Family Structure, Parental Practices and High School Completion

1. Introduction

Although South Africa has invested in access to instruction since the demise of apartheid, enquiry suggests that the majority of young people however practice not consummate high school, with some scholars calling the high dropout rates a crisis (Weybright et al. 2017). It is estimated that fifty% of learners who enter Form i at a particular time leave without completing high school (Spaull 2015). This condition quo suggests that there are still pregnant barriers in educational attainment prompting the following questions: What are some of the factors that influence high school completion and why are some learners more successful than others? Existing research has attempted to answer these questions, focusing mainly on the association betwixt educational attainment and schoolhouse quality, demographic factors, family background, in item, parental didactics, also as sexual behaviour (Bengesai et al. 2018; Weybright et al. 2017; Spaull 2015; Branson et al. 2014; Marteleto et al. 2008). Even so, the effect of other family dynamics, such as family structure, and in particular, family structure disruption is less explored.

In recent years, and peculiarly so in Due south Africa, family structures have been dramatically transformed, a state of affairs that has been partly attributed to the turn down in wedlock rates, the rise in non-marital fertility equally well as divorce rates (Posel and Rudwick 2013; Chuong and Operario 2012). South Africa also has a legacy of family disruption, which was orchestrated by the apartheid organisation through by laws, urban housing policy and the creation of the homelands (Budlender and Lund 2011). Appropriately, the country has i of the lowest rates of co-resident parents in the world (Hall and Sambu 2018). For instance, the Full general Household Survey of 2016 revealed that only 25% of Southward African households were 'traditional' families consisting of married parents and their children (Statistics South Africa (Stats SA) 2017). These family dynamics have been further compounded past the HIV epidemic, which has left many children orphaned (Chuong and Operario 2012; Monash and Boerma 2004). Consequently, many children today reside in diversified family unit contexts, which has implications for their developmental outcomes, including educational attainment.

Globally, some studies have recognised family construction as a risk cistron for children's educational outcomes. Although mainly dominated by the West, (Cid and Stokes 2013, Uruguay; Monserud and Elder 2011; Martin 2012, USA; Frisco et al. 2007, United states), this body of literature has consistently shown that children in 'intact' families have improve outcomes across different educational indicators. When examining the upshot of family structure on school dropout and falling behind, Cid and Stokes (2013) found that children raised in not-traditional families (without both biological parents) had negative outcomes, with more adverse effects for girls. Others accept also shown that growing upwards in single-parent families might reduce the chances of completing high school and enrolling in post-secondary education (Monserud and Elder 2011; Astone and McLanahan 1991). Similarly, the few studies from sub-Saharan Africa seem to concur with these findings. Using Demographic and Health Survey data from 26 countries, Amoateng et al. (2017) institute that children built-in into monogamous families completed more years of schooling than those in polygamous or single-parent families. Abuya et al. (2019) found that Ghanaian children in two-parent households were most likely to be in the right age for the class they were enrolled in relative to those from single-parent families or those who lived with guardians. In S Africa, Ndagurwa and Nzimande's (2016) study examined the upshot of family structure on school enrolment and dropout, focusing on children aged seven–17 years, while Anderson (2003) explored the association between family structure and school enrolment besides as the highest grade completed per year. Both of these studies found that children in co-resident parent families had the most favourable outcomes.

Several theoretical frameworks have been used to explicate how family structure affects educational attainment. Cartoon on the sociological work of Coleman (1988) and Bourdieu (1986), some scholars accept theorised the human relationship between familial resources and educational attainment in terms of majuscule, suggesting that a child'south wellbeing and success in life is contingent upon the different forms of capital that are transmitted past their parents since they are dependent on them for resource (Humble and Dixon 2017; Martin 2012). Within this framework, family background is considered a strong form of upper-case letter that has three interrelated components; human being capital, fiscal capital, and social capital. As Martin (2012, p. 34) notes, "families must have potent social capital letter to transmit the necessary financial and human capital for their child'due south human uppercase development".

Becker's household theory, which posits that children'southward educational attainment is a valued commodity in the family unit, has also been influential in the research on the family structure (Abuya et al. 2019). To produce this commodity, parents invest inputs such as fourth dimension and money (Monserud and Elder 2011), and past extension, the quality of the output depends on the quality of the inputs. For example, lone parenthood is frequently likened to low socioeconomic status, social isolation, and lower parental support for children (Amoateng et al. 2017; Martin 2012; Uwaifo 2012). This is mainly because females, who historically are less educated and probable to be employed in less prestigious occupations (Schatz et al. 2011), caput nearly single-parent families, particularly in S Africa. Thus, it is causeless that children from single-headed or non-resident parent families are likely to suffer from economic vulnerability equally well as structural deficiency related to lack of parental involvement in their welfare (Monserud and Elder 2011; Martin 2012). On the contrary, co-resident parents are seen as more bonny in transmitting socioeconomic resources to their children (Cid and Stokes 2013).

While previous studies on family construction contain numerous insights, there are pregnant gaps that need to be addressed. For instance, the family is an institution that is continuously evolving. This is much more pronounced in South Africa where the family unit construction is consistently showing changing characteristics, with double orphaned children, female-headed families and non-marital fertility existence a persistent issue (Sooryamoorthy and Makhoba 2016; Chuong and Operario 2012; Madhavan and Schatz 2007). Given the decreasing likelihood that children volition stay in 'intact' families across their life course, it is critical to understand how these transitions may affect their outcomes. Moreover, almost of the research on family unit structure has relied on snapshots or 'window observations' (Dominicus and Li 2011; Lee and McLanahan 2015) of family unit situations taken at ane point in a immature person's life. These observations are and then extrapolated to the entire childhood, which is likely to exist misleading and insensitive to the demographic shifts in family structure. The aim of this paper is, therefore, to motion beyond this static examination of family structure, to an approach that recognises family structure transitions.

Family Construction Transitions and Children's Educational Outcomes

Although scholars such equally Furstenberg and Seltzer (1986) started speculating about the effect of family construction alter (too called instability) on children'south outcomes as early equally the 1980s, much less attending has been paid to this aspect (Fomby and Cherlin 2007) especially in the empirical studies from Sub-Saharan Africa, including Due south Africa. Thus, the influence of family structure transitions is a much less theorised topic in South Africa, and most of what is known emanates from contexts where socio-cultural norms may differ. This limitation notwithstanding, there is strong evidence internationally which has shown that changes in family construction can potentially produce stresses for children that are singled-out from the family structure (Goldberg 2013; Steele et al. 2009; Fomby and Cherlin 2007). This body of bear witness, which is informed by the family stress theory, argues that the disparities in child educational outcomes arise from the stress acquired by the family structure disruptions (Sunday and Li 2011; Fomby and Cherlin 2007). This is considering family structure disruption is likely to crusade a reduction in resource (fiscal and time) due to the absence of a parent in the same household or other harmful changes such as fluctuating changes in parental roles and family routines (Hampden-Thompson and Galindo 2015; Steele et al. 2009).

Taking this hypothesis to exist truthful suggests that family structure stability (i.e., absenteeism of changes) might but be as protective against negative outcomes (Sun and Li 2011). Put differently, a kid built-in to a single parent might be ameliorate off if the parent does non cohabit or marry. This is considering children who exercise not experience any family structure disruptions are likely to be protected from the emotional stress associated with dramatic changes in parenting practices (Fomby and Cherlin 2007). Thus, consistency over time might also be as important for immature people'south developmental outcomes. Withal, almost of the studies on family unit structure instability have not considered this different perspective, choosing instead to focus on measuring the number of family unit structure changes and the marital condition of the resident parents (Hampden-Thompson and Galindo 2015; Fomby and Cherlin 2007) as more significant than the "blazon of family modify (e.g., go out versus entrance of a parent" (Lee and McLanahan 2015). In a country with the everyman rates of co-resident parents and failing nuptiality, capturing the residency of parents might be crucial in measuring the interaction between family unit construction and children'south outcomes.

A further limitation in the literature on family unit instability relates to whether all family unit structure changes are equally harmful to children (Lee and McLanahan 2015). This aspect has non been sufficiently addressed in prior studies every bit the tendency has been to compare children from alternative family structures with those from co-resident biological parent families. While comparing co-resident families and those experiencing transitions gives united states of america insights into the effect of family structure disruption, it might obscure some of the dynamics and mechanisms through which instability affects educational outcomes. As Lee and McLanahan (2015) put information technology, a child cannot move out of a two-parent family if they resided with a unmarried parent or had no residential parent. Likewise, a kid cannot move into a two-parent family if he or she already lived with both parents, except in cases of step-parent co-residence (Lee and McLanahan 2015).

Our study, therefore, will extend the existing literature in several means. Starting time, we examine whether family construction changes are associated with loftier school completion. In particular, we focus on the following family structure disruption statuses: between non-disrupted single-parent, two-parent and non-resident parent families and the disrupted counterparts. Thus, we focus on parents' residential status rather than their marital condition. To our noesis, this is the get-go study in South Africa that has examined this aspect and will, therefore, extend the existing international literature (for instance, (Sun and Li 2011; Lee and McLanahan 2015)) past providing an African perspective. 2d, we will compare the effect of changes (moving in and moving out of parents) on subgroups that were similar at the first of the observation period (eastward.g., the moving out of a parent from a lone parent family construction vis a viz a stable lone parent family unit). We hypothesise that non all transitions are the same. For instance, moving from a lone parent structure to a co-residential spousal relationship might increase admission to parental resources such as fourth dimension and money. (Lee and McLanahan 2015). Yet, it might too interrupt family routines, leading to stressful parent–child relationships (Fomby and Cherlin 2007). Similarly, while moving out of a co-residential union is expected to be harmful to children every bit it potentially reduces the family's resources; however, such a move might be beneficial to immature people in situations where at that place is disharmonize in the parental relationship.

2. Methods

2.1. The Data

Data for this written report was drawn from the five waves of the National Income Dynamic Study (NIDS) a longitudinal panel survey of the dynamic construction of households and changes in living conditions in South Africa (Murray et al. 2010). Individuals who were anile 12, 13 and 14 at wave one (2008) were singled out. We acknowledge that our sample falls curt in capturing changes that might have occurred in early childhood (i.e., below the age of 11), which have been shown to have a significant influence on children's outcomes. Nonetheless, our sample is still superior to snapshot measures of family construction that have been used in the majority of the earlier Due south African studies.

Given that high schoolhouse completion cannot be achieved before the age of at to the lowest degree eighteen or xix in S Africa, we gave a few more years for the sample to complete the high school cycle, considering that some might accept started school tardily or repeated a grade. Thus, the youngest in our sample were at to the lowest degree anile 21 and the oldest 23 past wave v (in 2017). The NIDS used a stratified two-stage cluster sampling, which involved outset selecting 400 Primary Sampling Units from 53 Commune Councils in the state. From these, 8 non-overlapping clusters of dwelling units were systematically selected.

Analysing family structure changes requires detailed longitudinal information, and the NIDS dataset is well suited for this as information technology contains information about the family's living arrangements, household characteristics too as children's educational characteristics, which are the key explanatory variables in this study. However, while the console nature of this data controls for unobserved characteristics that might influence the association between family unit structure and educational outcomes, it also raises other challenges such as compunction betwixt waves which is likely to bear upon on the validity of the study (Baigrie and Eyal 2013). For case, compunction between wave one and wave 2, moving ridge 2 and wave 3 also equally wave 3 and moving ridge iv was 21.95%, 15.82%, and 13.75%, respectively (Chinhema et al. 2016). Assuming this attrition occurred non-randomly, selection bias would have been introduced every bit the remaining sample would not accept been representative of the target population. To address these problems, we used panel weights provided in the NIDS dataset to arrange for attrition betwixt waves.

two.2. Dependent Variable

The consequence of interest in this study was high schoolhouse completion (0 = No, i= Yes) by the ages 21–23 or earlier. This outcome was structured using the information available pertaining to the highest level of education attained by wave v in 2017.

2.3. Independent Variables

Family structure transition was measured as the type of family structure modify a child experienced since the ages 12–xiv years. We chose these detail age groups, given that our focus was on high school completion. Much younger age groups surveyed in 2008 would not take completed high school past 2017.

In the NIDS data, respondents were asked questions pertaining to the residential status of the parents. If there was any change in the number or identity (resident father or mother) of the parents in the household from one wave to another, the child was considered to have experienced a family structure change. Using this information, nosotros classified children as residing in ii biological parents, single parent and no parent family structures at moving ridge 1. We had initially sought to allocate single-parent families as single mother and single father families; however, due to the pocket-size sample sizes for the begetter only category, nosotros decided to plummet these into single-parent families. To increase the sample size, we also used information on whether the mother or father was alive at each wave. The breakup of these family structures at each wave is presented in Table one.

Using these composite variables at Wave 1 (both parents, lone-parent and non-resident parent), and tracking the children through to Wave iv, we then identified the following types of family unit structure transitions: (a) stable co-resident parent families (b) stable lone-parent families and (c) stable non-resident parent families. We did not include wave 5 for the family structure change variable given this change would take happened in early machismo. For families that experienced changes between Wave i and Wave 4, we identified the post-obit structures: (d) disrupted co-resident parent families (e) disrupted solitary-parent and (f) disrupted not-resident parent families. Acknowledging that family structure transitions differ, and the moving in of a parent family might have a different effect on children than the moving out, we besides conducted a subgroup analysis of individuals who experienced the: (i) go out of a parent(south) from a co-resident parent family vs. those who remained in stable co-resident parent families; (ii) leave of a parent from a lone-parent family vs. stable alone-parent families; (three) entrance of ane or both parents vs. stable non-resident family structure and (four) archway of a parent to a lone parent or not-resident family structure. The breakdown and percentages of the family structure changes that the young people in our sample experienced is shown in Tabular array ii beneath.

Table 2 presents the young people's family construction changes across four waves (moving ridge 1–4 only). The results evidence that 24.ane%, did not reside with either of their parents, while approximately 21% lived with a lone parent, well-nigh of whom were the mothers. Only 14.vii% of the young people lived in undisrupted two-parent households. We also notice that approximately 38% of the immature people had experienced family construction disruption, 12.6% had experienced the exit of a parent from a 2-parent family structure, 10.0% of those who did not reside with any parent at moving ridge ane had a parent move in, while 17.7% of children in lone-parent families experienced the exit of a parent.

In the subgroup analysis, we notice that 10.4% of young people who resided with both parents had experienced the get out of a parent, while xi.8% of those in lonely-parent family unit structures experienced the moving out of a parent. Out of those who resided in lone-parent or non-resident parent family unit structures eight.2% had a parent move in, six.vii% of those who were in non-resident parent family unit structures also had a parent moving in. Less than 2% of young people in our sample experienced multiple transitions, which involved for instance, the get out of mother and archway of a father of vice-versa, the exit of both parents in one wave and the entrance in another. This group was non included in the statistical analysis given the small sample size

2.3.1. Family Resources

Family unit income has been identified equally ane of the cardinal indicators of social capital and familial resources associated with children's better life outcomes (Assari 2018). Therefore, to gauge the association betwixt resources and family unit structure disruption, we calculated the changes in household income between Waves i and Wave 4. A positive change in household income between the two waves was coded equally (one) while a negative change was coded (0). Prior studies have also included variables such equally female parent's and father'south didactics equally measures of family resources (Tsiplakides 2018; Li et al. 2019). Nevertheless, due to a large number of missing values on both mother and father's education, nosotros opted to combine both mother and begetter's education into a composite variable, parental education. For instance, if the mothers' highest form was chief (value = 0) and male parent's was consummate secondary (value = ii), parental education was computed as 2. Nosotros admit that this categorisation has the potential to mask significant heterogeneity as information technology does non differentiate between mothers and fathers' instruction. However, given the information limitations, we worked on the plausible supposition that at least one parent in that family had that highest level of educational activity. This modified parental education increased the sample size to 1234. Once again, considering that most of the missing values for both mother and father's educational activity were on children in stable co-resident families, we decided to include missing values every bit a dummy variable. Thus, our parental educational activity variable had the following categories: (ane = chief or less; 2 = some secondary teaching; iii = loftier school; and, iv = missing).

two.3.2. Child's Academic Characteristics

1 potential driver of educational attainment which is likewise a significant characteristic of the Southward African teaching system is grade repetition (Branson et al. 2014). As such, we also included a dummy variable that indicated whether a kid had repeated a grade or non (0/1).

two.4. Control Variables

Demographic factors such as historic period, population grouping/race and identify of residence were used as controls. Owing to the low sample sizes for the following racial categories (Blacks, Indians and Whites) we opted for a two-category population group variable to represent (0 = 'Other', 1 = Black S African). Research has consistently shown that Black South African students take worse educational outcomes relative to their peers from the other population groups. Therefore, we reasoned that this categorisation would at least give us data about this detail risk group. We use race in this study as a social construct rooted in S African history of apartheid, and which continues to bear upon on educational attainment.

ii.5. Analytic Strategy

Given that our outcome variable, loftier school completion was binary, nosotros used logistic regression models. Nosotros estimated iii models for the type of family structure transition. In Model i we estimated the effect of any changes in family structure and household income. Model two included family structure changes, household income changes, repeating a grade and all the demographic controls, while Model iii controlled for parental educational activity in addition to all variables included in Model 2. We similarly synthetic separate models for the subgroups, to capture the event of moving in and moving out of parents across the 3 family structures identified at Wave 1. As recommended by Wittenberg (2009), post stratified weights were practical to make the sample representative of the Due south African population while adjusting for nether or oversampling. Nosotros too used the svy commands in Stata v.14 to suit for the stratified sampling.

3. Results

3.1. High School Completion by Family Structure Transitions and Changes in Household Income

Figure ane shows the distribution of the sample by educational attainment. Nosotros observe that approximately 46% of the immature people had at to the lowest degree 12 years of schooling, followed by nigh 20% with at least 11 years of schooling. Simply a few immature people (about three%) had at least mail service-secondary education (more 13 years).

Table 3 presents the descriptive statistics of the distribution of high schoolhouse completion by family structure and disruption statuses and household income changes. Approximately 50% of the immature people had completed high school by the ages 21–23, while immature people from undisrupted two-parent family structures and disrupted lone-parent families had the most favourable outcomes. These results besides show that young people from undisrupted lone-parent and disrupted co-resident parent families were the least probable to consummate high school, while those from non-resident and disrupted non-resident parent families were more similar in terms of high school completion. This analysis, therefore, provides some initial evidence that family construction disruption could account for high schoolhouse completion in S Africa. We also detect that most of our variables, except for race and household income modify, were significantly associated with high school completion.

3.2. Family Construction Instability and High Schoolhouse Completion

Tabular array 4 presents the logistic regression estimations for high school completion. In Model 1, nosotros estimated the outcome of two predictors: family construction changes and household income change. The results demonstrate that, except for young people from disrupted lone-parent families, there are significant differences in loftier school completion betwixt undisrupted two-parent families and all other types of family unit structure transitions. Relative to young people in undisrupted co-resident family structures, those in disrupted or other undisrupted family structures were less likely to complete high school (OR = 0.49–0.58). Of notation from Model 1 is the fact that young people from disrupted co-resident families had the to the lowest degree favourable outcomes (OR = 0.49). We besides find that those who had a negative change or no change in income had increased odds of completing high schoolhouse, although this effect was not statistically significant. Model 2 included the central controls (gender, race, place of residence, and whether or not a child had repeated a course). We find that the associations for all the other family structure types adulterate to non-significant except for the disrupted two-parent families who were 46% less likely to complete loftier school relative to those in undisrupted co-resident parent families. Among the controls, repeating a form significantly reduced the probability of high school completion by a cistron of 0.24, while being female increased the odds by 44%.

When controlling for parental education in Model 3, young people from not-disrupted non-resident parent families and disrupted co-resident parent families were up to 51% and 49% less likely to complete high school relative to those in undisrupted co-resident parent families, respectively. Gender and repeating a form also significantly accounted for high schoolhouse completion while offspring of parents with at to the lowest degree some secondary school (aOR = 1.53) or consummate secondary education (aOR = 3.47) were more likely to consummate loftier school relative to those whose parents had principal education or less. Nosotros did not find any statistical significance for the missing category.

The second office of our analysis involved distinguishing between the effect of the exiting or entrance of a parent on high schoolhouse completion. Tabular array v presents this subgroup analysis

The first approximate in each subgroup is from a model which only included ii predictors, i.e., the subgroup and household income change, while the 2nd estimate was taken from a model which included the controls used in Model two in Table 4. The third estimate included all the controls used in Model three (Table 4). In the beginning model, we find that immature people from two-parent families who experienced the exiting of one or both parents were less likely (OR = 0.51) to complete high schoolhouse relative to those who did not experience whatever disruption. We did not find any statistically significant effect on the other categories. In Model ii, the exiting of a parent from a co-resident parent family unit construction was still significantly associated with high school completion (aOR = 0.54). A somewhat surprising finding was that immature people who experienced the moving out of a unmarried parent and hence were left with no resident parent were 75% more than likely to complete high school relative to those who resided in undisrupted single-parent families. In Model three, none of the family structure change subgroups were statistically significant.

4. Give-and-take

In this study, we have examined the effect of family structure changes on loftier schoolhouse completion. Nosotros specifically considered whether the outcome differed past types of disruption, including the exiting or entrance of a parent. The present study is the first (to our knowledge) to examine the effect of family construction changes on educational outcomes in S Africa, although there have been several other studies (for example (Ndagurwa and Nzimande 2016; Branson et al. 2014; Anderson 2003)) that have examined the effect of family structure on educational outcomes.

Pedagogy is a crucial element in human capital letter evolution, the ground for skills development and is both a catalyst and essential for the accomplishment of all Sustainable Development Goals (SDGs) (Sterling 2016). High schoolhouse completion is critical as it is the path towards mail service-secondary school education and ultimately, the labour market (Bengesai et al. 2018; Clark and Mathur 2012). For example, there is empirical evidence which suggests that individuals who do not graduate from loftier school have dour economic prospects (Stats SA 2014). Moreover, educational attainment has been linked to differences in physical and psychological wellbeing. Thus, poor educational outcomes can potentially lead to lead to other types of disadvantage (Steele et al. 2009). Because the importance of teaching in shaping adult outcomes, enquiry must explore how information technology is distributed and factors that might impact on its distribution.

Although access and participation in educational activity has improved in Southward Africa since the demise of apartheid, the analysis in this study reveals that almost 50% of the immature people had not completed high school by ages 21–23. This is likely due to the high dropout rates that seem to scourge the South African didactics system (Weybright et al. 2017). For instance, information technology is estimated that the mean years of schooling in Southward Africa is nine.9 years (UNESCO Institute for Statistics 2013), suggesting that a significant proportion of young people do not progress across the Course 10 level (Spaull 2013). We also constitute that a considerable number of children do not grow upwardly in traditional nuclear families, confirming both official statistics also every bit earlier studies on family structure in South Africa (Stats SA 2017; Sooryamoorthy and Makhoba 2016).

Regarding family construction disruption, a cardinal finding from our study is that individuals who do not reside with both their parents are upward to fifty% less likely to consummate loftier schoolhouse. This outcome is more pronounced for immature people from stable non-resident parent families likewise as those in disrupted co-resident parent family structures. How can these results exist interpreted? First, consistent with past research, our findings reinforce the notion that mayhap what 'counts' is residing with both parents (Hampden-Thompson and Galindo 2015; McLanahan and Sandefur 1994) who often accept greater resources at their disposal than in other family unit structures. Co-resident parents are likely to have a dual income and can share time to spend with their children relative to unmarried parents. For South Africa, our findings are especially important given that majority of young people practice non reside with both parents, with a significant proportion living in not-resident parent family structures (Stats SA 2017; Sooryamoorthy and Makhoba 2016; Chuong and Operario 2012). These disparities are too stratified by race and socioeconomic status. To illustrate, Stats SA (2017) reports that only 21% of African children resided with both parents relative to 67% and 61% of the White and Indian children, respectively. Thus, disparities in family unit structure add another layer of inequality which should be of business to policymakers in South Africa.

Our findings from the subgroup assay likewise confirmed the hypothesis that not all family structure changes have an equal effect (Lord's day and Li 2011; Lee and McLanahan 2015). For young people who resided with both parents at ages 12, 13 and 14, the exiting of a parent from a two-parent family structure significantly reduced their odds of completing high schoolhouse past upwardly to 50% when compared with those who remained in stable co-resident parent families, although this effect became insignificant when parental didactics was added. On the contrary, and rather surprising was the fact that the moving out of a parent from a lone-parent family construction either due to death or other reasons non provided in the data fix, increased the odds of completing high school. One interpretation for this is that a pregnant number of South African children live in extended families, with relatives such as grandparents, uncles and aunts (Hall and Mokomane 2018). For the Black South African racial group, this is especially the instance where the female parent is unmarried. Hence, in that location is a possibility that in the outcome of the expiry of the parent, or migration due to work, young people from the lone-parent household might be less afflicted by the change as the extended family might provide a rubber net for them (Foster 2000). In other words, there is the possibility that the presence of boosted adults, especially in Blackness African extended families might fulfil the same support found in co-resident families. Withal, these explanations have not been empirically tested in S Africa and thus remain speculatory. At that place is, therefore, demand for further research into why the exiting of a parent from a solitary parent family structure might be beneficial to young people. It might be as important to investigate whether the timing of these events (i.e., the exit of the parent) might explicate the variation in the effect of non living with both parents between immature people who were in non-resident parent families at Wave i, and those who experienced this change during the ascertainment period.

The fact that high school completion was not attributable to household income change was rather surprising as research has long established income-based inequality in educational outcomes (Assari 2018; Branson et al. 2014). In the absence of alternative explanations, we attribute the insignificant effect of household income modify to the possibility of multicollinearity between with family unit structure change. It is probable, changes in family unit construction are directly associated with changes in household income, in which instance, the significance of the coefficient might be misleading. Other factors that were found to exist insignificantly associated with high school completion are race and identify of residence.

The link betwixt gender and educational outcomes is no longer questioned. There is robust research which has shown that females are progressing through education faster than males, although in some cases, the gender differences are pocket-sized (Lam and Branson 2014; Eloundou-Enyegue et al. 2009). Thus, our study confirms these prior studies which have identified a female advantage in mean years of schooling.

Grade repetition is a common practice in many countries (UNESCO Institute for Statistics 2012). In South Africa, it is often considered a valid corrective action when the learning objectives of a particular grade take not been achieved (Branson et al. 2014). However, the testify regarding the association between grade repetition and educational attainment is inconclusive, with some studies suggesting that it is beneficial for the student, while others have found the opposite (Branson et al. 2014; Ikeda and Garcia 2014). There is a possibility that repeating a grade may exist discouraging to some individuals and affect their attitudes towards schoolhouse, leading to dropout. However, if pedagogically effective, it may improve the acquisition of noesis, leading to increased retention, although delaying completion of the schooling bike. Nonetheless, in terms of this study, fifty-fifty if they persist, individuals who repeat grades are well-nigh likely to fall backside in terms of class level, perhaps explaining why they had not completed high school by the given time.

Parental education has been shown to be 1 of the strongest determinants of children'southward educational outcomes. It is ofttimes used as a proxy for socioeconomic status and has been shown to influence children'due south outcomes (Martin 2012) through financial investments in children's pedagogy besides as the transfer of skills and habits to their children through behaviour modelling (Hampden-Thompson and Galindo 2015; Chevalier et al. 2013). Better educated parents are besides knowledgeable about the returns from education and therefore might be willing to invest more money in providing quality instruction for their offspring (Erola et al. 2016). Expectedly, nosotros also constitute that the offspring of parents who had some secondary level teaching or completed high schoolhouse had the all-time educational outcomes. This suggests that the parent'southward educational status, and by extension, the socioeconomic status might be more important than family structure instability (Chevalier et al. 2013). However, given the broad conviction interval for both the 'some secondary school' and 'complete secondary schoolhouse' categories in our analysis, these results should be interpreted with caution. As mentioned earlier, the probability of missing parental education was largely associated with family structure, in particular, among immature people who lived with both their parents. Information technology is as well possible that the composite parental didactics variable used in this study might take masked the real consequence of parental instruction.

In determination, our findings suggest that children who grow up in culling family structures and more so, those who experience a alter from two-parent family structures have poorer educational outcomes. Family instability acquired by the exiting of a parent has important consequences for loftier school completion even after controlling for other factors. Thus, the finding lends support to the notion that other family structures might exist 'incomplete institutions' which do not provide children with the necessary resources needed for success (Nock 1995). Nosotros, therefore, suggest that research on family unit construction in South Africa should consider the family construction changes that young people are exposed to during their life grade as 1 of the fundamental determinants of educational attainment. Such a refined understanding of the family as an institution in transition will too assist policymakers in coming up with holistic interventions to back up families also equally classify public resource in ways that tin can help reduce educational inequalities.

Although this study has some notable strengths, we acknowledge that there are some limitations. First, the study only focused on parent–kid relationships. We recognise that the diversity of the family goes beyond this. This might include co-residence with grandparents, stride-parents and step-siblings and it is recommended that futurity studies might besides consider these family structure complexities. Second, physical residence with parents was captured in this written report when the individuals were aged 12–14 years sometime (NIDS wave 1) and, hence might non fairly capture the dynamics of the family structure during an individual's childhood. These limitations notwithstanding, the present study has managed to highlight the prevalence of family structure disruption in South Africa and the clan with a detail educational outcome. Given that family structure disruption is a widespread phenomenon, the findings from this written report are not simply relevant to S Africa but will resonate in many other contexts where children are growing up in non-traditional and fragile families.

Author Contributions

Both A.V.B. and N.N. conceptualised and designed the research together. A.V.B. took the lead in data assay and writing up the paper while North.Due north. provided disquisitional feedback as well as editing. All authors accept read and agreed to the published version of the manuscript.

Funding

This enquiry received no external funding.

Acknowledgments

We would similar to thank the Southern African Labour and Development Enquiry Unit (SALDRU) for allowing us to apply the data from the National Income Dynamics Written report.

Conflicts of Interest

The authors declare no disharmonize of interest.

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Figure 1. Distribution of the outcome variable (NIDS moving ridge 5).

Figure one. Distribution of the outcome variable (NIDS wave 5).

Table 1. Breakdown of family structure by moving ridge (National Income Dynamic Study (NIDS) moving ridge 1–four).

Table 1. Breakup of family structure by wave (National Income Dynamic Report (NIDS) wave 1–4).

Family Structure Blazon	Wave 1	Wave 2	Wave 3	Moving ridge 4
Co-resident parents	537	345	353	275
Not-resident parents	380	135	199	251
Lone parent	477	646	785	819
Total	1394	1126	1337	1345

Table 2. Breakdown of family structure by disruption status (NIDS wave 1–4).

Table ii. Breakdown of family structure by disruption status (NIDS wave 1–four).

Parental Residential Status	Unweighted Freq.	%
Families that did not experience disruption
Undisrupted co-resident	242	xiv.vii
Undisrupted non resident	398	24.one
Undisrupted alone parent	347	21.0
Families that experienced disruption
Disrupted co-resident	207	12.vi
Disrupted non resident	164	10.0
Disrupted alone parent	291	17.seven
Subgroup
Go out of a parent(southward) from a co-resident family	171	10.4
Exit of a parent from a lone parent family	194	11.8
Entrance of a parent(southward) into a lone or not-resident family	135	8.ii
Archway of a parent into a non-resident parent family unit	110	six.7
Multiple transitions	27	1.6

Table 3. Descriptive statistics for high school and association with family structure change and other variables (NIDS, waves one–5).

Table 3. Descriptive statistics for high school and association with family unit structure change and other variables (NIDS, waves 1–five).

Variables	Unweighted Freq.	High Schoolhouse Completion	Sig.
Total	1649	49.vii
Family unit Structure Transitions			**
Undisrupted co-resident parents	242	55.0
Undisrupted non-resident parents	398	46.0
Undisrupted lone parent	347	41.5
Disrupted co-resident	207	43.0
Disrupted non-resident parents	164	46.three
Disrupted lone parent	291	48.8
Subgroup analysis
Exit of a parent(s) from a co-resident family	171	42.1	**
Go out of a parent from a lone parent family unit	194	50.0	**
Archway of a parent(s) into a lone or non-resident family	135	43.6
Archway of a parent to a non-resident parent family	110	45.2	*
Household Income change
Positive change	352	47.vii
Negative change	1261	47.ane
Controls
Gender			***
Male	874	41.2
Female	839	51.0
Race
African	46.1	1472
'Other'	45.6	241
Residence			*
Urban	620	49.0
Non-urban	1093	44.3
Form repetition			***
Yes	764	30.viii
No	917	59.nine
Parental Education			***
Primary or less	491	33.0
Some secondary	425	43.5
Complete secondary or more	318	66.4
Missing	479	48.0

Table four. Logistic regression models estimating the effect of family unit construction changes on high schoolhouse completion (NIDS, waves ane–5).

Table 4. Logistic regression models estimating the effect of family unit construction changes on high school completion (NIDS, waves 1–5).

Variables	Model 1		Model 2		Model 3
	OR	CI	aOR	CI	aOR	CI
Family unit construction changes (Ref—co-resident parent family unit)
Non disrupted—non-resident parent	0.58 **	0.34–0.97	0.69	0.xl–1.sixteen	0.49 **	0.23–1.02
Non disrupted—lonely-parent	0.58 **	0.34–0.99	0.71	0.42–1.21	0.57	0.28–i.12
Disrupted—co-resident parents	0.49 ***	0.27–0.89	0.54 **	0.31–one.03	0.51 *	0.24–1.06
Disrupted—non-resident parent	0.57 ***	0.31–i.04	0.84	0.45–1.58	0.65	0.29–1.45
Disrupted lone parent	0.88	0.51–1.52	1.22	0.69–ii.xvi	0.93	0.44–1.93
Household Income Change (Ref is positive change)	one.05	0.74–one.51	1.07	0.71–1.59	0.96	0.63–ane.46
Gender (Ref- Male person)			one.44 **	1.04–2.00	1.56 ***	one.12–ii.19
Race (Ref-Other)			1.08	0.sixty–1.95	1.09	0.62–1.96
Place of Residence (Ref-Urban)			1.xix	0.82–1.72	1.06	0.74–1.52
Kid repeated a grade (Ref-No)			0.24 ***	0.17–0.33	0.25 ***	0.eighteen–0.35
Parental Instruction (Ref- ≤ primary)
Some secondary					ane.53 **	1.00–2.34
Complete secondary					3.47 ***	2.00–v.ninety
Missing					1.28	0.71–2.28

Table 5. Subgroup analysis of types of type of family structure changes, (NIDS waves one–5).

Table 5. Subgroup analysis of types of type of family unit structure changes, (NIDS waves 1–5).

Variables	Model i		Model 2		Model three
	OR	CI	aOR	CI	AaR	CI
Leave of a parent(s) (ref is undisrupted co-resident)	0.51 ***	0.27–0.97	0.54 **	0.27–1.10	0.85	0.22–3.21
Go out of a parent (ref is undisrupted lone resident parent)	1.44	0.81–2.56	1.75 ***	0.93–iii.29	1.61	0.83–3.18
Entrance of a parent (ref is stable non-resident parent)	0.89	0.49–1.63	0.94	0.51–i.73	ane.12	0.57–2.17
Entrance of a parent (ref is stable co-resident)	0.seventy	0.37–1.33	1.12	0.57–2.17	0.23	0.39–1.36

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