Single Parent Effect on Children's Well-Being and Educational Attainment (Evidence from Indonesia)

doi:10.21203/rs.3.rs-2458209/v1

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Single Parent Effect on Children's Well-Being and Educational Attainment (Evidence from Indonesia)

https://doi.org/10.21203/rs.3.rs-2458209/v1

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Human capital investment such as access to education and better nutrition has been considered as one of the way for poor households to avoid intergenerational poverty. Better education and nutrition for children will improve productivity in the future. Some programs related to poverty reduction has launched by the Government of Indonesia to guarantee children from poor families to easily access education and receive better nutrition and health care. However, there is no program targeting single mother household. This paper presents the effect of single mother on children well-being and education attainment. We use data from Indonesia Family Life Survey (IFLS) and take specific variables such as parent marital status, per capita expenditure, access to health and education facilities, and children test scores. Byusing Structural Equation Model (SEM) and comparing the effects of divorced single-mother families and widowed single-mother families on boys and girls well-being, we find that divorce and larger household size appear to increase household poverty. In the second part of the equation, higher poverty proving to be decreasing the children's educational attainment.

JEL classification: D19, I00, J12

Single-Parent

Educational Attainment

Well-Being

Education

Indonesia Family Life Survey (IFLS)

Indonesia

Human capital investment has been considered one of the ways for poor households to escape intergenerational poverty. There are at least two crucial keys to human capital investment: access to education and better nutrition. Access to education improves knowledge and skills and higher individual productivity in the future. Meanwhile, better nutrition for the younger generation gives better health status in the future, which relates to individual future productivity.

The government of Indonesia (GoI) has launched several programs to guarantee children from low-income families have access to education and receive better nutrition and health care. Bantuan Siswa Miskin

(BSM[1] or Aids for Underprivileged Students in literal translation) is one of the programs to ensure low-income family children have access to education. Program Keluarga Harapan (PKH/Family Hope Program), Beras Untuk Rakyat Miskin (Raskin/Subsidized Rice for Low-Income Households), and Jaminan Keluarga Sehat (Jamkesmas/Community Health Insurance) are all of the programs that secure children of poor families to get access to better nutrition and health care services. However, of all those programs, there is no program targeting single-mother households. A single-mother household is a household that only has one parent, in this case, a mother, who lives within the household with all the children.

Bergmann (1981) explains three economic risks of being a housewife. One of the risks is the threat of displacement or termination of marriage (divorce). This risk is co-related with the other two risks: job quitting risk and high payoff variability. Job quitting usually occurs when the mother is in the child-rearing phase due to the need for care work. Due to the withdrawal from the labor market, female workers lose their source of income and the contemporary skill needed in the labor market. Therefore, make it harder for them to get back into the labor market. High payoff variability, which usually leads female workers to get paid less than their male counterparts, leads to a lack of cash reverse owned. Eventually, the threat of termination of marriage lead or divorce creates a higher economic risk for the female and the children in the family.

Krein and Beller (1988) present the adverse effects for children living in a single-parent family. Using the U.S. National Longitudinal Surveys, they find that at least three effects occur when children live in single-parent families. First, the negative effect increases with the number of years children spend in this family. Second, the negative effect reaches its peak during preschool age. Lastly, the adverse effects are more significant for boys than girls. Moreover, Keith and Finlay (1988) argue that divorce reduces children's economic and social resources. These indicate that children lack support for their education, especially in financial terms. Furthermore, Handa (1996) argues a female decision maker generally increases the share of the household budget allocated to child and family goods, although they also spend on health.

This article will be divided into four sections. The first section is the introduction, which will cover both the case of divorce in Indonesia and the gender aspect of it. The second section reviews the literature, which will cover how divorce affects kids and how poverty manifests in the household. The third section covers the methodology and empirical approach. The last section covers the empirical results and their policy relevance.

This study extends the limited and outdated research on the understanding of divorce, its impact on children, and poverty. This study is the first to consider how the three issues are interconnected, especially in developing countries such as Indonesia. Second, literature regarding the gendered aspect of marital termination (divorce) in the context of economic behavior in developing countries, especially in Indonesia, is rarely found. A country that typically has an inadequate progressive policy, a strongly patriarchal society, and is very narrow in terms of women's role in society. Lastly. This article hopes to spark and ignite a perspective of policy implementation that gendered mainstream in Indonesia.

1.1 The Case of Indonesia

The recent rapid increase in divorce, along with its distinctive cultural and welfare environments for single-parent families, makes Indonesia a compelling case to examine the effects of single parenthood on children's education. Qibthiyyah and Utomo (2016) found that there are slowly decline household size and fertility in Indonesia as well as fewer women marry up but more out of marriage (marriage out).

Table 1 shows the household head gender, age, and its living location based on Socio-Economic Survey (Susenas) year of 2016.

Table 1. Household Head, Age, and Living Location

Age	Male (%)			Female (%)
Age	Urban	Rural	Total	Urban	Rural	Total
<18	0.06	0.04	0.05	0.4	0.17	0.3
18-25	3.34	2.41	2.89	7.75	1.22	4.65
26-40	34.55	33.76	34.16	11.86	11.93	11.89
41-50	27.92	27.58	27.76	18.4	18.18	18.32
51-60	19.99	20.35	20.18	25.8	25.69	25.73
>60	14.12	15.87	14.96	35.76	42.83	39.09

Source: Susenas 2016, author's calculations.

Based on the Susenas data year 2016, female-headed household is dominant dominant at the age group 18-25 (showing implicit rate of divorce) and 50 years and above (showing implicit case of widower). Both urban and rural facing similar situations and there's not much difference between the two locations. In this article, we are using Indonesia Family Life Surveys (IFSL) which not only rich and vast dataset, but also has capabilities to track the individual and household over the years[2].

Using the IFLS (Indonesia Family Life Survey) data, we compare the levels of children's well-being (classified by gender, boys and girls) with divorced single mothers and widowed single mothers. Indonesia has a higher divorce rate compared to other Asian countries, and it tends to be getting higher each year (Dommarju & Jones, 2011). Economic reasons caused most divorces in Indonesia, and most of them ended up in lawsuits regarding child custody[3]. Indonesia's law regarding child financial support after a divorce is also not very strict and sometimes ignored. Thus, the children become victims, not only psychologically but also financially.

Until now, there has not been any paper on the case of Indonesia which discusses divorce's effects on children's educational attainment and general well-being. Most of the papers discuss divorce's psychological and emotional effects on children. These papers try to observe the effects of divorce from two sides. First, the children's current well-being by looking at their per capita consumption. Second, children's future well-being by looking at their educational attainment, assuming that educational attainment does have a high correlation with the children's opportunity to get better jobs and then get better lives.

1.2 Research Question and Gender Aspect

In this study, we examine the effects of single parenthood on children's well-being and educational outcomes in Indonesia using IFLS (Indonesia Family Life Survey) data, the longitudinal surveys. In this research, we will use panel data set from IFLS 3 (the year 2000) and IFLS 5 (the year 2015). We take specific variables such as parent marital status, per capita expenditure, health and education facilities access, and children's test scores. We explicitly address variations among different types of single-parent families by comparing the effects of divorced single-mother families and widowed single-mother families. Then, we continue explaining the disadvantages of single mothers, if any, occur. We mainly focus on the extent to which household incomes and parent-child interactions account for the effects of single parenthood.

Then, single motherhood may have different impacts on the well-being of boys and girls. The tendency for some studies to suggest that boys are more likely than girls to experience adverse outcomes as a result of family breakdown has been questioned. Amato and Keith (1991) argue that the data on adult outcomes show no significant gender differences, although it is also possible that there are gender differences in the way distress may be expressed (Zaslow, 1989). Mencarini et. al (2017) discuss how, although both gender receive less parental inputs, living in single mother family has detrimental effect on boys in term of time studying and amount of effort into study. Evidence from cohort studies shows that the negative impact of family breakdown on girls has a delayed effect and tends to emerge during adulthood when they experience greater anxiety and depression than boys (Rodgers and Pryor, 1998). It has been hypothesized that family breakdown has a greater influence on women's expectations of relationships in adulthood (Mackay, 2005). Cohort studies in the U.K. also indicate that young women are at greater risk of educational underachievement, leaving school early, lower occupational status, and of early family formation and dissolution (Kiernan 1997; Ely and Richards 1997; Sweeting and West, 1997, all cited in Rodgers and Pryor, 1998).

[1] Currently named PIP (Program Indonesia Pintar)

[2] The nature of Susenas is cross-section and it is paid data set instead of free to access like IFLS.

[3] Can be seen in https://www.ucanews.com/news/indonesia-records-sharp-rise-in-divorce-rate/90725, accessed January 1^st 2022.

2.1 Why Single Parenthood Affects Children

Understanding why family instability places some children at greater risk is essential in planning programs and policies to promote healthy children and families. The following briefly summarizes five (5) perspectives on the possible pathways through which these effects are transmitted: economic hardship, loss of parental support and supervision, lack of community resources, parental conflict, and life stress and instability (Bogenschneider, 1993).

2.1.1 Economic Hardship

Poverty is the most profound and pervasive factor underlying the developmental problems of the young. McLanahan & Booth (1989) found that one in two families headed by a single parent (only mother) is living in poverty compared with one in ten married couples with children. Not surprisingly, single parents are twice as likely to report that they worry "all or most of the time" that their total income is insufficient to meet family expenses. Garfinkel & McLanahan (1986) said that, on average, poor children in mother-headed families are poor for seven years, more than a third of their childhood.

The economic differences result not only from lower income preceding the divorce but also from the decline in income that accompanies divorce (McLanahan & Sandefur, 1994); the effect may differ somewhat for families who start poor or become poor. Nevertheless, the income of single mothers and their children after divorce is only 67 percent of their income before the divorce. At the same time, the income of divorced men is 90 percent of the pre-divorce income (McLanahan & Booth, 1989).

In one study using four nationally representative databases, lack of income emerged as the most critical factor in accounting for the differences in children from single-parent and intact families (McLanahan & Sandefur, 1994). Differences in income are estimated to account for over half of the differences in the educational attainment and steady employment of young adults and just under half of the differences in non-marital childbearing (McLanahan & Sandefur, 1994). Lack of income, however, does not appear to account for the differences in child well-being between intact and stepfamilies (McLanahan & Sandefur, 1994) or in intact and divorced families (Amato & Keith, 1991a). Mother-only families are likelier to be poor because of the lower earning capacity of single mothers, the insufficient benefits provided by the state, and the lack of child support provided by the nonresidential father (Garfinkel & McLanahan, 1986). Nationally, only 50 percent of mothers were supposed to receive a child support award in 1989; of these, only half received full payment, and a fourth received no payment at all.

2.1.2 Loss of Parental Support and Supervision

Parents who support and supervise children enhance their well-being (Maccoby and Martin, 1983). Poor parental monitoring has proven to be one of the most potent predictors of youth involvement in problem behaviors. Single parents and stepparents monitor their children less closely and know less about where their children are, who they are with, and what they are doing than parents in intact families (Amato & Keith, 1991a; Hetherington, 1989; McLanahan & Booth, 1989; McLanahan & Sandefur, 1994). Single parents are also less involved in their children's school activities and have lower educational goals for their children (Furstenberg & Nord, 1985; McLanahan & Booth, 1989; McLanahan & Sandefur, 1994).

2.1.3 Lack of Community Resources

Youth who overcome disadvantages can rely on a more significant number of sources of social support than youth with serious coping problems, including teachers, ministers, older friends, family day-care providers, nursery schoolteachers, neighbors, or contacts at social agencies.

Furthermore, the benefits of a supportive community appear to be strongest for children who are the most vulnerable, to begin with. For example, the number of adult male relatives, usually grandfathers and uncles, who took a child on outings away from home was related to improved report card scores (Riley & Cochran, 1987). The benefits, however, were restricted to the subgroup with the lowest average grades, single-parent boys.

Not only does social support benefit youth, but it also benefits parents. Social isolation is well-documented as one of the best predictors of poor parenting. Regardless of culture and social class, a mother is warmer and more emotionally stable when more adults are around to help (Crockenberg, 1981; Crnic, Greenberg, Ragozin, Robinson & Basham, 1983).

Not surprisingly, the children of single parents do better when the mother receives strong support from nearby relatives, friends, or neighbors; members of religious groups; and staff members of family support and childcare programs (Bronfenbrenner, 1974).

Two-parent families tend to live in better neighborhoods, and their children are more apt to attend better schools and associate with less deviant peers than single-parent or remarried families (McLanahan & Sandefur, 1994). Single parents are less likely to report that they consider their neighborhoods excellent or good places to raise children than two-parent families. Limited economic resources may force some families to move and live in neighborhoods with poorer schools and fewer community services (McLanahan & Booth, 1989).

2.1.4 Parental Conflict

This explanation is potentially more helpful in explaining the differences in child well-being in divorced or remarried families than in never-married families. Considerable evidence exists that a conflict-ridden marriage jeopardizes the well-being of children. Based on this, ending a conflict-ridden marriage may actually boost rather than undermine children's well-being.

Recent evidence suggests that children in divorced single-parent families do better than children in high-conflict, intact families (Amato, 1993; Amato & Keith, 1991a; Peterson & Zill, 1983). In fact, a review of 92 studies documented strong and consistent support for the parental conflict explanation of the differences in child well-being between divorced and non-divorced families (Amato, 1993; Amato & Keith, 1991a). While some families are undoubtedly conflict-ridden and pathological that they cannot adequately care for children, McLanahan and Sandefur (1994) contend that the proportion of families that fall into this category may be small. Half of all children experience family instability, and it is hard to believe that half of all parents have such conflictual relationships that they cannot do a reasonably good job raising their children.

Obviously, this is a complex issue. Some disagreements in a family may be healthy, and a temporary period of conflict between parents is less detrimental to children than persistent conflict or divorce. Yet, too much conflict can be quite destructive. Furthermore, divorce does not necessarily stop the conflict and may generate its own; research suggests post-divorce conflict persists between many parents (Amato & Keith, 1991a).

2.1.5 Life Stress and Instability

According to this explanation, one stressful life event is not as detrimental to children's well-being as many (Amato, 1993). Family disruptions often entail a number of changes which, taken together, can be more stressful than anyone considered alone (i.e., moving, changing schools, loss of contact with the noncustodial parent, and a decline in one's standard of living). McLanahan and Sandefur (1994) speculate that the instability of resources may be as critical to children's well-being as the level of resources. In particular, they suspect that instability may explain why children in stepfamilies are as disadvantaged as children in single-parent families despite their income advantage. Children in stepfamilies are exposed to a series of changes in location, income, and people living in the household (i.e., grandparents, partners, and stepparents). The support provided by parents who are adjusting to a new marriage and new stepchildren may also be less consistent

2.2 Boy's and Girl's Well-Being/Attainment

Then, the impact of single parents may be different on boys' and girls' well-being. The tendency for some studies to suggest that boys are more likely than girls to experience adverse outcomes as a result of family breakdown has been questioned. Amato and Keith (1991b) argue that data on adult outcomes show no significant gender differences, although it is also possible that there are gender differences in the way distress may be expressed (Zaslow, 1989). Evidence from cohort studies shows that the negative impact of family breakdown on girls has a delayed effect and tends to emerge during adulthood when they experience more significant anxiety and depression than boys (Rodgers and Pryor, 1998). It has been hypothesized that family breakdown has a greater influence on women's expectations of relationships in adulthood (Mackay, 2005). Cohort studies in the U.K. also indicate that, because of early family formation and dissolution, young women are at greater risk of educational underachievement, leaving school early, and lower occupational status (Kiernan 1997; Ely and Richards 1997; Sweeting and West, 1997, all cited in Rodgers and Pryor, 1998).

2.3 Household Head Education and Poverty

According to a World Bank (1995) report, primary and lower secondary education significantly enhances the productivity of the poor, decreases fertility, and improves health conditions. On the other hand, education helps people to gain abilities to participate in the economy and society. According to Berg (2008), the probability of finding a job increases with an increase in one's education level; additionally, educated people earn more. Moreover, the effect of education levels on poverty displays differences in diverse regions and under different socioeconomic circumstances. As indicated in Gemmell (1996), primary education is salient for low-income developing countries, secondary education for middle-income developing countries, and tertiary education for rich countries in terms of economic growth.

The link between poverty and education has been subject to numerous studies through diverse methods and data. The problematic issue in question has focused on variables such as gender, education, age, and region to explain the effect of the given factors on poverty. Gundlach, de Pablo, and Weisert (2001) investigate the relationship between education and income inequalities. Given their findings, education is intrinsically a cornerstone to distributing income equally and provides the opportunity for the poor to enjoy economic growth to a greater extent. Okojie (2002) analyzed the link between gender, the education of household heads, and the poverty of households in Nigeria between 1980 and 1996 by using multivariate regression models and obtained results that suggest that the probability of being poor in a family with female heads is higher than those with male heads. As inferred, education and the size of households have a considerable impact on welfare and poverty. The better educated a household head is, the lower the risk of poverty. Another study by Maitra and Vahid (2006) surveyed the effects of household characteristics in South Africa on poverty and living standards.

2.4 Household Size and Poverty

Observing the poverty status of households experiencing economic shocks can reveal the relationship between vulnerability to poverty and family size. Reyes (2002) uses panel data from the 1997 FIES and the 1998 and 1999 Annual Poverty Indicator Surveys (APIS) to study the movement of households in and out of poverty. Vulnerability to poverty increases with family size. It also can be described by looking at changes in human capital expenditures, actual school attendance, and incidence of child labor as family size increases, which provides even more revealing information. Not only does expenditure per student decline, but actual school attendance decline, and child labor increases as household size increases. Additional children will impact the parents' labor supply, wage income, and family savings.

2.5 Distance from Metropolitan and Poverty

Some studies find that poverty rates are positively associated with greater rural distances from successively larger (higher-tiered) metropolitan areas (ceteris paribus). Poverty is higher in these rural areas because of their remoteness. Poverty remains high in many areas of the nonmetropolitan area, particularly in regions non-adjacent to or far removed from metropolitan areas (Glasmeier and Farrigan, 2003; Swaminathan and Findeis, 2004; Partridge and Rickman, 2006). Extensive literature has emerged examining whether there is a rural poverty effect.

Weber et al. (2005) conclude that poverty is higher and more persistent in the more remote rural, although they were reluctant to describe this as a rural effect. Fisher (2005) shows that while part of the higher rate of poverty in rural areas is attributable to poor economic opportunities, she also contends that part is attributable to the self-selection of poor people into rural areas. Partridge and Rickman (2008) find that poverty increases with greater distance from each successive tier of the metropolitan area, even when accounting for a host of county characteristics such as the area's amenity attractiveness and the demographic composition of the local population. Further analysis details how rural communities receive fewer benefits from nearby metropolitan area job growth if they are more distant. More remote rural communities have more inelastic labor supply, which causes them to have higher poverty when labor demand is weaker, but allows them to capture more poverty-reducing benefits if they were to have stronger local job growth. The same accessibility factors that give rise to the distance effect on poverty imply that employment growth has more significant antipoverty effects in more remote areas.

This research uses Structural Equation Model (SEM) as a method of analysis. In SEM, the effect of independent variables is presumably indirect rather than direct. A mediation model will be built using several mediator variables. Thus, instead of working on a single equation, there will be two equations, with one equation as the explanation for the other equation.

Whereas equation (1) is a mediation model to equation (2). Equation (2) with dependent variable Y₂is explained by equation (1) plus other covariates closely related to the dependent variable in equation (2).

The mechanism behind how the model work can be seen in figure 1.

To be more direct and applicable, our model in STATA program built will be like the figure 2 below:

Based on the picture above, we have two different equations (Y1 and Y2). Y1 is the dependent variable in equation (1) but becomes the independent (mediation) variable in equation (2). Variables X1-X6 are all independent variables for Y1, whereas variables X7-X13 are specifically independent variables for Y2. To be clear, our list of variables is as follows:

Table 2. Variables in The Model

Variable	Explanation
Y1	Poverty Score The poverty score is measured by using the characteristic poverty definition from the National Bureau of Statistics of the Republic of Indonesia (BPS RI). There are nine different categories: Size of the house, type of floor mat, type of wall, level of education of household head and spouse on average, electricity access, clean water access, toilet access, kitchen and stove type, and asset ownership status. Each category will be summed up to determine the poverty score. Zero means non-poor; meanwhile, nine means very poor.
Y2	Cognitive Score The cognitive score is measured by asking children several questions related to cognitive skills, such as fitting the shape, basic mathematical skills, etc. We are retrieving cognitive scores from IFLS5.
X1	Dummy Married (Divorced+Widowed=1) Dummy Married (Divorced=1) Dummy Married (Widowed=1) These three different kinds of variables represent three different marital statuses. First, it represents every single ever married man/woman. The reason for being single could be separation (divorced), a decision to live separately, and separation by death (widowed). In the second variable, we only see families with divorces and decisions to live separately. While variable number three is specifically for widowed household heads.
X2	Household Size Household size represents the number of family members in the household.
X3	Distance from Capital This variable measures remoteness. How far the household is from the nearest Kecamatan (Sub-district) Capital.
X4	Distance from Business Centre This variable measures remoteness. How far the household is from the nearest business center, such as traditional markets or groups of shops.
X5	Household Head Education This variable measures the years of schooling of the household head.
X6	Per Capita Expenditure This variable shows the per capita expenditure of each individual in the household. Taken from IFLS per capita expenditure dataset.
X7	Age Explaining the age of respondents when taking the cognitive score test.
X8	Child Status This variable explains whether children are adopted (=1) or biological children.
X9	Number of Children in The Household Explaining the number of children in the household. Showing whether more children means fewer resources for each child.
X10	Gender Child gender.
X11	Remaja (teenager=1) Dummy variable showing whether the children are already teenagers (12 years old and above).

Source: IFLS3 and IFLS5 processed, writer

4.1 The Factors Affecting Poverty

Poverty is a multi-faceted phenomenon that affects not only the ability to purchase goods but also vulnerability to various pressures that may prohibit an individual from enjoying life. This vulnerability may be gauged from living conditions such as employment, health, education, and housing. It is important to monitor gender differences in poverty, vulnerability, and living conditions and also to understand the causes of these differences to prepare strategies for more efficient intervention schemes aimed at poverty reduction. Efforts towards poverty alleviation, therefore, require a complete intervention scheme, not simply in economic aspects but including social dimensions, so poverty may be addressed as a socioeconomic phenomenon. We find that marital status, household size, distance from the capital, distance from business centers, household head education, and per capita expenditure affect poverty.

Table3. Factors Affecting Poverty Score

	(1)	(2)	(3)	(4)	(5)	(6)
VARIABLES	pov_score	pov_score	pov_score	ln_pov_score	ln_pov_score	ln_pov_score
	divorcde+widow	divorce	widow	divorcde+widow	divorced	widowed
Marital status (1=divorced+widowed)	0.245*	0.464*	0.161	0.235*	0.466*	0.145
	(0.127)	(0.244)	(0.147)	(0.129)	(0.248)	(0.150)
Household Size	0.0466***	0.0470***	0.0466***	0.0422***	0.0426***	0.0422***
	(0.0102)	(0.0103)	(0.0103)	(0.0107)	(0.0107)	(0.0107)
Distance from Capital	0.00618***	0.00615***	0.00621***	0.00643***	0.00640***	0.00645***
	(0.00105)	(0.00105)	(0.00105)	(0.00106)	(0.00106)	(0.00106)
Distance from Business Centre	0.0344***	0.0342***	0.0344***	0.0346***	0.0343***	0.0345***
	(0.00718)	(0.00718)	(0.00718)	(0.00736)	(0.00736)	(0.00736)
Household Head Education	-0.406***	-0.406***	-0.406***	-0.372***	-0.373***	-0.372***
	(0.0272)	(0.0272)	(0.0272)	(0.0286)	(0.0286)	(0.0286)
Per Capita Expenditure	-6.75e-07***	-6.75e-07***	-6.73e-07***	-7.62e-07***	-7.62e-07***	-7.60e-07***
	(7.84e-08)	(7.84e-08)	(7.84e-08)	(8.45e-08)	(8.45e-08)	(8.45e-08)
Observations	2,454	2,454	2,454	2,285	2,285	2,285
Standard errors in parentheses * p<0.01, p<0.05, * p<0.1

Marital status (1=divorced or widowed) is a significant positive influence on poverty. It means that divorce appears to aggravate household poverty. Single parents have much lower incomes and poverty rates than their married counterparts. Some of this, to be sure, is because they also have other characteristics, such as less education that limits what they can earn. But two incomes, even low, are always better than one. Rank and Hirschl (1999) find that children in non-intact families face a higher risk of poverty throughout childhood. Children in non-married households who are one year old have exceeded the risk of poverty that children in married households experience during their entire 17 years of childhood. Morrison and Ritualo (2000) found a 66 percent reduction in poverty among children whose divorced single mothers remarried and a 40 percent reduction in poverty among children whose mothers cohabited after a divorce.

Mothers are more likely than fathers to fall into poverty following a divorce. Among households above poverty before marital separation, mothers were much more likely than fathers to fall into poverty during the first year following separation. While 19 percent of mothers became impoverished, only 3 percent of the husbands became poor after separating. (Bianchi, et.al, 1999). When divorce occurs among families living in poverty, mothers are less likely than fathers to rise out of poverty. Bianchi et al. (1999) also found that fathers were significantly more likely to rise out of poverty among households whose incomes fell below the official poverty line than mothers during the first year following marital separation. While only one-quarter of the fathers who had been in poverty remained, so after separation, three-quarters of the mothers remained in poverty.

Our study finds that household head education is a significantly negative influence on poverty. This finding is in line with research by Rank and Hirschl (1999). Households headed by adults with less than a high school education tend to experience higher poverty rates. Children in households headed by adults with less than a high school education tend to experience higher poverty rates.

Household sizes also affect poverty. We find that it is a significant positive influence on poverty. Associations between larger household sizes and poverty are solid and enduring. These results have important implications for efforts of poverty reduction. A substantial population program must accompany poverty alleviation efforts. In the short run, it may be in the form of providing family planning services for those who need them. In the long run, it may include advocacy for smaller family sizes.

High poverty persisted in remote rural areas. We find that poverty rates increase with greater rural distances from successively larger metropolitan areas. We explain this outcome as arising from the distance from the capital and the distance from the business center. We find that two variables significantly positively affect poverty. One implication is that remote areas may experience greater poverty reductions from place-based economic development policies.

4.2 The Factors Affecting Educational Attainment

In a perfect world, children of all races, socioeconomic backgrounds, and family types would not only have the opportunity to receive a higher education but also take full advantage of these opportunities. In educational and economic studies, it has been found that background variables, including family income per capita, family type, family size, and parents' education, are determinants of the amount and quality of education children receive over their lifetime.

By SEM, we find that poverty score, age, and child status statistically significantly affect educational attainment (score). Poverty score has adverse effects on educational attainment. Poverty increases as educational attainment decreases. As a result of increasing poverty, education is harder to achieve, and attainment is lower. It can be described via school readiness, which reflects a child's ability to succeed academically and socially in a school environment. It requires physical well-being, appropriate motor development, emotional health, a positive approach to new experiences, age-appropriate social knowledge and competence, age-appropriate language skills, and age-appropriate general knowledge and cognitive skills.

Poverty decreases a child's readiness for school through aspects of health, home life, schooling, and neighborhoods. This results supporting Khiem and Kuo (2022) which found that the impact of health reform in Vietnam to educational attainment. A child's home has a powerful impact on school readiness. Children from low-income families often do not receive the stimulation and do not learn the social skills required to prepare them for school. Typical problems are parental inconsistency (concerning daily routines and parenting), frequent changes of primary caregivers, lack of supervision, and poor role modeling. Very often, the parents of these children also lack support. Then, higher incomes were consistently associated with better outcomes for children. The most prominent effects were for cognitive and school measures.

Table4. Factors Affecting Educational Attainment

	(1)	(2)	(3)	(4)	(5)	(6)
VARIABLES	totalscore	totalscore	totalscore	ln_totalscore	ln_totalscore	ln_totalscore
Poverty Score	-0.568***	-0.568***	-0.568***	-0.0842***	-0.0842***	-0.0842***
	(0.0605)	(0.0605)	(0.0605)	(0.00724)	(0.00724)	(0.00724)
Age	-0.165***	-0.165***	-0.165***	-0.0228***	-0.0228***	-0.0228***
	(0.0149)	(0.0149)	(0.0149)	(0.00177)	(0.00177)	(0.00177)
Child Status (1=Adopted)	-0.845	-0.845	-0.845	-0.152**	-0.152**	-0.152**
	(0.629)	(0.629)	(0.629)	(0.0737)	(0.0737)	(0.0737)
Number of Children in The Household	-0.0987**	-0.0987**	-0.0987**	-0.00209	-0.00209	-0.00209
	(0.0452)	(0.0452)	(0.0452)	(0.00546)	(0.00546)	(0.00546)
Gender (1=Male)	-0.344**	-0.344**	-0.344**	0.00339	0.00339	0.00339
	(0.162)	(0.162)	(0.162)	(0.0191)	(0.0191)	(0.0191)
Constant	11.71***	11.71***	11.71***	2.501***	2.501***	2.501***
	(0.241)	(0.241)	(0.241)	(0.0286)	(0.0286)	(0.0286)

Observations	2,454	2,454	2,454	2,285	2,285	2,285
Standard errors in parentheses * p<0.01, p<0.05, * p<0.1

Poverty score that affects cognitive score also can be described via family income, which may have a direct impact on a child's academic outcomes, or variations in achievement could simply be a function of the school the child attends: parents with greater financial resources can identify communities with higher-quality schools and choose more-expensive neighborhoods—the very places where good schools are likely to be. More-affluent parents can also use their resources to ensure that their children have access to a full range of extracurricular activities at school and in the community.

Nevertheless, it's not hard to imagine the direct effects of income on student achievement. Families struggling economically don't have the wherewithal to check homework, drive children to summer camp, organize museum trips, or help their kids plan for college. Working multiple jobs or inconvenient shifts makes it hard to dedicate time for family dinners, enforce a consistent bedtime, read to infants and toddlers, or invest in music lessons or sports clubs. Even slight differences in access to the activities and experiences that promote brain development can accumulate, resulting in a sizable gap between two groups of children defined by family circumstances.

For a given parental income level, family size/number of children is likely to reduce the per capita resources that can be spent on educational investments. We find that the number of children in the household is negatively significant to the cognitive score. Many studies have shown the effects number of children on the educational attainment of the children in the family. Family constraints often affect several children in terms of finance and the intellectual environment. Becker and Lewis (1973) point out that an increasing number of children often come up with lower quality of education output. On the other hand, according to Zajonc (1976), the intellectual environment per person decreases when the number of children increases. Using the military examination score modified by the Raven Progress Matrixes, Belmont and Marolla (1973) showed an inverse relationship between the family size and the Raven score. The estimates also show that the child's educational attainment is declining with age. The age of children is negatively significant to the cognitive score. Age increases as cognitive score decrease. The specification also shows that the child's educational attainment is lower if the child is male.

4.3 Policy Relevance

Divorce appears to increase household poverty. Mothers are more likely to fall into poverty after divorce compared to fathers. Therefore, it is very relevant to provide recommendations on Marriage Laws and safety nets for single mothers. Human capital investment has been considered one of the ways for poor households to escape intergenerational poverty. Access to education and better nutrition are crucial to human capital investment. Access to education improves knowledge, skills, and higher productivity in the future of individuals. Meanwhile, better nutrition for the younger generation gives better health status in the future, which relates to individual future productivity.

Household size also affects poverty. We find that it is a significant favorable influence on poverty. Associations between larger household sizes and poverty are solid and enduring. These results have important implications for efforts of poverty reduction. A robust population program must accompany poverty alleviation efforts. In the short run, it may be in the form of providing family planning services for those who need them. In the long run, it may include advocacy for smaller family sizes. Poverty rates increase with greater rural distances from successively larger metropolitan areas. One implication is that remote areas may experience more significant poverty reductions from place-based economic development policies.

Funding

This work was supported by the Faculty of Economics, Universitas Gadjah Mada through yearly professor research funding.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose

Author Contribution

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Wisnu Setiadi Nugroho, Evi Noor Afifah and Andika Ridha Ayu Perdana. The first draft of the manuscript was written by Wisnu Setiadi Nugroho and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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No competing interests reported.

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Single Parent Effect on Children's Well-Being and Educational Attainment (Evidence from Indonesia)

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1. Introduction

2. Review Of Literature

2.1 Why Single Parenthood Affects Children

3. Methodology

4. Empirical Result

4.1 The Factors Affecting Poverty

4.2 The Factors Affecting Educational Attainment

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