Unique longitudinal measures from Nepal allow us to link both mothers’ and fathers’ reports of their marital relationships with a subsequent long-term record of their children’s behaviors. We focus on children’s educational attainment and marriage timing because these two dimensions of the transition to adulthood have wide-ranging, long-lasting consequences. We find that children whose parents report strong marital affection and less spousal conflict attain higher levels of education and marry later than children whose parents do not. Furthermore, these findings are independent of each other and of multiple factors known to influence children’s educational attainment and marriage timing. These intriguing results support theories pointing toward the long-term intergenerational consequences of variations in multiple dimensions of parents’ marriages.
The emotional bond between spouses is a critical component of family life, yet we know little about the long-term consequences of this component for the next generation. Marriage is a key dimension of social networks in nearly all societies (Coleman 1994; Ogburn and Tibbets 1934; Thornton and Fricke 1987), and emotional dimensions are widely recognized as core features of marriage, regardless of whether emotions were historically considered important for marriage formation (Ahearn 2001; Fuller and Narasimhan 2008; Pasupathi 2002). Research has established intergenerational links between parents’ marital experiences (such as divorce) and multiple dimensions of children’s transitions to adulthood, yet few studies have investigated emotional dimensions of the parental marriage (for exceptions, see Orthner et al. 2009; Rijken and Liefbroer 2009).
In this study, we advance this topic by investigating the association of the emotional bond between mothers and fathers with the subsequent pace of their children’s transition to adulthood, using more than a decade of intergenerational panel data from Nepal. We focus on two key dimensions of this transition: educational attainment and entrance into marriage. Educational attainment has many important consequences for adulthood, particularly in work and earnings trajectories (Card 1999) but also in health, marital, and childbearing experiences (Baker et al. 2011; Brand and Davis 2011; Hout 2012). Likewise, marriage timing also has many important consequences: marriage occurring earlier than average is associated with lower earnings, higher risk of divorce, poor mental health, higher rates of maternal and child death, and higher risk of domestic violence (Harris et al. 2010; Loughran and Zissimopoulos 2009; Santhya et al. 2010; UNICEF 2001).
Research has revealed that parental family factors constitute a powerful, long-lasting influence on children’s educational attainment and marriage behavior. For example, longitudinal studies have demonstrated that the parental family in early childhood shapes cognitive development and children’s educational attainment (Cavanagh et al. 2006; Fomby and Bosick 2013; Fomby and Cherlin 2007; Heard 2007; Sun and Li 2011). Similarly, studies have also shown that the parental family influences the pace at which children exit the parental home and the pace at which they form their own unions (Goldscheider and Goldscheider 1993; Goldscheider and Waite 1993; McLanahan and Bumpass 1988).
We add to the literature in two major ways. First, we examine the emotional dimension of the parental home environment as opposed to family events (such as divorce). Second, we explicitly link these measures of parental marital quality in childhood to trajectories of both children’s educational attainment and their marriage timing over 12 years. Also novel, we investigate these associations in rural South Asia, a setting quite different from the Western European and U.S. setting for most prior research on these associations.
We pose multiple related research questions. Independent of other factors known to influence children’s education and marriage timing, do children whose parents have a stronger positive emotional bond (i.e., express more love) have higher educational attainment and/or marry later than those whose parents have a weaker positive emotional bond? And do children whose parents have more marital conflict exit school and marry earlier than those whose parents have less marital conflict? Our theoretical framework and analyses examine parental affection and conflict as different, potentially contrasting dimensions of the parental marital relationship. In the end, this study motivates increased research attention to the long-term intergenerational consequences of marital quality.
To guide our investigation into the associations between parental marital relationships and their children’s transition to adulthood, we construct a multicomponent theoretical framework. We draw on research from Western Europe and North America to identify likely mechanisms creating these associations but apply this reasoning to a very different context: Nepal. Therefore, we begin with background information on Nepal to contextualize both the specific dimensions of marital relationships that we consider and the theoretical connection between those dimensions and children’s transition to adulthood. We then build on that to present some setting-specific mechanisms likely to link parents’ marital quality to their children’s transition to adulthood generally, and both educational attainment and marriage timing specifically. Finally, we discuss the known determinants of children’s educational attainment and marriage timing that may also shape the emotional dimensions of the parental relationship.
Marriage in Nepal
Marriage in Nepal is universal. Until recently, marriages occurred at young ages for both men and women, with a nontrivial amount of child marriage, but age at marriage has increased in recent decades for both men and women (Bajracharya and Bhandari 2014). For example, the median age at marriage for women increased from 16.4 in 1996 to 17.9 in 2016 (Ministry of Health 1997, 2017). As of 2016, the median age at first marriage among men aged 25–49 is 21.7 years (Ministry of Health et al. 2017). Thus, women in Nepal marry about four years earlier than men. This age pattern is similar to that seen in India, although later than in Bangladesh; for example, median age at marriage for women aged 25–49 in 2005/2006 was 17.0 for Nepal, 16.8 for India, 14.5 for Bangladesh (Macro International 2007). These relatively young ages at marriage make Nepal quite different from the United States and Western Europe.
Nepal’s history of parentally arranged marriage is another important difference from the United States and European populations. Marriages were characterized by high levels of parental involvement in many ethnic groups but also high heterogeneity across ethnic groups in the ways that they were and are arranged (Acharya and Bennett 1981; Ahearn 2001; Fricke 1986). Individuals are becoming increasingly involved in the choice of spouse (Allendorf and Pandian 2016; Allendorf et al. 2017; Ghimire et al. 2006). In the data used here, no spouses of the 1936–1945 marriage cohort had participated in the selection of their spouse, but one-half of those in the 1986–1995 marriage cohort had done so (Ghimire et al. 2006). Love marriages, for which parents have essentially no say in their children’s marriage partner, are also increasingly prevalent but remain uncommon. In most Nepalese ethnic groups, wives move to live with the husbands’ family after marriage, although this is less widespread today (Bennett 1983; Pearlman et al. 2017).
Finally, premarital cohabitation and divorce, both common in North America and Western Europe, are increasing but are still quite rare in Nepal. There remains no evidence of population-scale premarital cohabitation, but divorce is rapidly becoming more common (Jennings 2016).
Education in Nepal
The spread of schools and accompanying increased proportion of childhood spent in school are key factors producing these changes in marriage and other family-related behaviors (Brauner-Otto 2012; Ji 2013; Yabiku 2005). The dramatic increase in the availability and quality of schools created a watershed change in mass education, increasing both school enrollment and educational attainment, with wide-ranging demographic consequences (Axinn and Barber 2001; Brauner-Otto 2012; Ghimire et al. 2006). From 2011 to 2016, the median years of schooling for those aged 15–49 increased from 3.5 to 5.0 for women and from 7.4 to 8.0 for men (Ministry of Health et al. 2017). In our study area, by 1996, all children aged 5 and 6 had been to school for at least one day (Beutel and Axinn 2002). School location and quality also changed over this period. In 1996, only 88% of households in Nepal lived within a 30-min walk of a school, but 95% did so by 2011 (Ministry of Education and UNESCO 2015). The percentage of teachers with required qualifications and training increased from 15% in 2001 to 98% in 2012 (Ministry of Education and UNESCO 2015).
The educational system in Nepal is structured such that primary school begins at age 5, and the completion of secondary school occurs after grade 10. Early childhood care and education (ECCE) has also become a greater priority in the Nepalese education plan, and enrollment has similarly increased. For example, roughly 40% of eligible children were enrolled in ECCE in 2006, compared with more than 70% by 2012 (Ministry of Education and UNESCO 2015). Upon completion of grade 10, students are eligible to take an exam to earn their School-Leaving Certificate (SLC), the equivalent of a high school diploma in the United States. Fewer than 3% of ever-married women had received an SLC in 1996, compared with 18.4% of women aged 15–49 by 2011 and 24.4% by 2016 (Ministry of Health et al. 2017). For men, the percentage aged 15–49 with an SLC increased slightly from 31.6% in 2011 to 36.8% in 2016 (Ministry of Health et al. 2017).
Parental Marital Quality
Research has consistently found that across settings, marital quality comprises multiple related and often contrasting but independent dimensions (Allendorf and Ghimire 2013; Bradbury et al. 2000; Umberson et al. 2005). The positive emotional bond (affection or love) is commonly identified as one of the most important (Allendorf 2009; Allendorf and Ghimire 2013; Axinn et al. 2017; Goode 1970). This has long been the case for research on Western European marriages, which has usually treated love and affection as a prerequisite and the singular core defining feature of marriage (Goode 1959; Hamon and Ingoldsby 2003; Thornton et al. 2007). The recognition of the centrality of love in non-Western marriages is more recent: arranged marriages were often characterized as loveless, empty, patriarchal, and without choice (Khandelwal 2009; Pasupathi 2002). However, recent work has criticized this ethnocentric characterization recognizing love—in particular, that between husbands and wives—as a universal psychological phenomenon, not something unique to Western marriage (Coontz 2005; Khandelwal 2009). In fact, Hinduism often glorifies the idea of love between the sexes, as is evident from the variety of mythical love stories, such as Kamasutra, that abound in Sanskrit literature (Vātsyāyana 2009). It is clear that the positive emotional bond between husbands and wives is part of daily life for married couples in Nepal and that there is variation in the degree of this bond (Ahearn 2001; Allendorf 2009; Fricke 1986; MacFarlane 1976; Pasupathi 2002).
Negative dimensions of marriage, such as conflict between spouses, are also apparent in families in Nepal (Allendorf and Ghimire 2013; Hoelter et al. 2004; Jennings 2014). Domestic violence, disagreements between spouses, and worries about the marriage have all been identified as prevalent in marriages in Nepal (Allendorf and Ghimire 2013; Ghimire et al. 2015; Hoelter et al. 2004). An important but missing component of the literature is understanding how love and conflict between spouses influence their children’s lives. The combination of measures of both positive emotional bond and spousal conflict (obtained from both members of the couple) in a long-term, intergenerational panel study provides us the rare opportunity to provide insight into the associations with these different and often contrasting dimensions of marital quality.
Mechanisms Linking Parents’ Marital Quality to Children’s Transitions to Adulthood
Previous research has indicated that multiple mechanisms may link parents’ marital quality to their children’s life courses (for a review, see Orthner et al. 2009). Here we consider three mechanisms likely to be operating in the Nepal-specific context: parental investments in childrearing, general social psychological links between parents and children, and children’s motivations to leave the parental home. This study does not aim to identify which mechanism is at work, and all three—and possibly others—are likely operating simultaneously. Rather, we examine the overarching relationship between parental marital quality and children’s transition to adulthood.
Parents’ Investments in Childrearing
Positive parental marital quality may shape childrearing practices, with potentially strong consequences for educational attainment. As processes of entering marriage change, some scholars have argued that married couples with higher levels of affection for each other may be more likely to spend more resources on their children than on their extended kin (Caldwell 1982; Degler 1980). In this view, as childbearing and childrearing become an expression of marital love and affection, couples invest more time and resources in their children and begin trading low investments in many children for high investments in a small number of “high quality” children (Becker 1991; Caldwell 1982; Willis 1973). Parents’ investments in the quality of their children may increase children’s educational attainment, particularly as children’s educational resources have been identified as the leading form of parental investment in the quality of their children (Becker 1991; Caldwell 1982; Willis 1973). Therefore, we expect positive emotional bonds between parents to be positively related to their children’s educational attainment. Further, the social science literature has provided formidable evidence that enrollment in school delays marriage among both men and women and across a wide range of settings, including in Asia (Caldwell et al. 1988; Thornton and Lin 1994; Thornton et al. 2007; Yabiku 2005). Because high educational attainment requires school enrollment, this mechanism may also delay children’s marriages.
Social Psychological Links Between Parents and Children
Social psychological perspectives on parenting behavior and intergenerational transmission suggest that marital relationships may shape multiple aspects of parents’ lives, including their parenting (Cherlin et al. 1995; Shek 1998). This has been described as a spillover from the parental marital relationship to the parent-child relationship (e.g., Malinen et al. 2010), as shaping children’s taste for family (Rijken and Liefbroer 2009), or simply as a fundamental component of the socialization process. Empirical research has demonstrated this across the life course and for both behavioral and psychological outcomes, such as children’s behavior problems and their family-related attitudes in adulthood (Cunningham and Thornton 2006; Goldberg and Carlson 2014).
We expect that these positive dimensions of the parental marital relationship may also spill over to have other consequences for their children’s lives, including their children’s marital relationships. In settings historically characterized by young and arranged marriages, such as Nepal, this positive spillover may delay children’s marriage. Exposure to parents’ positive marital relationships may set different expectations for the younger generation’s marital relationships such that young people and their families spend more time selecting a spouse before entering marriage (Bandura 1986). This is particularly likely as an increasing fraction of young people participate in the selection of their own spouse (Allendorf 2017; Ghimire et al. 2006). This mechanism could lead to delayed timing of marriage among young people with parents who have a relatively more positive relationship. Additionally, because early marriage is a key reason for truncated educational attainment in a setting like Nepal (Beutel and Axinn 2002), it is also possible that this mechanism links more positive parental marital relationships to higher educational attainment.
Children’s Motivations to Move Away
Children’s own motivations to move away from the parental home may also link parents’ marital quality to children’s transition to adulthood, especially their marriage timing (Goldscheider and Goldscheider 1993; Goldscheider and Waite 1993; Thornton et al. 2007). The quality of the parental home has been identified as influencing the pace of children’s moving out (Goldscheider and Goldscheider 1993). As with other dimensions (e.g., household goods) of the parental home that may make it more pleasant, positive mother-father relationships are expected to reduce children’s motivation to exit the parental home. Said another way, the positive parental marital relationship may delay children’s marriage because family members are content in their current situation (Rijken and Liefbroer 2009). This reduced motivation to leave the parental home is then expected to reduce the pace of entry into marriage because marriage is an important way children secure living arrangements away from parents (Goldscheider and Waite 1993; Thornton et al. 2007).
This is particularly likely in Nepal, where in contrast to settings like the United States in which young people often enjoy many different options for alternative living arrangements outside the parental home, marriage is the most common long-term, viable option (Fricke 1986; MacFarlane 1976; Pearlman et al. 2017; Yabiku 2004). Young people in Nepal rarely live alone, with housemates, or in school or work dormitories. Moreover, young people who test these alternative arrangements do not spend much time in them and transition rapidly to marriage. It is also possible that by continuing to live in the parental home, children are able to focus on education, achieving higher levels of educational attainment.
Negative Dimensions of Marital Quality
Because marital quality is multidimensional, we note that although positive dimensions (such as love) may operate as described earlier, negative dimensions (such as conflict) may also simultaneously influence children (e.g., Amato and DeBoer 2001; Amato and Sobolewski 2001; Cherlin et al. 1995; Rijken and Liefbroer 2009; Wolfinger 2003). For example, negative dimensions of the parental relationship may lower the quality of the parental home, thereby increasing the motivation to leave the parental home. As described earlier, marriage in this context is the most likely long-term path away from the parental home, and marriage truncates education attainment. Therefore, in this context, negative parental marital relationships may speed children’s marriages and lower educational attainment.
Because children are increasingly involved in spouse selection, parental marital quality is likely related to children’s marriage timing even in this setting of marital arrangement. Children whose parents do not love each other or who have a high-conflict marriage may be more willing to accept a less desirable spouse. Alternatively, children in higher-conflict homes may have lower expectations for positive affect from a partner, enabling earlier marriage by allowing a broader range of potential spouses to be acceptable.
Factors That May Shape Both Parental Marriage Quality and Children’s Transition to Adulthood
To estimate the relationship between parental marital quality and children’s transition to adulthood in an observational study design, we must consider other aspects of the parental family known to shape both children’s transitions to adulthood and parents’ emotional bond (Kalmijn 1991, 1994, 2015; Mare 1991; Sweeney 2002). Because they themselves are not the focus of this article, we discuss them only briefly here.
Empirical research in Western and non-Western settings has documented substantial variation in the transition to adulthood by race, ethnicity, and religion (Goldscheider and Goldscheider 1993; Goode 1959; Gullickson and Torche 2014; Kuo and Raley 2016; Page and Stevens 2005). In Nepal, these three characteristics are intricately connected, typically manifest themselves in terms of caste-ethnicity, and have been linked to variation in family formation behavior (Bennett 1983; Fricke 1986; Pearce et al. 2015).
Parents’ marital and nonfamily experiences also shape the quality of their relationship and their children’s transitions to adulthood. Parental age at marriage has consistently been found to influence children’s transition to adulthood across geographic settings (Allendorf and Ghimire 2013; Goldscheider and Waite 1993; Thornton and Lin 1994). In a setting like Nepal, marital arrangement in the parents’ generation is also likely important because it may influence the level of spousal choice that they give their children: parents who had more choice may also give their children greater choice, leading the children to delay their entrance into marriage. Parents’ childbearing may also be important (Axinn et al. 1994; Barber and Axinn 1998): those who are strongly pronatalist are likely to socialize their children to marry more quickly (Barber and Axinn 1998) but must also divide their investments in children across more children, and the number of children couples have may influence their marital quality. Finally, parents with more experiences outside the family—for instance, living away from parents and going to school—have likely been more influenced by Western ideas of education and courtship prior to marriage, which may influence their marital quality, investments in their children, and their children’s marriage timing (Allendorf and Ghimire 2013; Ghimire et al. 2015; Goldscheider and Waite 1993; Thornton and Lin 1994; Yabiku 2005).
Prior research has also demonstrated that mothers’ and fathers’ communities in childhood and later in life influence their children’s transitions to adulthood (Thornton and Lin 1994; Yabiku 2004, 2006). Communities shape the opportunity structure that individuals face and have independent influences on individuals’ attitudes (Barber 2004; Caldwell et al. 1988; Coleman 1994; Pearce et al. 2015). Schools can be particularly important because mechanisms link access to schools to educational attainment and delayed marriage independently of school attendance (Axinn and Barber 2001; Brauner-Otto 2012; Thornton et al. 2007; Yabiku 2004).
To test our predictions, we use data from the Chitwan Valley Family Study (CVFS) conducted in the Western Chitwan Valley in Nepal. We are able to use the CVFS for this investigation because separate individual interviews measuring marital relationship quality were conducted independently with mothers and fathers, and their children were subsequently followed for 12 years to document their education and marital behaviors. In 1996, the CVFS collected information from residents of a systematic sample of 151 neighborhoods, or tols, in the Western Chitwan Valley. Tols are distinct clusters of 5–15 households, typically located at crossroads and surrounded by fields. Every resident aged 15–59 in the sampled neighborhoods and their spouses were interviewed.
The original 1996 respondents were reinterviewed in 2008, at which time women completed life history calendars (LHCs) with yearly information on children’s school enrollment for all children. These data are the source for annual measures of children’s education after the 1996 baseline interviews. Following the 1996 interviews, the CVFS began collecting a prospective monthly demographic event registry for every individual interviewed in 1996, even if they left Chitwan, yielding 126 months of event measures. These data are our source for monthly measures of the children’s marriage behavior after the 1996 baseline interviews.
We study the intergenerational link between parents’ marital quality and children’s transition to adulthood among children whose parents were married and interviewed in 1996. The CVFS interviewed both husbands and wives, with an overall initial response rate of 97%. Response rates remained high over the data collection period, with a low of 93% (Axinn et al. 2012).
To study educational attainment, we examine children age 16 or younger who were living with their parents in 1996. We limit the sample to these children to ensure that they experienced the parental marital quality as measured. Students typically finish secondary school around age 16, so we exclude children older than 16 in 1996. The final analysis sample is 2,714 children living with 1,168 sets of parents. We also estimate models including children born before 1980 and those born after 1996 and find similar if not stronger relationships than shown here.
To study marriage, we examine children who were unmarried but aged 15–24 in 1996 (i.e., interviewed in 1996 and subsequently exposed to the risk of first marriage). We exclude children if they were already married in 1996 to ensure proper temporal ordering in our analysis. Analysis of 15- to 19-year-olds, for whom marriage by 1996 was exceptionally rare, yields results substantively similar to those show here. The final analysis sample is 667 children living with 437 sets of parents.1
Parents’ Marital Quality
To measure parents’ marital quality, we create two indexes based on the separate reports from mothers and fathers in 1996. Recall that all currently married respondents were interviewed, and fathers and mothers were interviewed at the same time in separate places. This was done specifically to ensure that one spouse was not present and influencing the interview of the other spouse. First, consider our measure of the positive emotional bond between spouses. Fathers and mothers were each asked, “How much do you love (maya) your (husband/wife)? Very much, some, a little, or not at all?” The item is coded 1 for “a little” or “not at all,” 2 for “some,” and 3 for “very much,” such that a higher value indicates higher parental marital affection.2 In other research in this setting, with a wider range of measures of marital quality, responses to this question loaded strongly onto a factor of “positive satisfaction” (Allendorf and Ghimire 2013). Because husbands and wives were interviewed simultaneously but separately, we treat fathers’ and mothers’ responses as independent measures of the same underlying concept—the positive dimension of marital quality—and combine the two measures by calculating the mean. We also test models with each parents’ response separately and an index that adds the responses for both parents. Results for the additive measure are even larger than those shown here, and effect estimates are stronger for fathers’ than mothers’ reports. Descriptive statistics for this and other variables used in the analyses are shown in Table 1. Average love/affection between spouses is fairly high, with a mean of 2 across analysis samples, and about 80% of children having a mother and father who each reported loving the spouse “some” or “very much.”
To measure marital conflict, we create a measure of extreme conflict: whether either parent reported that his/her spouse had ever beaten him/her. In the 1996 interview, respondents were asked, “Has your (husband/wife) ever beaten you?,” with response options of yes or no. For both analysis samples, about 18% of children have parents who reported being victims of spousal violence. Of them, roughly 80% have only mothers who reported that their husbands beat them, 10% have only fathers who said their wives beat them, and 8% of children had parents who both reported experiencing physical violence. The correlation between the two indicators of parental marital quality is –.13 and –.10 (p < .001) for the two analysis samples.
Of course, marriages may have conflict that does not result in violence. We also test models that use measures of arguably more mild marital conflict: how often they have disagreements with their spouse and how often they are criticized by their spouse. Results are similar to those presented here. However, disagreements and criticism, even frequent ones, are likely to be a part of any marriage, and the more relevant question is whether such disagreements are dealt with positively, in a context of affection and understanding, or whether they lead to dysfunctional outcomes, such as bitterness or domestic violence. As such, we present only the models with the more extreme measure of conflict.
Some studies have provided evidence that marital quality changes over time and that different dimensions of marital quality may be more or less variable (James 2014, 2015). Specifically, marital happiness/satisfaction appears to decrease overall with marriage duration, but that decrease is more rapid for those who start at a lower level (James 2014, 2015; Whiteman et al. 2007). Marital conflict has been found to be more consistent over time, even with different starting levels (James 2015; Whiteman et al. 2007). Additionally, marital quality is generally thought to be most volatile in the early years of marriage, and some research has provided evidence that marital quality is quite stable over time (Bradbury 1998; Johnson and Booth 1998; Johnson et al. 1992).
Despite the potential for marital quality to change over time, previous empirical research has looked at the relationship between marital quality at one point in time and various behaviors across the life course. Most relevant for our analytic approach, studies have linked marital quality to mortality and divorce risks over the subsequent 5 to 16 years (Bulanda et al. 2016; Lawrence et al. 2018; Whiteman et al. 2007). This work is consistent with the expectation that even a single point-in-time measure of parental marital quality may indicate variance associated with long-term consequences.
On the other hand, from a measurement error perspective, a single point-in-time measure is likely characterized by error that increases over time. To test the sensitivity of our results to the potential measurement error resulting from the lag between the 1996 interview and the child’s behavior, we estimate models that include an interaction term between parental marital quality and time since 1996. We also conduct robustness tests that limit the length of time between the measurement of parents’ marital quality and children’s behavior. We discuss these results shortly.
Transition to Adulthood: Education
To investigate educational attainment, we estimate hazard models of the rate of stopping school. We use the 12 years of education data in the mothers’ LHCs collected in 2008 to operationalize the yearly hazard of stopping school in discrete time. The hazard starts in 1996 or the year the child first attended if he/she started school after 1996. We create a time-varying, dichotomous variable equal to 1 the first year the child stops attending school and 0 in years prior. Children are censored in 2008 or the year they turned 16 (when children typically finish high school). Less than 5% of eligible children had never attended school and are therefore excluded from the analysis sample.
The CVFS data provide many alternative measures of children’s educational attainment. The hazard of exit from schooling has strong statistical and comparative properties (Beutel and Axinn 2002); however, only 13% of children stopped attending school during the observation period. We test the robustness of our findings from this primary specification in two ways. First, we estimate models including person-years after age 16. Second, we use a different analysis sample and estimate models in which the dependent variable is whether children over age 16 in 2008 had obtained an SLC: 45% of children aged 17–27 in 2008 had received their SLC. In both cases, results are substantively identical to those shown here.
Transition to Adulthood: Marriage Timing
To investigate the marriage transition, we estimate hazard models of the rate of entrance into first marriage following the 1996 interview. We use 126 months of data on marriage to operationalize the monthly hazard of marrying in discrete time between 1996 and 2008. We create a time-varying dichotomous variable equal to 1 in the month the respondent marries and 0 in months prior. Roughly three-quarters of the sample—72% of men and 87% of women—marry at some point in the prospective data.
Factors That May Shape Both Parental Marriage Quality and Children’s Transition to Adulthood
Although we use carefully constructed longitudinal data to make sure the temporal order of our measures is consistent with our hypotheses, prior factors may produce a spurious association between measured parental marital quality and children’s behavior. The breadth of the CVFS allows us to include setting-specific measures of these factors that capture experiences and characteristics that occurred before parental marital quality and children’s behaviors were measured. Unless otherwise stated, the measure is time-invariant, is a mean of the mother’s and father’s reports, and is measured at the parent level.
We differentiate among the five groups representing major caste-ethnic and religious differences in our study site in Nepal: Chhetri-Bahun (high-caste Hindus), Dalit (low-caste Hindus), Newar, Hill Janajati (Tibeto Burmese descendants of Hill residents), and Terai Janajati (indigenous to northern India and the southern part of Nepal). Caste-ethnic group is the same for all household members.
We create categorical measures for parents’ education and living away from family equal to 2 if both parents had the experience before marriage (measured in 1996), 1 if one parent did, and 0 if neither parent had the experience. For 92% of the children, when only one parent went to school, it was the father.
We create three measures of parents’ experiences with marriage: parental age at marriage, marital arrangement, and the year the parents’ married. On average, fathers are almost five years older than mothers, but consistent with what we know about assortative mating, mothers’ and fathers’ ages are correlated (Mare 1991). Following previous research, we create a scale to indicate the level of participation in spouse choice ranging from having no choice of spouse (1) to having complete choice (5) (Ghimire et al. 2006; Jennings et al. 2012). As expected, given previous research on marital arrangement (Ghimire et al. 2006; Ghimire et al. 2015), fathers reported more involvement in the choice of their spouse than mothers.
Next we include measures of household characteristics including member composition in 1996 (the number of grandparents, number of siblings, and number of siblings who had died) and the quality of the parental home environment operationalized in terms of household affluence in 1996. Incomes are low in rural Nepal, and because many farming-related assets create affluence that increases the comfort of the parental home, we measure ownership of specific assets rather than income: a dichotomous measure for whether the household owned the land on which their house sits, and counts of the number of livestock and consumer durables that the household owned. Ownership of the home, livestock (which supply food), and consumer durables (e.g., radios, TVs, and bicycles) each enhance the comfort of the parental home and are not dependent on one another (e.g., those who do not own their home may have significant numbers of livestock).3
To measure community context, we focus on schools because they are the most salient dimension of community context that these young people navigate during the years they are in our analyses. We include a neighborhood-level, geographically weighted measure of school quality that incorporates all the schools open in 1995 (for more on geographically weighted measures of community context in this setting, see Brauner-Otto 2012 and Brauner-Otto et al. 2007). The specific school characteristic that we control for—namely, the proportion of teachers with advanced degrees—has been identified in the literature as important in keeping students, particularly girls, enrolled in school longer (Card and Krueger 1992; Lloyd et al. 2000; Mensch and Lloyd 1998) and has been found to be related to family-formation behaviors (Brauner-Otto 2012). This is a neighborhood-level measure.
Finally, in all our models, we include measures of children’s gender and year of birth. To account for the duration of the exposure to dropping out of school, we control for years since starting school, years squared, and years cubed. To account for exposure to marriage risk, we use a measure of months since the first monthly interview and months squared.
In addition to the aforementioned controls, we examine many other theoretically motivated measures.4 However, because these measures are not statistically significant and including them does not change our estimated relationship between parental marital quality and children’s behaviors, for parsimony we do not include them in the analyses shown.
To investigate children’s behavior, we treat education and marriage as transitions occurring over time, from being in school to stopping school and from being never married to marrying for the first time. We use event-history techniques to estimate these discrete-time hazard models (Allison 1982). Because the outcomes in question have only one destination state and are measured as dichotomous variables, logistic regression is an appropriate estimation technique (Allison 1982). Person-years of exposure are the unit of analysis for education and person-months for marriage. We start the hazard of stopping school in 1996 or the first year a student is enrolled if they had not yet started in 1996, and the hazard of marriage the first month of the prospective data collection. Individuals are clustered within households and within neighborhoods, so we estimate three-level hazard models.5 In the CVFS data, neighborhood clustering generally accounts for very little of the overall variance; and in these models, the neighborhood interclass correlation coefficient (ICC) was 1% or lower.
We investigate potential gender differences by also estimating separate models for sons and daughters and pooled son-daughter models with interaction terms. We do not find any significant gender differences in our key independent variables, so we present the pooled models.
Table 2 shows models of the relationship between parents’ marriage quality and children’s education (stop attending school). The hazard model coefficients displayed are the multiplicative effects on the odds of marriage—the odds ratios. We start with the positive dimension of the parental marriage. Looking at our most parsimonious model (Model 1), we see that parental emotional bond (love) has a negative relationship with the hazard of stopping school. Children whose parents reported loving each other more were less likely to stop attending school (i.e., had higher educational attainment) than children whose parents reported less love. In this model, we also see that older children were more likely to stop school, and there was no difference in the hazard for boys and girls.
In Model 2, we add our measures of factors known to influence parental marital quality and children’s outcomes. The relationship between parental marital quality and children’s education is robust to the inclusion of these additional controls for the ethnicity, parents’ experiences before birth, their marriage, household characteristics, and the current educational context. As expected, many of these factors are related to children’s education themselves. Chhetri-Bahun, the ethnic group that has historically held the highest social status and privilege, had a lower hazard of stopping school than Dalits, Hill Janajati, or Terai Janajati. Additionally, we find that children whose parents had gone to school and who lived in wealthier households (as measured by consumer durables) had a lower hazard of stopping school. Children with more siblings had a higher hazard.
In Model 3, we turn to our measure of marital conflict and find that it is positively related to the hazard of stopping school and that relationship is robust to controlling for other factors (Model 4). Finally, in Model 5, we include both measures of parental marital quality and find that the relationship between parental love and children’s education is independent of the amount of marital conflict the parents report.
One potential limitation is that these measures of marital quality refer to one time period and that it is possible, and in fact probable, that the parental marriage changes over time, making these measures less accurate as time passes. This potential is exacerbated by looking over a 12-year period. Models with an interaction term between parental love and years since 1996 provide some evidence of this: the sign of this interaction term is consistent with the idea that the 1996 measure of marital quality is less reflective of the marriage as time goes on (i.e., that measurement error increases over time). However, the interaction term itself is not statistically significant. Of course, this finding is also consistent with other hypotheses, such as a diminishing cumulative effect model.6
Next we turn to our analysis of marriage behavior (Table 3). Model 1 is the most basic model and shows that high parental affection was significantly related to children’s marriage timing, delaying the transition to marriage. The more positive the relationship between the parents, the later their children married.
In Model 2, we add measures of factors previous research has found to be related to children’s marriage timing. We find that even as some of these factors are related to children’s marriage timing—in particular, parents’ education and the current educational context—the relationship between parents’ emotional bond and children’s marriage timing remains unchanged.
Gender is significantly related to the hazard of marriage, with daughters marrying earlier than sons, but we find no significant differences in the relationship between parents’ emotional bond and children’s marriage timing by gender. This finding is entirely consistent with previous research on intergenerational influences on marriage timing, which in spite of strong gender differences in the overall pace of marriage, almost never identifies significant gender differences in associations between parents’ characteristics and the pace of marriage across many settings (Marini 1978; Thornton and Lin 1994; Thornton et al. 2007).
Next we examine the relationship between negative dimensions of parents’ marital quality and their children’s marriage timing (Model 3 showing the base model and Model 4 including additional measures). As we predict in this setting, parental marital conflict accelerated entry into marriage, and this relationship is independent of the other factors known to influence children’s marriage timing. Finally, in Model 5, we include measures of both dimensions of the parental marriage quality and see that they maintain their strong, independent effects.
Decades of empirical research has provided evidence that children’s transition to adulthood is influenced by their parents’ experiences (e.g., McLanahan and Bumpass 1988; Thornton et al. 2007) and that the emotional quality of a marriage has wide-reaching consequences (Cherlin et al. 1995; Malinen et al. 2010). Yet we know little about how this emotional dimension of the parental home influences children’s transition behaviors. Although this is an important theoretical question, rarely do we have the empirical tools to investigate it. Because the CVFS includes measures of the emotional dimensions of parents’ marital quality in an intergenerational panel study covering more than 10 years, we are able to investigate the association between variations in emotional dimensions of parents’ marriage and subsequent variations in their children’s education and the timing of their children’s marriages.
The relationship between mothers and fathers has a substantial, enduring association with the pace at which their children subsequently leave school and marry. Parents’ marital quality is multidimensional, encompassing both affection/love and conflict/violence as independent dimensions of the relationship. We find that children with parents who reported more affection/love for each other stayed in school longer and married later, whereas those whose parents reported spousal violence left school earlier and married earlier (i.e., left the parental home earlier). These findings, based on simple measures of marital quality, are what we expect based our setting-specific framework and on the literature documenting distinct dimensions of marital quality (Allendorf and Ghimire 2013; Bradbury et al. 2000; Umberson et al. 2005). Couples with a more positive emotional bond may be supporting, encouraging, and enabling of their children’s education because they are investing more in the quality of their children rather than quantity. Regarding marriage timing, these findings support multiple possible mechanisms, including the possibility that parents’ love for one another may spill over to their children in such a way that the family spends more time looking for a spouse, perhaps because they have higher expectations, or that the love between the parents creates a comforting home environment that young people are reticent to leave.
Parental marital conflict may be related to children’s transitions to adulthood behaviors because conflict between parents lowers the quality of the parental home, thus increasing young people’s motivations to leave home. Because marriage is virtually the only acceptable long-term way for young people to leave the parental home in this setting, parental conflict hastens leaving school and entry into marriage.
Note that we find these strong relationships even though our measures of parental marital quality are simplistic. Although multi-item repeated measurement over time might be desirable, this study is an important contribution because we have independent measurement from each parent (as opposed to children’s reports of their parents’ marriage), and these single items still reveal important insights. Research using more thorough measures of marital quality is crucial given that it will likely yield evidence of even stronger long-term, intergenerational influences and will certainly reveal more information on the nature of these relationships.
Of course, the social context of our investigation is specific. Because divorce remains rare in Nepal, particularly in the parental generation, parental marriages remain intact even when marital quality may be quite low. Independent living and premarital cohabitation are also rare, so marriage is a child’s primary long-term opportunity to leave their parental home. These setting-specific differences produce different expectations for the consequence of variations in parental marital quality. This study adds to the existing literature by emphasizing the importance of setting-specific studies and hypotheses. At the same time, our study also provides evidence of the long-lasting influence parental relationships have on their children across a wide range of settings.
Documenting the intriguing finding that the response to a specific family/parental condition depends on the social context raises many important research questions. High priority among these is whether the different findings are due to different mechanisms or a result of different socially acceptable behavioral options available to individuals. Future research that can investigate the specific mechanisms across dramatically different settings is necessary to separate these possibilities.
The wide-ranging, intergenerational consequences of the emotional dimensions of parental relationships go beyond intriguing. Across the globe, including in South Asia and many other highly populated regions, we are witnessing dramatic transitions in marriage. Age at marriage has increased throughout South Asia (Yeung et al. 2018). There is widespread change from “arranged” marriage toward “love” marriage along with hybrid marital arrangements in which both parents and children participate in spouse choice (Allendorf 2013, 2017; Allendorf and Pandian 2016; Ji 2013; Netting 2010; Rindfuss and Morgan 1983). In addition, divorce is rapidly becoming more common (Jennings 2016). Together, these factors are changing the marital context within which childrearing takes place. Our findings are consistent with the conclusion that these changes in the nature of parental marriages are likely to have long-term consequences for their children across multiple dimensions of social life.
At the same time, the institution of marriage still varies considerably within South Asia. Differences in economic and educational contexts as well as important cultural legacies may explain some of this variation (Desai and Andrist 2010; Yeung et al. 2018). The findings presented here demonstrate that research on the connection between parents’ marital relationships and their children is a high priority. This may help us better understand the consequences of the variability in marriage in this region.
The strong associations with subsequent education and marriage documented here provide evidence that it is also possible that the emotional dynamics within parental marriages may influence their children in other domains of social life, including work, family, recreation, and ideation. Thus, we argue the findings described here should motivate a broad range of research into the emotional basis of behavior and the high potential for intergenerational consequences for multiple dimensions of children’s lives, potentially shaping all aspects of their health and well-being.
This research was generously supported by the National Institute of Child Health and Human Development (R01 HD032912 and R24 HD041028). We gratefully acknowledge the efforts of Cathy Sun at the Population Studies Center for data management assistance, staff at the Institute for Social and Environment Research–Nepal, and the residents of the Western Chitwan Valley for their contributions to the research reported here. The authors alone remain responsible for any errors or omissions.
Children who died after 1996 are included in the analysis of education, although child mortality was very low during this period, making the issue trivial: 11 children died by 2008, only 1 of whom had dropped out of school before her death. The remaining 10 were censored at their death (n = 11). Divorce is extremely rare in this setting, and in 1996, no ever-married women were currently divorced from their most recent husband. Twenty-four sets of parents from the education analysis and one set of parents from the marriage analysis divorced after 1996. We exclude 4% of children from the education analysis and 14% from the marriage analysis because of missing data on at least one variable, most of which were for household structure and parental education.
Surveys were conducted in Nepalese. We provide English translations of Nepalese wording.
Although these household measures reflect processes that happened before our measures of parental marriage quality, because the processes that produce both aspects of the parental home occurred over time, we cannot be sure of the temporal order of these measures. We include them to be conservative in our approach and note that doing so does not influence the observed relationship between parental marital quality and children’s behavior.
Regarding parental experiences, we examine a measure of exposure to media: specifically, watching TV. For current community, we use geographically weighted measures of the proportion of teachers who were female and the proportion of students who were female and other dimensions of the family’s community context in 1995 (whether the family lived within a five-minute walk of a health service provider, bus stop, or market). For mother’s and father’s childhood communities, we create measures of whether each parent had a school, health service, employer, market, or bus stop within an hour’s walk at age 12.
The 2,714 children in the first analysis sample (used to study education) live with 1,168 sets of parents in 151 neighborhoods. The data include 116 “cousin” sets in which the parent set is not equivalent to the household. The 667 young people in the second analysis (to study marriage) live with 437 sets of parents in 141 neighborhoods. The data include 4 “cousin” sets in which the parent set is not equivalent to the household. Clustering at the household or parent level yields the same results.
To shed further light on the potential problem arising from an increasing lag between the measure of parental marital quality and children’s behavior, we also estimate hazard models of starting school—an event that would have occurred much closer to the measurement of parental marital quality—and find results that are substantively identical to those shown in Table 2. Although not a measure of the transition to adulthood, starting school is a measure of education that is likely influenced by parental marital quality through similar mechanisms as described earlier. Furthermore, when this analysis is limited to children born after 1996, the measures of marital quality are completely exogenous to the measures of child’s schooling.
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