to be married or cohabiting than their less-educated counterparts, there is very little differ-ence in the experience of mothers without a high school diploma and those with only a diploma.

The next set of figures examines parents’ reports of the supportive-ness of their spouse or partner, as well as overall relationship quality. Supportiveness is estimated based on each parent’s reports of a partner’s behavior with regard to six domains: fairness and willingness to compro-mise; expression of affection or love; insults and criticism (reverse coded); encouragement and helpfulness; listening when partner needs someone to talk to; and perceptions that the other really understands one’s hurts and joys. Quality is measured by asking parents to rate the overall quality of their relationship, which ranges from poor to excellent. This second ques-tion is asked irrespective of whether parents live together or apart (for the wording of the questions, see the appendix).

Figure 5.4 plots trajectories for mothers’ reports of biological fathers’ supportiveness. This figure is based on biological parents who are living


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together and makes it clear that mothers’ perceptions of fathers’ support-iveness are quite positive and remain steady over time. Overall, and in comparison with the results for relationship status, differences in reports of supportiveness across education groups are small. This is also true when we look at fathers’ reports of mothers’ supportiveness (figure 5.5), and at mothers’ reports of a new partner’s supportiveness (figure 5.6).

Figure 5.7, which presents mother’s assessments of relationship qual-ity with their child’s biological father for coresident couples, shows that more-educated mothers report higher quality relationships than less-educated mothers. No pronounced trend is evident, but overall relation-ship quality declined slightly between when children were one and nine years old for all education groups. Most of the decline for those with less than a college education occurred between when the child was ages one and three. Patterns were similar for biological fathers’ reports about overall relationship quality with the mother (figure 5.8).

In short, college-educated parents are much more likely to be mar-ried and report slightly higher quality relationships with their partners than less-educated parents. In the next section, we turn to the question of how the Great Recession affected marriage, cohabitation, and rela-tionship quality.


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EFFECTS OF THE GREAT RECESSION ON RELATIONSHIP STATUS AND QUALITY

We follow the approach of the previous chapters and examine the relation-ship between area-level unemployment rates (averaged over the year prior to interview) and parents’ relationship status and quality. As in the previ-ous chapters, we use our model to predict relationship status and quality, given unemployment rates of 5 percent and 10 percent. We treat the dif-ference in predicted values as the “effect of large recessions.”

relationship status

We begin by looking at the effect of large recessions on mothers’ relation-ship status. Figure 5.9 examines changes in the probability that mothers are married (left two columns) or married or cohabiting (right two col-umns) assuming unemployment rates of 5 percent and 10 percent. These estimates are derived from regression models described in the appendix. The full regression estimates for mothers married or cohabiting with father or new partner are presented in appendix table 5.A1. We do not distinguish between mothers’ relationships with biological father and new partner in

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figure 5.9, but supplementary analyses (not shown here) indicate that doing so does not alter the results. Considering only marriage (left two bars), 39 percent of mothers are predicted to be married when unemployment is relatively low, whereas 37 percent are predicted to be married when unem-ployment is twice as high, representing a 5 percent decrease in marriage. The difference is not statistically significant. In contrast, when we include cohabiting unions, the proportional gap is larger (61.3 percent at 5 percent unemployment and 57.5 percent at 10 percent unemployment), and the 7 percent difference in statistically significant. These results suggest that poor economic conditions do reduce coresidential partnerships. Whether this difference is a result of fewer new partnerships, more breakups among existing partnerships, or both is a question we return to later in the chapter.

Next we consider whether these effects are broadly shared across fami-lies with different class backgrounds. Figure 5.10 shows the effects of large recessions on the share of women in a marital relationship by educa-tion. Here, we see that mothers with some postsecondary education but no college degree are less likely to be married when unemployment rates are high. In contrast, large recessions have no effect on marital status for mothers with a college degree or those with a high school diploma or less. Interestingly, although the differences between groups are not statistically significant, the negative effects of high rates of unemployment are most pronounced among mothers with some postsecondary education but no college degree. This finding is similar to results reported for several of the economic outcomes in the previous chapters, suggesting these families may be particularly compromised by a big recession.

Figure 5.11 shows similar predictions for the share of women in a married or cohabiting union. For all education groups combined, recessions reduce

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Figure 5.11 Mothers’ Marriage or Cohabitation (Bio Father or New Partner)

coresidential unions, and the effect is significant. Women without a college education are less likely to be in a coresidential union when unemploy-ment rates are high than when they are low. Once again, college-educated women are actually more likely to be in a union when unemployment rates are high, but the effect is not statistically significantly different from zero. Notice that the negative effect of high unemployment on the status of less-educated mothers (high school diploma or less) is more pronounced


when we consider cohabitation in addition to marriage. This difference reflects the fact that cohabiting unions are much more common among less-educated mothers, and these groups are apparently more sensitive to variation in economic conditions. This finding is also true for the eco-nomic well-being outcomes reported in chapter 2.

These analyses tell us that high levels of unemployment reduce marriage and cohabitation among women with less than a college degree. However, they do not tell us whether the differences in relationship status are due to increases in a mother’s chances of ending a relationship with the biological father or decreases in her chances of entering a relationship with the father or a new partner. To further investigate these processes, we estimate a set of models on the effects of unemployment on the probability that a mother would end her relationship with the biological father. We also estimate models that look at the effects of unemployment on the probability that a mother would enter a relationship with the child’s father or a new partner. To examine dissolution, we focus on mothers who were living with the bio-logical father at the time of the previous interview. To estimate entrances, we focus on mothers not living with a father or new partner at the time of the previous interview. The supplementary analyses suggest that the effects of major recession on changes in relationship status are driven by a combi-nation of small increases in dissolution and small decreases in relationship formation during bad economic times. Although none of these estimates are statistically distinguishable from zero, they suggest that the net results are driven by two distinct forces.

relationship Quality

In the next set of analyses, we look at the effects of large recessions on relationship quality among parents. We begin by looking at biological parents’ reports about how their coresidential partners treat them. These analyses are restricted to biological parents who are living together, either married or cohabiting.

According to mothers, the typical biological father is very supportive. When we look at all mothers combined, fathers’ supportive behavior is not particularly sensitive to increases in unemployment rates (figure 5.12). The overall null result masks some underlying differences across education groups. Mothers with a high school diploma report declines in fathers’ supportiveness as a result of large recessions, whereas mothers with some postsecondary education and mothers with a college degree report slight increases in supportiveness. Recall that the supportiveness scale ranges from 0 (never) to 2 (often) based on a set of six supportive behaviors, and that the average mother reports a value of around 1.6 on the scale. This set of figures display a truncated scale to aid in visualizing differences across groups and economic conditions.


As shown in figure 5.13, fathers also report high levels of support from mothers, though here we see a more general decline in supportiveness when unemployment rates are high (10 percent). For fathers, recessionary conditions increase inequality in supportiveness across education groups. Men living with mothers who have less than a college education see a drop in supportiveness, and their counterparts see an increase.16

Figure 5.14 shows the effects of recessions on mothers’ reports of sup-port from new partners. Overall, supportiveness from new partners is

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Source: Authors’ calculations based on Fragile Families and Child Wellbeing Study data.Note: Chow tests shows that the coefficient for unemployment for college is different from the coefficient for unemployment for the less than high school group. **p < .01; *p < .05; †p < .1

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high, even slightly higher than reports of supportiveness from fathers. Looking at mothers as a whole, we find that high unemployment is asso-ciated with small increases in partners’ supportiveness. When we look at the evidence by education, we see that the increase in partners’ support-iveness is concentrated among mothers with less than a college degree. For mothers with a college degree, major increases in unemployment are associated with large declines in new partners’ supportive behavior. The decline in support from new partners reported by college-educated mothers is the only case in which families with a college-educated mother appear to be more negatively affected than other mothers by poor eco-nomic conditions. In all other analyses, these families report stability or improvement in their relationships under recessionary conditions, but their less-educated counterparts report modest declines. However, this result is based on an extremely small sample size—just sixty-three observations.

Figures 5.15 and 5.16 focus on coresident biological parents’ assess-ments of overall relationship quality. Looking first at mothers’ assessments (figure 5.15), we find that large recessions lead to small increases in rela-tionship quality among mothers in all education groups.

Looking next at fathers’ assessments of the overall quality of their relationship with their child’s mother (figure 5.16), fathers report lower relationship quality when unemployment rates are high, with one excep-tion: if the mother has a college degree, fathers report higher relationship quality. We also reestimate these relationships, broadening our focus to include mothers’ reports of all fathers of focal children and fathers’ reports

Source: Authors’ calculations based on Fragile Families and Child Wellbeing Study data.Note: Chow tests show that the coefficient for unemployment for college is different than the coefficient for unemployment for the less than high school group. †p < .1

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of all mothers of focal children, whether or not they were romantically coresident. We find substantively similar results.

These analyses of relationship quality assume that unemployment rates had the same type of effect on relationship quality in the early 2000s they had during the Great Recession. In separate analyses, we relax this assumption (see table 5.A3). We look instead at whether the effects of unemployment were more pronounced during periods of unusually high unemployment, such as occurred during the Great Recession. We find that unemployment rates characteristic of the Great Recession led to

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larger declines in mothers’ reports of fathers’ supportiveness and fathers’ reports of the quality of his relationship with the mother. In contrast, the effect of unemployment on marriage and cohabitation was weaker during the last part of the decade.

How quickly area-level unemployment rates are deteriorating (or improv-ing) may better capture the sense of economic unease or uncertainty felt by households than the prevailing level of unemployment. To test this idea, spline models distinguish between percentage decline in annual unemploy-ment rates and percentage increase in annual rates (table 5.A2). For relation-ship status and quality, we observe few significant effects of rapidly changing rates. The only exception is fathers’ reports about their relationship with their child’s mother. For this outcome, fathers in the two lowest educa-tion groups—those with less than a high school diploma and those with a high school diploma only—report additional declines in relationship qual-ity. Although deteriorating economic conditions did not have much effect on relationship supportiveness and overall relationship quality, the recession may nevertheless have increased undesirable relationship behaviors such as being violent or controlling. Other research using the Fragile Families study finds just that—that an increase in the unemployment rate is associated with increases in men’s controlling behavior toward their female partners.17

SUMMARY AND CONCLUSION

A large body of research dating to the turn of the twentieth century shows that marriage rates are positively associated with favorable macroeconomic conditions. Further, studies of the Great Depression indicate that job loss lowered marital quality by increasing financial strain and reducing warmth and emotional supportiveness.18 We contribute to this body of research by examining the effects of unemployment on the status and quality of parental relationships during the Great Recession.

Focusing first on relationship status, we find that high rates of unemploy-ment reduce marriage and cohabitation among mothers with less than a college degree. In contrast, for college-educated mothers, the chances of marriage are not affected by high unemployment. Indeed, college-educated women are slightly more likely to be living with a partner (married or cohab-iting) in difficult economic times. Our analyses of relationship status reveals a wide marriage gap between mothers with a college education and their counterparts with less education. Mothers with a college degree are far more likely to be married to or living with a partner than their less-educated counterparts in good or bad economic times. Although the relationship changes brought about by the Great Recession were modest, the recession widened already large marriage gaps between families with college-educated mothers and those with less-educated mothers.

We find some evidence that unemployment rates on the order of mag-nitude of those during the Great Recession reduce relationship quality


for select social class groups. Biological fathers, for example, are likely to have less support from mothers and to see the overall quality of their relationship with the mother of their child decline during periods of high unemployment. If the mother has a college degree, however, she offers more support during hard times.

A large literature in recent years argues that economic stability is a pre-requisite for stable marriages and that economic distress has a destabilizing effect. Evidence from the Great Depression suggests that the period had major repercussions for couples and families whose incomes dropped pre-cipitously. Given the magnitude of the shock of the Great Recession, we might have expected to observe sizable increases in relationship instability or relationship distress and conflict. Instead, our estimates suggest modest negative effects on relationship status overall, and somewhat larger negative effects on relationship status for mothers in the middle education groups. On balance, the Great Recession tended to destabilize relationships or fore-stall relationship entry more so than it forced couples to stay together. It also tended to lower the quality of relationships slightly.

APPENDIX

Measures

We examine two measures of mother’s romantic relationship status. First we construct a measure of whether the mother is married to either the focal child’s father or a new partner at the time of the interview. Second we construct a measure of whether the mother is either married to or cohabiting with the focal child’s father or a new partner at the time of the interview.

Our relationship supportiveness measure is based on six items: partner is fair and willing to compromise when you have a disagreement, expresses affec-tion or love for you, insults or criticizes you or your ideas (reverse coded), encourages or helps you to do things that are important to you, listens to you when you need someone to talk to, and really understands your hurts and joys. Response categories were 0 = never, 1 = sometimes, and 2 = often. We sum these measures and divide by the number of items answered to construct our measure, so the resulting scale ranges from 0 = never for all six items to 2 = often for all six items. We first examine reports of supportiveness from mothers, who report on fathers with whom they are currently in romantic coresidential relationships or on new partners with whom they are currently in romantic coresidential relationships. We then examine reports of support-iveness from fathers, who report on mothers with whom they are currently in romantic coresidential relationships.

We construct a measure of overall relationship quality based on mothers’ and fathers’ report of their relationship with the focal child’s other parent


on a 5-point scale. Relationships with a score of 0 are poor and those with a score of 4 are excellent. We limit our analysis of this measure to biological parents who are currently in coresidential romantic relationships.

Key independent Variable

For each analysis, the unemployment rate is a measure of the average unemployment rate in the sample city over the twelve months before the interview. This is calculated to match the period preceding the out-come measures.

Key Moderating Variables

We study differences in the trajectories over time, and in the effects of the Great Recession, on relationship status and quality stratified by maternal education at baseline. Mother’s education is coded as less than a high school diploma or the completion of a GED, a high school diploma, some college or an associate’s degree or technical degree, or a bachelor’s degree or greater.

control Variables

We include a number of covariates in our models, all measured at the first survey wave (baseline). These include mother’s age at the birth, immigrant status (foreign born), number of children in the household, a measure of whether the mother was living with both biological parents at age fifteen, as well as city (twenty dummies for each sample city) and survey year fixed effects (twelve calendar year dummies). In analyses of relationship support-iveness and overall relationship quality, we control for whether parents were married at the time the focal child was born.

Method

The figures that plot the trajectories of each outcome measure over time present the mean levels of each outcome at each survey wave. All means are weighted with the wave-specific city-weights to be representative of births in the twenty study cities; the sample is restricted to mothers who are interviewed in all survey waves.

To study the effects of the Great Recession, we conduct logistic regres-sions for binary outcomes and ordinary least squares regression analyses using the pooled data (waves 2 through 5). The standard errors are clus-tered at both the city and individual level to account for within city and within person clustering–nonindependence. Analyses are conducted for all mothers and separately for mothers with less than high school, high school only, some college, or college degree or greater. We estimated pooled models and also a parallel set of models with mother fixed effects.


To predict the effects of the Great Recession, we estimate the predicted probability (for binary outcomes) or the predicted level (for the contin-uous variables) when the unemployment rate is set at 5 percent, a rate typical of the period before the recession, and compare these predictions with when the unemployment rate is set to 10 percent, a rate typical of the Great Recession. We predict different probabilities for each level of mother’s education.

suppleMental analyses

We conduct a number of additional analyses to test the association between the unemployment rate and parents’ relationships. First, to test whether the speed of change in the unemployment rate was related to our outcomes, we run spline models to distinguish between the percentage decline in annual unemployment rate and the percentage increase in annual unemployment rates (table 5.A2). For relationship status, we observe few significant effects of rapidly changing rates, and the negative effects of unemployment levels on status remained largely unchanged and significant. We also find little evidence that rapidly worsening unemployment rates affected mother’s perceptions of supportiveness of either fathers or new partners. In contrast, rapidly worsen-ing rates lowered fathers’ reports of the quality of his relationship with child’s mothers but only when mothers had a high school degree or less education.

Second, we estimate a set of models that include individual-level mea-sures of mother’s and partner’s employment status (table 5.A3). In gen-eral, we find few significant effects in the models with mother fixed effects. The exception is that fathers report better overall relationship quality with coresident mothers when she is unemployed, but worse quality when he is not working.

Third, we run analyses that include an interaction term with the unem-ployment rate and the year nine wave of data collection to test whether the association between unemployment and the outcomes of interest differed during the Great Recession (table 5.A3). We find three significant interac-tions: one for relationship status and two for relationship quality. For rela-tionship status, the effects of unemployment were less negative during the Great Recession; for mother reports of father supportiveness and fathers’ assessment of overall relationship quality, however, the effects were more negative during the Great Recession.

Finally, we estimate our preferred model stratified by race-ethnicity and by marital status at birth rather than by education (table 5.A4). Few pat-terns in these results are consistent. One interesting exception is father’s reports of mother’s supportiveness and overall quality of relationship with mother. For those outcomes, we find significant negative subgroup effects for men in romantic coresidential relationships with Hispanic mothers and men who were cohabiting at the birth of the focal child.


Table 5.A1 Full Regression Results, Married to or Cohabiting with Father or New Partner

With Individual Fixed Effects

Without Individual Fixed Effects

Unemployment rate -0.056† (0.034) -0.043* (0.019)Education Less than high school — (.) -1.188*** (0.133) High school — (.) -1.079*** (0.108) Some college — (.) -0.998*** (0.116)Mother’s age — (.) 0.006 (0.004)Race-ethnicity Black — (.) -1.127*** (0.070) Hispanic — (.) -0.502*** (0.084) Other — (.) -0.675*** (0.144)Immigrant — (.) 0.732*** (0.147)Children in household — (.) 0.016 (0.017)Lived with both parents at age fifteen — (.) 0.241*** (0.059)Interview year 2000 0.327 (0.210) 0.379* (0.154) 2001 0.025 (0.156) 0.020 (0.143) 2002 0.009 (0.194) 0.101 (0.170) 2003 -0.095 (0.188) -0.067 (0.130) 2004 -0.041 (0.195) 0.053 (0.166) 2005 -0.303 (0.186) -0.190 (0.139) 2006 -0.490 (0.539) -0.478 (0.296) 2007 -0.802** (0.245) -0.447*** (0.103) 2008 -0.206 (0.192) -0.034 (0.157) 2009 -0.144 (0.225) -0.099 (0.157) 2010 -0.304 (0.366) -0.583* (0.286)

(Table continues on p. 138.)


City Austin — (.) -0.143*** (0.030) Baltimore — (.) -0.008 (0.100) Detroit — (.) -0.120 (0.094) Newark — (.) -0.000 (0.081) Philadelphia — (.) -0.055 (0.096) Richmond — (.) -0.263* (0.106) Corpus Christi — (.) 0.183* (0.081) Indianapolis — (.) -0.123 (0.082) Milwaukee — (.) 0.049 (0.078) New York — (.) 0.085 (0.062) San Jose — (.) 0.085 (0.066) Boston — (.) -0.356*** (0.072) Nashville — (.) -0.079 (0.081) Chicago — (.) 0.356*** (0.079) Jacksonville — (.) 0.127 (0.082) Toledo — (.) 0.008 (0.088) San Antonio — (.) 0.111 (0.071) Pittsburgh — (.) -0.373*** (0.086) Norfolk — (.) 0.118 (0.085)Constant 2.200*** (0.201)Observations 7,187 15,855Number of individuals 1,951 4,603

Source: Authors’ calculations based on Fragile Families and Child Wellbeing Study data.Note: Z-stats in parentheses. Covariates are measured at the baseline survey (except year) and are clustered at city and individual level. Model 1 includes level unemployment rate. The model without individual fixed effects is clustered at city and individual level.***p < .001; **p < .01; *p < .05; †p < .1

Table 5.A1 Continued

With Individual Fixed Effects

Without Individual Fixed Effects

Tabl

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(0.0

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(0.0

28)

(0.0

13)

(0.0

20)

(0.0

25)

(0.0

24)

(0.0

32)

In

crea

sing

un

empl

oym

ent

rate

-0.0

04-0

.010

*-0

.010

†0.

007

-0.0

01-0

.006

-0.0

010.

001

-0.0

000.

001

(0.0

03)

(0.0

05)

(0.0

05)

(0.0

06)

(0.0

03)

(0.0

04)

(0.0

01)

(0.0

01)

(0.0

01)

(0.0

01)

D

ecre

asin

g

unem

ploy

men

t ra

te-0

.000

-0.0

020.

000

0.00

10.

000

-0.0

00-0

.005

-0.0

27-0

.060

*-0

.016

(0.0

01)

(0.0

01)

(0.0

01)

(0.0

01)

(0.0

01)

(0.0

01)

(0.0

20)

(0.0

25)

(0.0

24)

(0.0

32)

O

bser

vatio

ns6,

807

2,14

61,

585

1,77

41,

298

6,80

32,

146

1,58

51,

774

1,29

8

Num

ber

of in

divi

dual

s2,

773

974

666

708

423

2,77

197

466

670

842

3

Sour

ce: A

utho

rs’ c

alcu

latio

ns b

ased

on

Frag

ile F

amili

es a

nd C

hild

Wel

lbei

ng S

tudy

dat

a.N

ote:

Sta

ndar

d er

rors

and

z-s

tats

in p

aren

thes

es. M

odel

1 in

clud

es u

nem

ploy

men

t rat

e as

a le

vel.

Mod

el 2

incl

udes

une

mpl

oym

ent r

ate

as a

leve

l as w

ell a

s rat

e in

crea

sing

chan

ge

and

the

rate

of d

ecre

asin

g ch

ange

in u

nem

ploy

men

t rat

e. S

Es f

or th

e O

LS

with

fixe

d ef

fect

s are

clu

ster

ed a

t city

, for

OL

S an

d lo

gist

ic m

odel

s with

out f

ixed

eff

ects

are

clu

ster

ed a

t ci

ty a

nd in

divi

dual

.**

p <

.01;

*p

< .0

5; † p

< .1

Tabl

e 5

.A2

C

onti

nu

ed

With

Ind

ivid

ual F

ixed

Eff

ects

With

out

Indi

vidu

al F

ixed

Eff

ects

All

Les

s th

an

Hig

h Sc

hool

Hig

h Sc

hool

Som

e C

olle

geC

olle

ge +

All

Les

s th

an

Hig

h Sc

hool

Hig

h Sc

hool

Som

e C

olle

geC

olle

ge +

Tabl

e 5.A

3

Sen

siti

vity

of U

nem

ploy

men

t R

ate

Coe

ffic

ient

s, R

elat

ions

hip

Out

com

esW

ith I

ndiv

idua

l Fix

ed

Eff

ects

With

out

Indi

vidu

al

Fixe

d E

ffec

ts

Mot

her

mar

ried

to

fath

er o

r ne

w p

artn

er

Une

mpl

oym

ent

rate

(m

odel

1)

-0.0

17(0

.044

)-0

.038

*(0

.018

)

Une

mpl

oym

ent

rate

(m

odel

3)

0.04

0(0

.053

)-0

.022

(0.0

25)

M

othe

r’s

unem

ploy

men

t-0

.081

(0.1

26)

-0.3

71**

*(0

.077

)

Bio

-soc

ial f

athe

rs n

ot e

mpl

oyed

——

——

U

nem

ploy

men

t ra

te (

mod

el 4

)-0

.067

(0.0

60)

-0.0

40(0

.027

)

Une

mpl

oym

ent

rate

* y

ear

nine

0.08

4(0

.069

)0.

002

(0.0

29)

Mot

her

mar

ried

to

or c

ohab

iting

with

fath

er o

r ne

w p

artn

er

Une

mpl

oym

ent

rate

(m

odel

1)

-0.0

56†

(0.0

34)

-0.0

43*

(0.0

19)

U

nem

ploy

men

t ra

te (

mod

el 3

)-0

.034

(0.0

79)

-0.0

48*

(0.0

24)

M

othe

r’s

unem

ploy

men

t-0

.056

(0.0

40)

-0.2

30**

*(0

.051

)

Bio

-soc

ial f

athe

r’s

not

empl

oyed

——

——

U

nem

ploy

men

t ra

te (

mod

el 4

)-0

.111

*(0

.047

)-0

.063

*(0

.026

)

Une

mpl

oym

ent

rate

* y

ear

nine

0.08

6†(0

.051

)0.

032

(0.0

24)

Mot

her’

s re

port

of f

athe

r’s

supp

ortiv

enes

s

Une

mpl

oym

ent

rate

(m

odel

1)

-0.0

00(0

.005

)0.

001

(0.0

05)

U

nem

ploy

men

t ra

te (

mod

el 3

)-0

.000

(0.0

04)

-0.0

01(0

.007

)

Mot

her’

s un

empl

oym

ent

0.02

9(0

.018

)-0

.018

(0.0

14)

B

io-s

ocia

l fat

her’

s no

t em

ploy

ed0.

010

(0.0

18)

-0.0

48**

(0.0

17)

U

nem

ploy

men

t ra

te (

mod

el 4

)0.

008

(0.0

07)

0.01

3(0

.009

)

Une

mpl

oym

ent

rate

* y

ear

nine

-0.0

17*

(0.0

07)

-0.0

24**

(0.0

08)

Mot

her’

s re

port

of n

ew p

artn

ers’

sup

port

iven

ess

U

nem

ploy

men

t ra

te (

mod

el 1

)0.

009

(0.0

11)

-0.0

01(0

.008

)

Une

mpl

oym

ent

rate

(m

odel

3)

0.01

6(0

.014

)0.

007

(0.0

10)

M

othe

r’s

unem

ploy

men

t-0

.029

(0.0

28)

-0.0

46**

(0.0

15)

B

io-s

ocia

l fat

hers

not

em

ploy

ed-0

.012

(0.0

29)

-0.0

32(0

.022

)

Une

mpl

oym

ent

rate

(m

odel

4)

-0.0

01(0

.014

)-0

.010

(0.0

13)

U

nem

ploy

men

t ra

te *

yea

r ni

ne0.

014

(0.0

14)

0.01

1(0

.012

)(T

able

con

tin

ues

on

p. 1

44.)

Tabl

e 5.A

3

Con

tin

ued

With

Ind

ivid

ual F

ixed

E

ffec

tsW

ithou

t In

divi

dual

Fi

xed

Eff

ects

Mot

her’

s re

port

of o

vera

ll qu

ality

of r

elat

ions

hip

with

bio

fath

er

Une

mpl

oym

ent

rate

(m

odel

1)

0.01

1(0

.013

)0.

018

(0.0

18)

U

nem

ploy

men

t ra

te (

mod

el 3

)0.

005

(0.0

14)

-0.0

02(0

.025

)

Mot

her’

s un

empl

oym

ent

0.00

9(0

.048

)0.

011

(0.0

31)

B

io-s

ocia

l fat

her’

s no

t em

ploy

ed-0

.072

(0.0

54)

-0.1

89**

*(0

.038

)

Une

mpl

oym

ent

rate

(m

odel

4)

0.01

2(0

.016

)0.

036

(0.0

22)

U

nem

ploy

men

t ra

te *

yea

r ni

ne-0

.002

(0.0

15)

-0.0

38*

(0.0

18)

Fath

er’s

rep

ort

of m

othe

r’s

supp

ortiv

enes

s

Une

mpl

oym

ent

rate

(m

odel

1)

-0.0

08*

(0.0

04)

-0.0

10†

(0.0

06)

U

nem

ploy

men

t ra

te (

mod

el 3

)-0

.008

(0.0

05)

-0.0

11(0

.007

)

Mot

her’

s un

empl

oym

ent

0.00

8(0

.020

)0.

001

(0.0

14)

B

io-s

ocia

l fat

hers

not

em

ploy

ed-0

.006

(0.0

15)

0.01

1(0

.014

)

Une

mpl

oym

ent

rate

(m

odel

4)

-0.0

05(0

.004

)-0

.003

(0.0

06)

U

nem

ploy

men

t ra

te *

yea

r ni

ne-0

.006

(0.0

06)

-0.0

13†

(0.0

07)

Fath

er’s

rep

ort

of o

vera

ll qu

ality

of r

elat

ions

hip

with

bio

mot

her

U

nem

ploy

men

t ra

te (

mod

el 1

)-0

.014

(0.0

12)

-0.0

22†

(0.0

12)

U

nem

ploy

men

t ra

te (

mod

el 3

)-0

.038

*(0

.016

)-0

.037

*(0

.016

)

Mot

her’

s un

empl

oym

ent

0.08

4†(0

.046

)-0

.066

†(0

.039

)

Bio

-soc

ial f

athe

rs n

ot e

mpl

oyed

-0.0

91†

(0.0

50)

-0.0

33(0

.035

)

Une

mpl

oym

ent

rate

(m

odel

4)

0.01

0(0

.007

)0.

025

(0.0

17)

U

nem

ploy

men

t ra

te *

yea

r ni

ne-0

.044

**(0

.013

)-0

.085

***

(0.0

16)

Sour

ce: A

utho

rs’ c

alcu

latio

ns b

ased

on

Frag

ile F

amili

es a

nd C

hild

Wel

lbei

ng S

tudy

dat

a.N

ote:

Sta

ndar

d er

rors

and

z-s

tats

in p

aren

thes

es. M

odel

3 in

clud

es u

nem

ploy

men

t rat

e an

d a

mea

sure

of i

ndiv

idua

l une

mpl

oym

ent.

Mod

el 4

in

clud

es u

nem

ploy

men

t rat

e an

d an

inte

ract

ion

betw

een

unem

ploy

men

t rat

e an

d ye

ar n

ine,

whe

n th

e G

reat

Rec

essio

n hi

t. SE

s for

the

OL

S w

ith fi

xed

effe

cts a

re c

lust

ered

at c

ity, f

or O

LS

and

logi

stic

mod

els w

ithou

t fix

ed e

ffec

ts a

re c

lust

ered

at c

ity a

nd in

divi

dual

.**

*p <

.001

; **p

< .0

1; *

p <

.05;

† p <

.1

Tabl

e 5

.A4

C

oeff

icie

nts

and

Sta

ndar

d Err

ors

for U

nem

ploy

men

t R

ate,

Rel

atio

nshi

p O

utco

mes

Whi

teB

lack

His

pani

cM

arri

ed a

t B

asel

ine

Coh

abiti

ng

at B

asel

ine

Sing

le a

t B

asel

ine

Mot

her

mar

ried

to

fath

er o

r ne

w p

artn

er

Une

mpl

oym

ent

rate

-0.0

74-0

.011

0.03

2-0

.051

-0.0

40-0

.040

(0.0

87)

(0.0

81)

(0.0

75)

(0.1

20)

(0.0

66)

(0.0

88)

Mot

her

mar

ried

to

or c

ohab

iting

with

fath

er o

r ne

w p

artn

er

Une

mpl

oym

ent

rate

-0.1

32-0

.023

0.01

4-0

.041

-0.0

81-0

.087

†

(0.0

82)

(0.0

51)

(0.0

63)

(0.1

19)

(0.0

56)

(0.0

48)

Mot

her’

s re

port

of f

athe

r’s

supp

ortiv

enes

s

Une

mpl

oym

ent

rate

0.00

3-0

.002

0.00

00.

006

-0.0

06-0

.002

(0.0

07)

(0.0

11)

(0.0

05)

(0.0

08)

(0.0

07)

(0.0

10)

Mot

her’

s re

port

of n

ew p

artn

ers’

sup

port

iven

ess

U

nem

ploy

men

t ra

te0.

048†

-0.0

11-0

.006

-0.0

600.

009

0.01

6(0

.025

)(0

.022

)(0

.015

)(0

.037

)(0

.026

)(0

.011

)M

othe

r’s r

epor

t of o

vera

ll qu

ality

of r

elat

ions

hip

with

bio

fath

er

Une

mpl

oym

ent

rate

0.01

50.

013

0.01

20.

021†

-0.0

070.

021

(0.0

21)

(0.0

22)

(0.0

20)

(0.0

12)

(0.0

17)

(0.0

37)

Fath

er’s

rep

ort

of m

othe

r’s

supp

ortiv

enes

s

Une

mpl

oym

ent

rate

-0.0

060.

005

-0.0

18**

*0.

008

-0.0

26**

*-0

.026

(0.0

05)

(0.0

09)

(0.0

03)

(0.0

05)

(0.0

06)

(0.0

21)

Fath

er’s

rep

ort o

f ove

rall

qual

ity o

f rel

atio

nshi

p w

ith b

io m

othe

r

Une

mpl

oym

ent

rate

0.00

0-0

.025

-0.0

31*

-0.0

15-0

.035

**0.

041

(0.0

23)

(0.0

35)

(0.0

13)

(0.0

25)

(0.0

10)

(0.0

31)

Sour

ce: A

utho

rs’ c

alcu

latio

ns b

ased

on

Frag

ile F

amili

es a

nd C

hild

Wel

lbei

ng S

tudy

dat

a.N

ote:

Sta

ndar

d er

rors

and

z-s

tats

in p

aren

thes

es. M

odel

1 in

clud

es le

vel u

nem

ploy

men

t rat

e; r

esul

ts in

clud

e in

divi

dual

fixe

d ef

fect

s an

d tim

e. S

Es

for

the

OL

S w

ith

fixed

eff

ects

are

clu

ster

ed a

t city

.**

*p <

.001

; **p

< .0

1; *

p <

.05;

† p <

.1


NOTES

1. Ogburn and Nimkoff 1955; Cherlin 1992. 2. Lichter, McLaughlin, and Ribar 2002; Blau, Kahn, and Waldfogel 2000;

Moffitt 2000. 3. Schaller 2012; Schneider and Hastings 2015. 4. Ogburn and Nimkoff 1955. 5. Willcox 1893; Ogburn and Thomas 1922; Gulden 1939. 6. Conger and Elder 1994; South 1985; Fischer and Liefbroer 2006. 7. Amato and Beattie 2011; Hellerstein and Morrill 2011; Schaller 2012. 8. Cherlin et al. 2013. 9. Cohen 2014.10. Cherlin et al. 2013.11. Komarovsky 1940.12. Conger et al. 1999; Conger and Elder 1994.13. Fox et al. 2002; Benson et al. 2003; Vinokur et al. 1996.14. Patterson 1998; Hatchett et al. 1995.15. Bakke 1940; Komarovsky 1940.16. The father sample is positively selected on seriousness of relationship with

mother. Fathers who were interviewed tended to have closer relationships with mothers (for example, to be married or cohabiting) than those who were not. The positive selection explains why fathers tend to report higher mean levels of relationship quality, but why this selectivity would bias the comparison of father reports of supportiveness under strong and weak economic conditions is unclear (see figure 5.13). Therefore, the decline in fathers’ reports of mothers’ supportiveness but not mothers’ reports of fathers’ supportiveness likely reflects a differential response by gender to the recession conditions.

17. Schneider, McLanahan, and Harknett 2016.18. Conger and Elder 1994.

REFERENCESAmato, Paul R., and Brett Beattie. 2011. “Does the Unemployment Rate Affect

the Divorce Rate? An Analysis of State Data 1960–2005.” Social Science Research 40(3): 705–15.

Bakke, E. Wight. 1940. Citizens Without Work: A Study of the Effects of Unemployment Upon the Workers’ Social Relations and Practices. New Haven, Conn.: Yale University Press.

Benson, Michael L., Greer L. Fox, Alfred DeMaris, and Judy Van Wyk. 2003. “Neighborhood Disadvantage, Individual Economic Distress and Violence Against Women in Intimate Relationships.” Journal of Quantitative Criminology 19(3): 207–35.


Blau, Francine D., Laurence M. Kahn, and Jane Waldfogel. 2000. “Understanding Young Women’s Marriage Decisions: The Role of Labor and Marriage Market Conditions.” Industrial and Labor Relations Review 58(4): 624–47.

Cherlin, Andrew J. 1992. Marriage, Divorce, Remarriage. Cambridge, Mass.: Harvard University Press.

Cherlin, Andrew, Erin Cumberworth, S. Philip Morgan, and Christopher Wimer. 2013. “The Effects of the Great Recession on Family Structure and Fertility.” Annals of the American Academy of Political and Social Science 650(1): 214–31.

Cohen, Phillip N. 2014. “Recession and Divorce in the United States, 2008–2011.” Population Research and Policy Review 33(5): 615–28.

Conger, Rand D., and Glenn H. Elder Jr. 1994. Families in Troubled Times: Adapting to Change in Rural America. Social Institutions and Social Change. New York: Aldine de Gruyter.

Conger, Rand D., Martha A. Rueter, and Glenn H. Elder Jr. 1999. “Couple Resilience to Economic Pressure.” Journal of Personality and Social Psychology 76(1): 54–71.

Fischer, Tamar, and Aart C. Liefbroer. 2006. “For Richer, for Poorer: The Impact of Macroeconomic Conditions on Union Dissolution Rates in the Netherlands 1972–1996.” European Sociological Review 22(5): 519–32.

Fox, Greer L., Michael L. Benson, Alfred A. DeMaris, and Judy Van Wyk. 2002. “Economic Distress and Intimate Violence: Testing Family Stress and Resources Theories.” Journal of Marriage and the Family 64(3): 793–807.

Gulden, Tees. 1939. “Divorce and Business Cycles.” American Sociological Review 4(2): 217–23.

Hatchett, Shirley J., Joseph Veroff, and Elizabeth Douvan. 1995. “Marital Instability among Black and White Couples in Early Marriage.” In The Decline in Marriage Among African Americans, edited by M. Belinda Tucker and Claudia Mitchell-Kernan. New York: Russell Sage Foundation.

Hellerstein, Judith K., and Melinda S. Morrill. 2011. “Booms, Busts, and Divorce.” B.E. Journal of Economic Analysis & Policy 11(1): ISSN (Online) 1935–1682.2914.

Komarovsky, Mirra. 1940. The Unemployed Man and His Family. New York: Dryden Press.

Lichter, Daniel T., Diane K. McLaughlin, and David C. Ribar. 2002. “Economic Restructuring and the Retreat from Marriage.” Social Science Research 31(2): 230–56.

Moffitt, Robert A. 2000. “Welfare Benefits and Female Headship in US Time Series.” American Economic Review 90(2): 373–77.

Ogburn, William F., and Meyer F. Nimkoff. 1955. Technology and the Changing Family. Westport, Conn.: Greenwood Press.

Ogburn, William F., and Dorothy S. Thomas. 1922. “The Influence of the Business Cycle on Certain Social Conditions.” Journal of the American Statistical Association 18(139): 324–40.

Patterson, Orlando. 1998. Rituals of Blood: Consequences of Slavery in Two American Centuries. Washington, D.C.: Civitas/CounterPoint.

Schaller, Jessamyn. 2012. “For Richer, if Not for Poorer? Marriage and Divorce over the Business Cycle.” Journal of Population Economics 26(3): 1007–33.

Schneider, Daniel, Sara S. McLanahan, and Kristen Harknett. 2016. “Intimate Partner Violence in the Great Recession.” Demography 53(2): 471–505.


Schneider, Daniel, and Orestes P. Hastings. 2015. “Socio-Economic Variation in the Effect of Economic Conditions on Marriage and Non-marital Fertility: Evidence from the Great Recession.” Demography 52(6): 1983–15.

South, Scott J. 1985. “Economic Conditions and the Divorce Rate: A Time Series Analysis of the Postwar United States.” Journal of Marriage and Family 47(1): 31–41.

Vinokur, Amiram D., Richard H. Price and Robert D. Caplan. 1996. “Hard Times and Hurtful Partners: How Financial Strain Affects Depression and Relationship Satisfaction of Unemployed Persons and their Spouses.” Journal of Personality and Social Psychology 71(1): 166–79

Willcox, Walter F. 1893. “A Study in Vital Statistics.” Political Science Quarterly 8(1): 69–96.

schneider, daniel, sara mclanahan, and kristen harknett ... · child’s age-year source:...

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