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. Author manuscript; available in PMC: 2018 Mar 20.
Published in final edited form as: Monogr Soc Res Child Dev. 2016 Mar 29;81(1):104–122. doi: 10.1111/mono.12228

GIRLS’ AND BOYS’ LABOR AND HOUSEHOLD CHORES IN LOW- AND MIDDLE-INCOME COUNTRIES

Diane L Putnick 1, Marc H Bornstein 2
PMCID: PMC5860687  NIHMSID: NIHMS949886  PMID: 29568137

States Parties recognize the right of the child to be protected from economic exploitation and from performing any work that is likely to be hazardous or to interfere with the child’s education, or to be harmful to the child’s health or physical, mental, spiritual, moral or social development.

–Article 32.1, Convention on the Rights of the Child General Assembly resolution 44/25, 20 November 1989.

Children in impoverished households in low- and middle-income countries (LMIC) often contribute to their family’s welfare by managing household responsibilities while parents work outside the home or by engaging in employment themselves. UNICEF (2007) estimated that 1 in 6 children aged 5-14 years was involved in child labor. However, estimates vary widely because of inconsistent definitions of child labor. Some definitions of child labor include only paid work outside the home and others include unpaid work, family work, and excessive household chores as child labor because each type has the same impact on child school attendance, health, and well-being (ILO, 2004, 2009). Girls are also more likely to be involved in excessive housework than boys (Huebler, 2008). In this chapter, we use a broad definition of child labor and compare the rates of different types of labor in girls and boys in 38 LMIC.

THREE TYPES OF CHILD LABOR

Child labor is often divided into three major categories: paid or unpaid work outside the home, family work, and housework. Children’s work outside the home has received the most empirical attention. Work outside the home is itself divided into three broad sectors of agriculture (69% of economically active children; such as farming, fishing, and forestry), services (22%; such as trade including street selling or begging, domestic, restaurant, and transportation work), and industry (9%; such as manufacturing, mining, construction, and public utility work; Hagemann, Diallo, Etienne, & Mehran, 2006). These kinds of work outside the home can be paid or unpaid. Family work consists of any (usually unpaid) work that children do for the family. Often, family work is agricultural (Webbink, Smits, & de Jong, 2010), but it also includes work for any other type of family-owned business. Finally, housework, or household chores, includes childcare, cleaning, cooking, laundry, shopping, fetching water and wood, and home maintenance. Housework is considered to be a hidden form of child labor because it is unpaid and it often goes unreported (Gibbons, Huebler, & Loaiza, 2005; Webbink et al., 2010). UNICEF (2006) considers housework to be child labor if the child engages in 4 or more hours per day (28 hours per week).

CHILD LABOR LEGISLATION

The International Labor Organization (ILO, 2012, p. 1) defines child labor broadly as any “work that deprives children of their childhood, their potential, and their dignity, and that is harmful to physical and mental development.” The ILO also established global standards to protect children from child labor. ILO Convention No. 138, ratified by 161 countries, set the minimum age for child labor at 15 (ILO, 1973), and ILO Convention No. 182, ratified by 174 countries, identified the “worst forms” of child labor as slavery, child trafficking, use of children in armed conflict, prostitution, drug trafficking, and any work which is likely to harm the health, safety, or morals of children (ILO, 1999). Because of the wording of ILO Convention No. 182, agricultural work, the most common form of child labor (Hagemann et al., 2006), is often considered to be a “worst form” on account of the risk of injury and exposure to pesticides (Woolf, 2002). Following the introduction of ILO conventions, the number of children engaged in child labor, and especially the number of children working in hazardous conditions, has decreased (Hagemann et al., 2006). However, Dessy and Pallage (2005) argued that a complete ban on the worst forms of child labor, without programs designed to counter the economic losses of the ban, only punishes families who rely on their child’s income to survive.

WHY CHILDREN WORK

Despite hazards associated with child labor, many children still work. For some children, there is little distinction between work and play (Harkness & Super, 1986). Children’s play may revolve around the “useful” activities that they see adults do. Consequently, children who watch adults carry wood may also carry smaller bundles of wood as a manner of play that has the benefit of helping the household. Just as children from developed countries pretend to drive the carpool and carry a briefcase around the house, children who live on subsistence farms in LMIC may pull weeds and water plants. Furthermore, children may engage in gendered work behavior because they pattern their play and work habits after the same-sex parent (Bussey & Bandura, 1999; Whiting & Whiting, 1975).

When Nigerian children were asked about the benefits of working, the most common reasons cited were supporting the family and having money to pay for school or to learn a trade (Omokhodion, Omokhodion, & Odusote, 2006). For children in Bangladesh, Guatemala, El Salvador, Ethiopia, Nicaragua, and the Philippines, the two most common benefits of working were earning money and supporting the family (Woodhead, 1999). Parents may employ their children in farm work because they cannot afford to pay outside workers (Dumas, 2007). Working mothers in LMIC may also have limited childcare options, leading them to use their older children to care for younger children (Mehra, Kurz, & Paolisso, 1992). However, the root cause of most child labor is generally accepted to be poverty (Dessy & Pallage, 2005; Jensen & Nielsen, 1997).

CHILD LABOR AND POVERTY

Child labor is more common in LMIC than high-income countries (HIC; Dorman, 2001; Fares & Raju, 2007). The countries included in this study all constitute LMIC (UNICEF, 2006). Although there is considerable variation within individual countries, children and caregivers in LMIC are likely to have a low standard of living (World Bank, 2012) and to command relatively few material resources (Bradley & Putnick, 2012), and they are unlikely to have access to governmentally sponsored social assistance programs (World Bank, 2012). Consequently, children in LMIC may work because their families need them to work to survive. Galli (2001) suggested that child labor contributed somewhere between 10% and 20% of family income, depending on the location. Considering the indirect contributions of unpaid family work (e.g., family farm or business work) and household chores (e.g., childcare), 10%-20% may be a drastic underestimate.

That said, child labor may perpetuate poverty. Children who work or spend many hours taking care of household responsibilities are less likely to attend school (Beegle, Dehejia, & Gatti, 2009; Fares & Raju, 2007; Gibbons, Huebler, & Loaiza, 2005; Guarcello, Lyon, & Rosati, 2008; Huebler, 2008). Furthermore, a study in Ghana suggested that it is not just school enrollment or attendance that are affected by child labor, but also math and reading achievement for those in school. Controlling for a host of family and personal variables, Heady (2003) demonstrated that work outside the home, more so than housework or work at home, had a negative relation with math and reading test performance in 9- to 18-year-olds. Orazem and Gunnarsson (2003) replicated these findings for working children in Latin American countries. Finally, in a retrospective study, Emerson and Souza (2007) explored the impact of age of entry into the labor force on adult men’s earnings in Brazil. Controlling for years of education, child labor was associated with lower adult earnings. Therefore, even if the child laborer stayed in school, his adult earnings were diminished compared to a child who delayed entry into the workforce into later adolescence (Emerson & Souza, 2007; see also Knaul, 2001).

BENEFITS AND COSTS OF CHILD LABOR

Under the right circumstances employment can teach children skills, responsibility, and time management that help prepare them for work as adults. Child apprentices may learn critical skills that will allow them to make enough money to support their families or pay for school (Lancy, 2012a). Children who work alongside their same-sex parents may learn important gender roles, rules for appropriate gendered behavior, and solidify their identities as contributing members of their communities (Lancy 2012b). Weisner (1984) suggested that through work, children learn culturally relevant behavior, self-reliance, self-esteem, and compliance. However, children often work out of necessity, and working conditions may not be designed with children’s best interests in mind. In addition to the negative economic and educational consequences of child labor already discussed, working children are exposed to a variety of toxins, and such exposure may have serious consequences for growth and health because children are less able to metabolize or eliminate those toxins than adults (Woolf, 2002). In a sample of 83 LMIC, Roggero, Mangiaterra, Bustreo, and Rosati (2007) found that child labor (limited to economically active children, not those working in the household) was associated with mortality and undernourishment, even after controlling for country-level poverty and the adult mortality rate. Farm work in the United States has been recognized as one of the most dangerous occupations for children because of high injury and death rates on the job (American Academy of Pediatrics, 2001). Farmwork is also likely to be dangerous in LMIC, but many countries lack the reporting systems necessary to track work-related injury and death (Hurst, 2007). Children working in poor conditions may also suffer from mental health problems, such as depression and anxiety (Fekadu, Hägglöf, & Alem, 2010; Thabet, Matar, Carointero, Bankart, & Vostanis, 2010).

Household chores can serve to teach important skills about how to keep a household functioning. However, like work outside the home, working inside the home presents numerous challenges (ILO, 2004). Many household chores are inappropriate to a child’s age or strength, and children may engage in many hours of household chores, leading to fatigue. For example, caring for younger children often requires lifting and carrying them, which can injure even the older child caregiver and put the younger child at risk. Similarly, child caregivers may lack the necessary judgment to adequately protect themselves and their younger siblings from harm. Collecting firewood and water and carrying them long distances can also lead to fatigue and injury in young children. Finally, cooking can lead to burns, cuts, and other injuries in children who do not have the necessary knowledge, strength, and dexterity to safely accomplish such tasks.

GENDER DIFFERENCES IN CHILD LABOR

Overall, boys may engage in more child labor than girls (Fares & Raju, 2007); but the meaning of this difference is challenging to interpret given that girls and boys tend to engage in different kinds of labor. Indeed, one study conducted in Ethiopia showed that 14- and 15-year old girls and boys spent about the same amount of time per day in family connected labor, but their time was spent in different forms of labor (Pells, 2011). Gender differences in participation rates also vary by country; thus, it can be difficult to infer what participation in various forms of labor may portend for children’s overall well-being.

Work outside the home

Overall, boys are more likely than girls to work outside the home (Fares & Raju, 2007), and they are more likely to be paid for work (Kolomiyets, 2004), but relative rates depend on the industries and norms in the region under study. Aggregating across multiple countries, girls are more likely to be employed in services (especially domestic work), boys are more likely to be employed in agriculture, and similar percentages of girls and boys are engaged in industry, but gender rates vary considerably by country (Allais, 2009).

Family work

Based on a sample of 8- to 13-year-old children in 16 LMIC in Africa and Asia, Webbink et al. (2010) concluded that boys spent about 1 hour more per week on family work than girls. Kolomiyets (2004) also noted that a higher proportion of 5- to 14-year-old boys than girls were working for their families in four LMIC. However, family work has not been studied systematically across LMIC.

Housework

Girls are more likely than boys to work inside the home doing household chores, childcare, and elder care (Allais, 2009; Bonke, 2010; Evans, 2010; Webbink et al., 2010), and twice the proportion of girls than boys works more than 28 hours per week doing household chores (Allais, 2009). There is also evidence that the household chores girls and boys do in HIC are gender differentiated (Goodnow, 1988), but there are no available data about the types of household work done in LMIC.

GENDER DIFFERENCES IN CHILD LABOR AS A REFLECTION OF NATIONAL GENDER INEQUALITY

Girls’ greater labor rates inside the home and boys’ greater labor rates outside the home may reflect macrosystem-level gender inequality. In some LMIC, women’s rates of employment and education are quite divergent from men’s. Few economic opportunities for adult women may position parents to encourage their girls to take on domestic responsibilities to prepare them for their likely adult responsibilities as homemakers. Similarly, boys may be encouraged to work outside the home to develop skills they could apply to their work as adults. To investigate the link between gendered labor and macrosystem influences, we explored two country-level indicators of gender equality/inequality, controlling for the overall level of human/economic development in the country.

THIS STUDY

Using a sample of 38 LMIC drawn from all regions of the world, we investigate differences between rates of child labor in girls and boys aged 5-14. We include three major types of child labor – work outside the family, work for the family, and household chores – and examine each type separately by gender, to provide a more complete picture of the types of labor engaged in by young girls and boys. Based on sparse previous research, we expected that more boys than girls would engage in child labor overall, in work outside the home, and family work, and that more girls than boys would engage in excessive household chores. Given the paucity of data from many of these countries we could not make specific predictions for every country. Most studies of child labor include only one country or a small selection of countries from a single region. By exploring the rates of child labor across 38 countries, we expand the knowledge base about gender similarities and differences in child labor. Finally, we explore whether differences between labor rates of girls and boys are related to national indicators of gender equality and the overall level of human/economic development in the country.

METHOD

Participants

We evaluate child labor in girls and boys in 233,980 families in 38 countries (Table 6.1). The randomly selected child from each family averaged 9.27 years of age (SD = 2.92, range = 5-14), and 49.54% were female. Girls were slightly but not meaningfully older than boys on average, M = 9.29, SD = 2.94, for girls and M = 9.25, SD = 2.90, for boys, t(233,735.07) = 3.95, p < .001. Questions were usually answered by the child’s biological mother (88.3%). Of the 11.7% that were completed by another mother figure, 98.3% had no biological mother living in the household. Mothers averaged 37.04 years (SD = 10.23, range = 15-95), and the highest level of education she had completed was none or preschool for 35.6%, primary school/non-standard curriculum/religious school for 29.9%, secondary/vocational/tertiary school for 29.0%, and higher for 5.5%. Mothers of girls were slightly, but not meaningfully, older (M = 37.14, SD = 10.38) and less educated (M = 1.04, SD = .93) than mothers of boys (M= 36.93, SD = 10.09, and M = 1.05, SD = .93, respectively), ts(233,089.40 and 233,553.19) = 5.04 and -4.16, ps < .001, respectively.

TABLE 6.1.

SAMPLE DESCRIPTIVE STATISTICS AND PERCENTAGES OF CHILDREN WHO WERE ENGAGED IN CHILD LABOR BY GENDER AND HDI

Child gender Child age Mother educationa Child labor index in the past week
Country n Female % M SD M SD Girls % Boys % OR largest shareb
High HDI
Trinidad & Tobago 1745 51.06 9.69 2.98 1.82 .78 .67 1.17   .57 fam/work
Montenegro 928 47.20 8.83 2.90 1.90 .65 7.18 9.13   .79 work
Serbia 2835 48.32 9.00 2.88 1.59 .82 4.28 4.99   .84 work
Belarus 1943 49.46 9.54 2.95 2.21 .41 5.53 5.91   .94 work
Macedonia 2712 51.66 8.01 2.95 1.18 .72 5.78 4.12 1.44* work
Albania 2244 46.43 9.82 2.88 2.46 .55 8.16 12.15   .61*** fam
Kazakhstan 5935 48.32 10.00 2.89 2.20 .43 2.34 3.03   .76 work/fam
Bosnia and Herzegovina 1989 50.58 8.89 2.81 1.65 .62 3.88 5.09   .74 fam
Medium HDI
Thailand 16263 49.29 9.68 2.81 1.39 .77 8.41 8.70   .95 fam
Ukraine 1668 48.32 9.58 2.79 2.27 .67 8.31 11.02   .74 fam
Jamaica 1990 49.05 9.58 2.85 1.99 .55 4.92 5.15   .95 work
Suriname 2593 50.02 9.25 2.87 1.60 1.18 3.73 4.79   .76 work
Georgia 3753 46.36 9.90 2.95 2.04 .75 16.80 19.46   .83* work
Syrian Arab Republic 11486 48.76 9.44 2.98 1.14 .88 2.13 4.49   .44*** fam
Guyana 2811 49.55 9.39 2.86 1.74 .99 17.79 18.68   .97 fam
Mongolia 3688 49.30 9.47 3.03 2.18 .59 15.95 18.29   .82* chores/fam
Viet Nam 4439 47.65 10.07 2.93 1.50 .76 17.07 16.75 1.02 fam
Uzbekistan 6271 48.62 9.77 2.97 2.12 .32 2.30 3.10   .73* work
Kyrgyzstan 3025 48.00 9.65 2.89 2.16 .43 2.34 3.69   .63* chores/fam
Tajikistan 5016 47.31 9.50 3.00 2.05 .37 10.03 10.82   .94 choresc
Laos 4515 49.57 9.36 2.96 .79 .71 11.67 9.53 1.21 fam
Yemen 2801 49.30 9.21 2.90 .35 .65 23.14 19.56 1.26* chores/fam
Mauritania 7415 50.21 8.95 2.93 .73 .77 14.23 17.69   .78*** fam
Ghana 3582 49.80 9.31 2.88 .78 .96 35.08 35.31 1.01 fam
Bangladesh 41168 48.90 9.30 2.83 .79 .87 8.33 16.62   .44*** chores/fam
Cameroon 5475 51.56 9.12 2.90 .94 .81 32.36 32.53   .99 fam
Djibouti 2790 50.14 9.45 2.95 .36 .72 6.35 6.29 1.05 work
Low HDI
Nigeria 17395 50.19 8.87 2.91 .63 .88 28.31 29.21   .96 fam
Togo 4545 50.45 9.11 2.88 .46 .74 28.96 28.93 1.00 fam
Gambia 6025 53.58 9.10 2.94 .42 .74 28.64 19.28 1.67*** fam
Côte d’Ivoire 6937 49.98 8.96 2.92 .38 .66 34.91 36.42   .93 fam
Guinea-Bissau 5220 48.64 9.03 2.88 .40 .88 39.07 42.42   .89* fam
Burundi 5454 51.39 9.32 3.00 .76 .55 16.57 17.74   .90 chores
Mozambique 9294 52.00 9.05 2.87 .76 .67 21.09 18.85 1.17** fam
Central African Republic 6586 51.15 8.72 2.88 .63 .73 48.71 42.75 1.27*** fam
Sierra Leone 5603 50.21 8.78 2.91 .32 .71 46.30 45.58 1.05 fam
HDI N/A
Iraq 11851 48.82 9.24 3.00 .98 .77 7.36 10.04   .70*** fam
Somalia 3990 49.02 8.79 2.87 .41 .72 56.01 46.12 1.48*** fam
TOTAL 233980 49.54 9.27 2.92 1.05 .96 16.82 18.10   .88*** fam
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Note. fam = family work; work = work outside the home; chores = household chores.

a

Mother education is rated as 0 = none or preschool, 1 = primary school, nonstandard curriculum, religious school, 2 = secondary, vocational, tertiary school, and 3 = higher education.

b

The type of work that accounted for the largest share of child labor. When the largest share differed between girls and boys, we report girls’ largest share/boys’ largest share.

c

For boys, there was a tie between chores and work.

*

p ≤ .05.

**

p ≤ .01.

***

p ≤ .001.

Procedures

We used the Multiple Indicator Cluster Survey (MICS3), the Gender Relative Status Index (GRS; Beneria & Permanyer, 2010; Permanyer, 2010), the Gender Inequality Index (GII; UNDP, 2011), and the Human Development Index (HDI). Additional information about the MICS3, GRS, GII, and HDI is available in Chapter II (Bornstein et al., 2016).

MICS3 Child labor module

The mother of each child between 5 and 14 years indicated whether the child had worked outside the home in the past week (0 = No, 1 = Yes) and whether the child had been paid for this work (0 = No, 1 = Yes). Mothers also estimated the number of hours the child had worked outside the home in the past week. Next, mothers indicated whether the child had engaged in family work (like a family farm or business) or helped with household chores (like shopping, collecting firewood, fetching water, and childcare) in the past week (0 = No, 1 = Yes), and estimated the number of hours the child had engaged in family work and household chores in the past week.

Following UNICEF (2006) we computed a child labor index, combining work outside the home, family work, and excessive housework into a single indicator. Children aged 5 to 11 were considered to engage in child labor if they had worked for 1 hour or more (for the family or outside the family) and/or had engaged in 28 or more hours of housework. Children aged 12 to 14 were considered to engage in child labor if they had worked for 14 or more hours (for the family or outside the family) and/or had engaged in 28 or more hours of housework per week. Allowing older children to work up to 2 hours per day without being counted as child labor accounts for the potential benefits associated with small amounts of work in this age group (Larson & Verma, 1999). The age group employed in the current sample and the definitions of child labor employed (i.e., excluding <14 hours of work in preteens, and reasonable hours of household chores for all ages) circumscribed our investigation to child labor that is likely to interfere with healthy child development. Supporting the use of 28 hours as the cut-point for excessive household chores, Allais (2009) and the ILO (2009) both reported that girls who do 28 or more hours of household chores per week are over 20% less likely to be enrolled in school compared to girls who do fewer than 14 hours of chores. The negative impact of 28 hours of household chores on school enrollment for boys was only about half that of girls. In addition to the child labor index, we explored the three components of work (work outside the home, family work, and excessive household chores) separately.

Analytic Plan

First, to determine whether girls and boys engaged in similar types and amounts of labor, we explored the child labor index and three components of work with binary logistic regressions. We modeled main effects and the interaction between child Gender and Country. Next, the effect sizes for child gender for each country (i.e., odds ratios) were correlated with the country’s HDI and the GRS and GII with and without controlling for the country’s HDI.

For the logistic regressions, we used child age and maternal education as covariates. Older children were generally more likely to engage in labor, rs(233,127 to 233,573) = −.00 to .10, ps = ns to .001. Children from families where the mother had higher education engaged in less labor, rs(232,776 to 233,217) = −.06 to −.19, ps < .001. There were also large differences in maternal education across countries, F(37, 233,597) = 3,956.57, p < .001, η2 = .385, and controlling for maternal education accounts for across-country differences as well as within-country differences, yielding more precise statistical estimates of gender differences in child labor.

RESULTS

The results supported our hypothesis that more boys than girls engaged in child labor overall as well as labor outside the home and family work, and more girls than boys engaged in excessive household chores. However, the pattern of relations was not consistent across countries, and gender differences were largely unrelated to national indicators of gender equality and sociodemographic development.

Child Labor Index

The Gender by Country interaction for child labor in the past week was significant, Wald χ2(37) = 809.20, p < .001, as were the main effects of gender, Wald χ2(1) = 118.74, p < .001, OR = .88, and country, Wald χ2(37) = 15,990.58, p < .001. Deconstructing the interaction (Table 6.1), in 10 countries boys were more likely than girls to have worked in the past week, in 6 countries girls were more likely than boys, and in the remaining 22 countries there was no difference between girls and boys.

The child labor index is an aggregate of work outside the home, family work, and excessive household chores. When we looked at which type of work contributed the most to the child labor index in each country, a distinct pattern emerged (Table 6.1). In high-HDI countries, the largest share of child labor was either from work outside the home or family work. In medium-HDI countries, there was a mix of work outside the home, family work, and chores (usually only for girls). In low-HDI countries, the largest share of child labor came from family work for girls and boys in every country except Burundi, where chores prevailed for both genders.

Looking across all 38 countries, boys were more likely than girls to have engaged in child labor in the past week (last row of Table 6.1), but the pattern varied considerably by country. The largest share of child labor, contributed by either work outside the home, family work, or household chores, varied by the economic level of the country. However, in some countries more than one type of child labor was prominent. Next, we explore gender differences in each type of labor.

Work Outside the Home

Work outside the home included any work (paid or unpaid) done for someone outside the household in the past week. The Gender by Country interaction for work outside the home in the past week was significant, Wald χ2(37) = 259.95, p < .001, as were the main effects of gender, Wald χ2(1) = 92.33, p < .001, OR = .82, and country, Wald χ2(37) = 6746.59, p < .001. Deconstructing the interaction (Table 6.2), controlling for child age, boys were more likely than girls to have engaged in child labor outside the household in the past week in 5 countries, girls were more likely than boys in 1 country (Viet Nam), and there was no difference between girls and boys in the remaining 32 countries.

TABLE 6.2.

PERCENTAGES OF CHILDREN WHO ENGAGED IN WORK OUTSIDE THE HOME, FOR THE FAMILY, OR DOING EXCESSIVE HOUSEHOLD CHORES IN THE PAST WEEK, BY GENDER AND HDI

Work outside the home Family work Household chores
Country Girls
%		 Boys
%		 OR Girls
%		 Boys
%		 OR Girls
%		 Boys
%		 OR
High HDI
Trinidad & Tobago 0.11 0.59   .19 0.45 0.47   .98 0.11 0.12   .89
Montenegro 4.17 5.56   .75 3.94 3.93 1.04 0.23 0.21 1.15
Serbia 3.16 3.91   .80 0.88 1.58   .54 0.37 0.07 5.20
Belarus 4.37 4.38 1.01 1.77 2.34   .75 0.00 0.00     n/a
Macedonia 4.28 3.20 1.36 1.43 1.07 1.39 0.14 0.00     n/a
Albania 2.30 1.91 1.20 6.14 10.48   .53*** 0.29 0.08 2.89
Kazakhstan 1.22 1.24   .99 0.91 1.60   .56* 0.66 0.72   .92
Bosnia and Herzegovina 0.80 1.22   .64 3.18 4.37   .71 0.00 0.00     n/a
Medium HDI
Thailand 2.66 2.40 1.09 5.80 6.32   .91 0.31 0.36   .82
Ukraine 3.35 3.48   .96 5.71 8.70   .64* 0.37 0.12 3.16
Jamaica 2.77 3.16   .86 1.23 1.19 1.02 1.23 0.89 1.39
Suriname 1.87 2.68   .66 1.40 1.86   .78 0.79 0.32 2.32
Georgia 14.01 15.54   .88 5.34 6.07   .87 0.58 0.85   .69
Syrian Arab Republic 0.43 2.09   .18*** 1.32 2.45   .53*** 0.57 0.34 1.59
Guyana 5.16 6.35   .82 14.18 14.51 1.00 0.58 0.43 1.68
Mongolia 0.88 1.44   .59 7.32 9.84   .71** 9.35 9.14   .97
Viet Nam 1.70 0.99 1.74* 12.72 14.20   .86 4.02 1.98 2.07***
Uzbekistan 2.13 2.70   .78 0.66 1.09   .59 0.00 0.00     n/a
Kyrgyzstan 0.76 1.27   .59 0.69 1.53   .45* 0.90 0.95   .93
Tajikistan 3.92 5.07   .77 0.97 1.78   .55* 5.90 5.07 1.23
Laos 1.25 1.67   .69 8.85 7.55 1.16 2.41 0.92 2.48***
Yemen 2.10 2.11 1.00 10.09 12.31   .80 13.32 6.32 2.39***
Mauritania 1.27 1.98   .64* 10.16 13.28   .75*** 3.60 3.22 1.11
Ghana 8.70 7.07 1.27 28.59 30.70   .92 3.20 1.95 1.70*
Bangladesh 2.05 4.49   .44*** 2.71 11.87   .20*** 3.97 0.87 4.84***
Cameroon 14.13 15.23   .92 15.85 17.38   .90 7.99 4.84 1.71***
Djibouti 3.86 4.46   .90 2.88 2.24 1.33 0.22 0.51   .39
Low HDI
Nigeria 10.13 10.62   .96 20.21 21.20   .95 2.13 1.93 1.08
Togo 7.85 7.83 1.01 21.10 22.30   .93 4.14 1.95 2.16***
Gambia 3.87 3.47 1.12 24.46 16.39 1.67*** 2.18 1.18 1.67*
Côte d'Ivoire 2.94 3.63   .80 29.42 33.39   .83*** 6.40 1.91 3.50***
Guinea-Bissau 4.18 4.82   .89 34.44 39.00   .84** 4.62 4.00 1.16
Burundi 2.33 1.94 1.18 3.66 5.96   .61*** 12.02 11.11 1.07
Mozambique 1.08 1.64   .66* 13.62 14.29   .95 8.76 4.70 2.04***
Central African Republic 15.08 15.01 1.00 34.61 29.78 1.25*** 11.08 7.72 1.50***
Sierra Leone 15.81 16.71   .95 38.61 38.26 1.03 2.01 1.31 1.48
HDI N/A
Iraq 1.31 3.23   .40*** 4.39 6.58   .65*** 2.44 0.99 2.49***
Somalia 2.62 1.78 1.47 37.63 39.54   .91 32.63 16.65 2.48***
TOTAL 4.14 4.90   .82*** 10.97 13.04   .78*** 4.01 2.25 1.84***
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Note. n/a = statistics not available because of no variance in one or both groups.

*

p ≤ .05.

**

p ≤ .01.

***

p ≤ .001.

Looking across all countries, boys were more likely than girls to have worked (last row of Table 6.2), but the pattern varied considerably by country. Some countries had very similar proportions of girls and boys working outside the household (e.g., Yemen and Cameroon), and others had quite different proportions of girls and boys working outside the household (e.g., Syrian Arab Republic and Iraq).

Family Work

Family work included any work done for a member of the household, including family farm or business work, but not household chores. The Gender by Country interaction for family work in the past week was significant, Wald χ2(37) = 1,095.55, p < .001, as were the main effects of gender, Wald χ2(1) = 326.61, p < .001, OR = .78, and country, Wald χ2(37) = 13,563.30, p < .001. Deconstructing the interaction (Table 6.2), in 13 countries boys were more likely than girls to have done family work in the past week, in 2 countries (Gambia and Central African Republic) girls were more likely than boys, and in the remaining 23 countries there was no difference between girls and boys.

Looking across all countries, boys were more likely than girls to have engaged in child labor for the family farm or business in the past week (last row of Table 6.2), but the pattern varied considerably by country. Some countries had very similar proportions of girls and boys doing family work (e.g., Montenegro and Guyana), but proportions were quite different in other countries (e.g., Bangladesh and the Gambia).

Household Chores

Household chores were (usually unpaid) work children did for 28 or more hours/week around the household, including childcare, fetching water or wood, cooking, and cleaning. The Gender by Country interaction for excessive household chores in the past week was significant, Wald χ2(37) = 1,616.61, p < .001, as were the main effects of gender, Wald χ2(1) = 557.23, p < .001, OR = 1.84, and country, Wald χ2(37) = 6,821.30, p < .001. Deconstructing the interaction (Table 6.2), in 13 countries girls were more likely than boys to have done excessive household chores in the past week, and in the remaining 21 countries for which tests could be computed there was no difference between girls and boys. For four countries (Belarus, Macedonia, Bosnia & Herzegovina, and Uzbekistan), no boys and/or no girls engaged in 28 or more hours of household chores, and statistics could not be computed.

Looking across all countries, girls were more likely than boys to have done excessive household chores in the past week (last row of Table 6.2). In no country were boys significantly more likely than girls to do excessive household chores, but girls’ and boys’ engagement was similar in some countries (e.g., Trinidad & Tobago and Burundi).

Relations between Gender Effect Sizes and National Indices

To assess whether differences between participation in child labor of girls and boys reflected national gender disparities and sociodemographic development, we computed correlations of the effect sizes for child gender for each country with national level GRS, GII, and HDI scores (Table 6.3). Larger effect sizes indicate that girls are more likely than boys to engage in the activity, and smaller effect sizes indicate that boys are more likely than girls to engage in the activity. Child labor was unrelated to national indicators of gender equality. In countries with lower sociodemographic development, girls were more likely than boys to engage in child labor overall and to engage in excessive household chores in the past week. However, the countries with lower gender equality also tended to have lower overall sociodemographic development. To remove the variance in the gender indices associated with overall economic level of the country, we controlled the correlations with the GRS and GII for the HDI, and two relations became significant. Controlling for the HDI, in countries with better national gender equality (as measured by the GII only), girls were more likely than boys to work outside the home in the past week, and boys’ engagement in excessive household chores approached that of girls.

TABLE 6.3.

CORRELATIONS OF CHILD GENDER EFFECT SIZES WITH COUNTRY-LEVEL GENDER AND SOCIODEMOGRAPHIC DEVELOPMENT

Labor in the past week GRS GII HDI
Child labor −.21/.07 .27/.13 −.39*
 Work outside the home .17/.32 −.17/−.43* −.11
 Family work −.26/−.13 .16/−.07 −.26
 Household chores −.19/−.22 .32/.49* −.03
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Note. GRS = Gender Relative Status Index. GII = Gender Inequality Index. HDI = Human Development Index. Correlations after the slash control for the 2009 Human Development Index.

*

p ≤ .05.

DISCUSSION

The incidence of child labor varied greatly across countries. In some countries, fewer than 1% of children engage in child labor, but in other countries, as many as half of 5- to 14-year-old children engage in child labor. Overall, these findings for LMIC support the existing western HIC literature on gender differences in child labor. Considering all types of child labor at once (as measured by the child labor index), a slightly higher percentage of boys worked than girls across all 38 LMIC, but there were significant gender differences in fewer than half of the countries, and in some countries girls worked more than boys. Overall, more boys in this study worked outside the home and did family work, and more girls worked inside the home. However, these patterns were not universal across all countries either. In some countries, more girls worked outside the home and did family work than boys. The pattern of relations for excessive household chores was somewhat more consistent. There were gender differences in one-third of the countries, with a higher percentage of girls doing excessive chores than boys, and in no country did significantly more boys than girls do excessive chores.

Gender Differentiated Work

The global pattern of gender relations suggests that parents allow their children to work in ways that reflect macrosystem influences (e.g., current and future gender-differentiated roles in society). In many LMIC, girls will become mothers and housekeepers, and boys will work outside the home. Hence, their patterns of child labor may reflect the general patterns of adult time use. However, the gender difference effect sizes were generally small, and we did not find consistent, strong relations between gender differences in child labor and gender inequality indices at the national level. When controlling for the overall economic level of the country, the only significant findings were that girls were more likely than boys to work outside the home and girls’ and boys’ engagement in excessive household chores was more similar in countries with better national gender equality.

The findings of this study support the importance of considering excessive household chores (≥ 28 hours/week) as child labor. Girls were sometimes more likely to engage in household chores than boys. In all countries, the average number of hours spent doing household chores was below the threshold of 28 hours (e.g., 4 hours/day), but sometimes a large percentage of children in a country met the threshold. For example, in Somalia, 33% of girls and 17% of boys spent 28 hours/week or more on household chores (even higher percentages did family work), but fewer than 3% of girls and boys worked outside the home in Somalia (Table 6.2). Any intervention designed to reduce or eliminate child labor should be informed by the types of child labor that children are employed in as well as the reasons for their employment.

One striking example of a country that did not follow the overall pattern of gender relations across LMIC was the Gambia. More girls than boys in the Gambia were engaged in child labor overall as well as every individual type of labor (work outside the home, family work, and household chores; although the difference was not significant for work outside the home). Kea (2007) explored girls’ work in Brikama, the Gambia, explaining that there is a strong cultural expectation for girls to work both in the household and on the farm. Girls’ higher rates of child labor in the Gambia can be explained by a host of macrosystem factors, including the reliance of local economies on crop farming, cultural norms of gendered behavior (e.g., women do farm work and men do more skilled jobs), the introduction of double-shift schooling that allows children to attend school for part of the day and then work for the rest of the day, and the cultural practice of “loaning” girls to relatives or patrons to live and work in other households (Kea, 2007).

Variability Across Countries

The variability in girls’ and boys’ labor across countries was striking. A relatively small percentage (< 12%) of children in high-HDI countries was engaged in child labor. In low-HDI countries, children were more likely to engage in labor (most > 20%; Table 6.1). Each HDI group contained countries where more girls than boys engaged in labor and more boys than girls engaged in labor. Smaller percentages of children in high-HDI than low-HDI countries also engaged in family work and excessive household chores, but work outside the home seemed to be less tied to HDI. Looking across types of labor, countries varied in whether work outside the home, family work, or excessive household chores accounted for the largest percentage of work. For example, Georgia, Viet Nam, and Burundi all had child labor rates in the 15%-20% range, but the relative contributions of different types of work diverged. In Georgia, the largest share of child labor came from work outside the home; in Viet Nam, the largest share of child labor came from family work; and in Burundi, the largest share of child labor came from excessive household chores. This inherent variability highlights the need to assess the prevalence of specific types of child labor, working conditions, and motivations associated with child labor in each country.

Limitations

This study has limitations that raise additional questions about gender in LMIC. Some general and specific limitations associated with the MICS3 are addressed in Bornstein, Putnick, Bradley, Deater-Deckard, and Lansford, Chapter VII (2016). Information that was gathered on child labor in the MICS3 is somewhat incomplete. We do not know the sector of work a child is doing (e.g., agricultural, trade, manufacturing), their working conditions, the types of tasks in which they engage on the job (e.g., operating machinery, childcare, cleaning), the psychosocial impact on the child (e.g., stressful and depressing vs. motivating and self-esteem building), and what factors drove the child to work. We might have found more gender differentiated work within the broad categories of work outside the home, family work, and household chores if the MICS collected more detailed data about the work (e.g., girls do more commercial sewing, weeding, and childcare, and boys do more mining, planting, and firewood collection). Another limitation is the seasonality of data collection. Data for some children may have been collected during school breaks or critical harvesting times, which could lead to over-estimates of some kinds of work in some areas. Potential over-estimates may also be offset by the parent-report nature of the MICS3. Child labor is a sensitive subject (especially in the context of laws governing child labor, which some countries have in place), so reporter bias and under-reporting may be an issue.

Conclusions and Implications

More in-depth research is needed to document the impact of varying amounts and types of child labor on child development. In some countries, child labor could have a positive impact on children’s psychosocial well-being as well as their future earnings and job prospects because they have few alternatives available for education or high-level employment. The link between education and child labor also needs to be explored across countries. For example, although child labor may decrease school attendance and performance (Beegle et al., 2009; Fares & Raju, 2007; Gibbons et al., 2005; Guarcello et al., 2008; Heady, 2003; Huebler, 2008; Orazem & Gunnarsson, 2003), child labor may not have detrimental effects on the child if the labor is paired with continued education, or if it is directly relevant to a future career. These effects are most likely moderated by the country of residence and/or the family’s socioeconomic status.

Much more research is also needed to understand factors that encourage and discourage child labor. There may be common factors, such as poverty, but there are certainly also country-, community-, and family-specific factors that influence the decision to put a child to work. A thorough investigation of these factors, such as that done by Kea (2007) for one community in the Gambia (see also Admassie, 2003, for Ethiopia), is needed for each country/community to inform effective interventions. To date, some governmental and non-governmental organizations have focused on global strategies to reduce child labor. One global strategy has been to set a minimum age for labor, another to ban child labor altogether (ILO, 1973, 1999). These strategies will likely fail to eradicate child labor and improve living conditions for children (Budhwani, Wee, & McLean, 2004; Levine, 2011; Morrow, 2010) because a host of factors promotes or maintains child labor, including (but not limited to) the unavailability or prohibitive costs of quality schooling, gender-based cultural norms, the unavailability of alternative labor sources, and individual family needs. Another more promising global strategy for reducing child labor is to improve access to schooling. Dessy (2000) argued that free and compulsory education could improve later job prospects and encourage families to choose school over work, but some incentives may be needed to offset immediate family losses associated with removing children from the workforce. Free education may also discourage child labor because many children work to pay for school (Omokhodion et al., 2006). Educating girls, in particular, may be the best long-term strategy for reducing child labor. Leinberger-Jabari, Parker, and Oberg (2005) and the ILO (2009) suggested that educating girls would have a positive cascading effect on the economy and human development (at least in the long-term) because more educated girls delay marriage and childbearing, are less likely to be poor, have children with fewer health and growth problems, and ensure that their offspring become educated as well.

The MICS3 yields comparable estimates of the percentages of girls and boys working outside the home, doing family work, and doing excessive household chores. For several countries, this study provides the first globally comparable estimates of the burden of child labor in girls and boys. However, this study is just a first step to describing and comparing child labor in girls and boys in LMIC. Only with a full understanding of the scope of child labor across types, countries, and genders can local governments and NGOs specifically target the types of child labor that affect girls and boys, work to protect children from ill effects, and promote positive effects of employment in children at a young age.

Acknowledgments

This research was supported by the Intramural Research Program of the NIH, NICHD. We thank UNICEF and participating countries for collecting the data.

Contributor Information

Diane L. Putnick, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Marc H. Bornstein, Eunice Kennedy Shriver National Institute of Child Health and Human Development

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