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Prohibiting Child Labor

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International Journal of Educational Research
Volume 60, 2013, Pages 38–45

Does prohibiting child labor increase secondary school enrolment? Insights from a new global dataset * Jody Heymann * Amy Raub1, , * Adele Cassola2, * UCLA Fielding School of Public Health, 650 Charles E Young Dr S, Los Angeles, CA, U.S., 90095 * http://dx.doi.org/10.1016/j.ijer.2013.01.003, How to Cite or Link Using DOI * Permissions & Reprints

Abstract
Objective
This article examines the association between minimum age of employment and secondary school enrolment.
Methods
We reviewed child labor laws for 185 states in 2008 and 2012. We assessed how many countries had a minimum age of employment of 15 or over and tested the association between these laws and secondary enrolment rates, after controlling for per-capita GDP, level of urbanization, and compulsory lower secondary education.
Results
A minimum age of employment of 15 or higher was significantly associated with increased secondary enrolment for girls, boys, and overall.
Conclusions
Combining a legislated minimum age of employment of 15 or higher with compulsory education may strengthen children's opportunity to achieve a secondary education.

Highlights
► We reviewed child labor laws for 185 countries in 2008 and 2012. ► 45 countries allow children to work before the ILO-recommended age of 15. ► Countries banning work until 15 have an 8 percentage point higher net secondary enrolment. ► Findings hold for girls (9.5 percentage points) and boys (7.8 percentage points). ► The impact is independent of per-capita GDP, urbanization and compulsory education.
Keywords
* Child labor laws; * Minimum age of employment; * Compulsory education; * Secondary education; * Enrolment rates

1. Introduction
Completing secondary school has a crucial impact on individuals’ income, employment and health outcomes across a wide range of economies. Men and women in OECD countries who have attained an upper secondary education are nearly 10 percentage points less likely to be unemployed than those who have only finished primary school, and 4 percentage points less likely to be unemployed than individuals with a lower secondary education (OECD, 2008). In eight low- and middle-income countries, men who have completed secondary school earn, on average, twice as much as their peers who have a primary education and 36 percentage points more than those with a lower secondary qualification. The discrepancy is even greater among women (UNESCO Institute for Statistics & OECD, 2002).
Increasing educational attainment matters for national economic outcomes as well. Data from 50 countries demonstrates that raising the average years of schooling completed at the population level by an additional year could increase Gross Domestic Product (GDP) growth by up to one percent annually once the impact of improved cognitive skills is accounted for (UNESCO, 2009). In 65 low- and middle-income states, ensuring that girls complete secondary school at the same rate as boys would increase GDP by an aggregate $92 billion each year (Plan International, 2008).
Finishing secondary school has an equally critical impact on health outcomes. Individuals with a secondary education have been found to enjoy longer life expectancy without experiencing cognitive impairment (Lievre, Alley, & Crimmins, 2008); are more likely to comply with dietary guidelines (Roos, Lahelma, Virtanen, Prättälä, & Pientinen,1998) and treatment regimens (Goldman & Smith, 2002); are at lower risk of all-cause mortality (Khang, Lynch, & Kaplan, 2004); and enjoy higher total and healthy life expectancy (Crimmins & Saito, 2001) than those who have only completed primary school. Even achieving a few years of secondary school has been shown to substantially increase overall and healthy life expectancy (Bossuyt, Gadeyne, Deboosere, & Van Oyen, 2004) and reduce the risk of contracting HIV (de Walque, 2007). Although increased years of schooling have an almost universally positive effect on individuals’ health regardless of the level of education they have attained, achieving a secondary school qualification has been found to have a threshold effect on certain health outcomes, including reducing risk of depression (Chevalier & Feinstein, 2006), increasing rates of cervical cancer screening (Sabates & Feinstein, 2004), and raising the probability of being in good health (Gerdtham & Johannesson, 1999).
For the 74 million secondary-aged youth who were out of school in 2008 (UNESCO, 2011), these data predict lifelong disadvantage in employment, earnings and health outcomes. Gross enrolment rates at the secondary level in 2008 were just 67 percent globally and 43 percent in low-income countries (UNESCO, 2011).
National economic wealth is a predictor as well as an outcome of differences in countries’ educational attainment, as lower-income countries are less likely to be able to invest adequate public resources in the development of educational systems that encourage and sustain high rates of enrolment. Within countries, children from poorer families are also less likely to attend school. In the Middle East and North Africa, West and Central Africa, and Latin America and the Caribbean, children from the poorest households are between 3 and 4.4 times more likely to be out of primary school than their wealthier peers (UNESCO Institute for Statistics, 2005); without a primary education, secondary school is far beyond their reach.
Whether education is compulsory affects educational participation, especially among children from lower-income households (Borkum, 2012, Brunello et al., 2009, Deininger, 2003, Nielsen, 2009, Oreopoulos, 2005,Oreopoulos, 2006 and Zhang and Minxia, 2006). Moreover, a country's level of urbanization is positively associated with school enrolment for a variety of reasons, including the higher returns to education in urban settings (Behrman, Duryea, & Szekely, 1999), the lower per-student cost of providing education in more highly populated areas (Behrman et al., 1999), and the greater ease of hiring teachers in areas with greater population density and better infrastructure (Arends-Kuenning & Duryea, 2006).
Beyond low income and rural residency, several empirical studies indicate that children who work are less likely to attend school and have poorer educational outcomes than those who do not. There are an estimated 215 million child laborers around the world (International Labour Organization, 2010). Boozer and Suri (2001)isolated the impact of labor on children's school participation by using the different rainfall patterns between Northern and Southern Ghana as an exogenous explanation for variation in demand for children's work. Their study analyzed household survey data for individuals aged 7–18 and found that each hour of work that a child performed decreased their school attendance by 0.38 h (Boozer & Suri, 2001). In a similar study, Beegle, Dehejia, and Gatti (2004) exploited the change in community-level price of rice and occurrence of disasters to explain variation in child labor independently of household choices in Vietnam. Drawing on panel data spanning a period of 5 years, they demonstrated that working seven hours per week (the mean) led to a 30 percent decrease in a child's likelihood of attending school and a six percent reduction in average years of schooling completed (Beegle et al., 2004). Assaad, Levison, and Zibani (2010) found a significant, direct, and negative effect of working 14 hours or more per week on girls’ school attendance in Egypt, even after controlling for individual and household characteristics.
Given the magnitude of the global child labor problem and the impact of secondary schooling on children's life chances, it is important to ask whether raising the legal age at which children are allowed to work would increase the overall probability of youth receiving a secondary school education. Recent evidence suggests that establishing a minimum age of employment reduces rates of child labor. An analysis of 16 countries found that the likelihood that a child will work for 28 or more hours per week doubles upon reaching the legal age of employment in their country (Blanco Allais, 2009). Fasih (2007) used a natural experimental approach to demonstrate that Pakistan's 1991 Employment of Children Act significantly decreased employment rates among those covered by its provisions, compared to a control group outside the law's purview.
Yet doubt remains both about the relationship between child labor legislation and economic need, and between child labor and overall educational outcomes once siblings are included. Several authors suggest that legal restrictions may be an ineffective pathway to eliminating child labor, and may even cause more harm by reducing household income or forcing children into illegal forms of employment (Basu and Van, 1998, Dessy and Pallage, 2005, Edmonds and Pavcnik, 2005 and Patrinos and Psacharopoulos, 1995). Substantial work hours clearly disadvantage working children's education, but their earnings may increase the probability that their siblings will go to school (Basu & Tzannatos, 2003).
Questions have also been raised as to whether conventional legislation can be an effective tool for decreasing girls’ labor participation and increasing their school enrolment (Assaad et al., 2010 and de Silva-de-Alwis, 2007). There are substantial gender differences in the type of work children perform and in household schooling choices. Boys typically work outside the home, while girls are disproportionately engaged in unpaid household chores (Assaad et al., 2010, Basu and Tzannatos, 2003, Blanco Allais, 2009,de Silva-de-Alwis, 2007 and Gunnarsson et al., 2006). As unpaid household work is much more difficult to regulate through legislation, minimum age of employment laws may be less effective as a pathway to increasing girls’ secondary school enrolment compared to boys’. In addition, girls are often disadvantaged in education due to cultural factors that lead parents to value their sons’ education more highly than their daughters’. When resources are scarce, female children in many countries are more likely to be withdrawn from school in order to earn the income that will enable their male siblings to be educated (Basu and Tzannatos, 2003 and de Silva-de-Alwis, 2007). It is therefore worthwhile to consider the impact of minimum age legislation and compulsory education policies on both genders separately.
Given the close relationship between employment and educational outcomes for children who work, the questions about the impact of child labor on educational opportunities for younger siblings, and the debate about the effectiveness of child labor legislation, it makes sense to examine empirically whether and how establishing the International Labour Organization (ILO)-benchmarked minimum age of employment of 15 or higher affects enrolment in secondary school. However, there has been no detailed exploration of the direct relationship between the minimum legal age of employment and school enrolment on a global scale. In this study, we used newly available global data on the legislated minimum age of employment to test the association of these laws with secondary school enrolment rates for males, for females, and overall, after controlling for national economic wealth, level of urbanization, and compulsory lower secondary education policies. Understanding how child labor legislation affects the secondary education opportunities of adolescents is critical considering the magnitude of the secondary-aged population that is out of school, the vast number of children who are engaged in work globally, and the importance of secondary education for children's income, employment and health outcomes.
2. Methodology
2.1. Data sources
In this study, we examined the employment protections offered to children globally and tested the association between a nationally legislated minimum age to work and secondary school enrolment rates. Specifically, we examined the number of countries worldwide that have a legislated minimum age of employment of 15 or over, which is the age recommended by the ILO in Convention 138 (International Labour Organization, 1973). To construct this indicator, this study draws on data we collected at the World Policy Analysis Centre at UCLA and McGill University. To obtain the information on legislated minimum ages of employment necessary for this analysis, we conducted a comprehensive review of all national labor legislation assembled by the ILO and available online through the NATLEX database. Legislation available through the World Bank's “Doing Business” online law library, the Lexadin World Law Guide legislation database, as well as in hard copy through Harvard University, McGill University and the ILO headquarters library, was also analyzed. The research team was able to obtain and standardize detailed information on child labor provisions for 185 of the 193 United Nations member states, more than has ever been available in a comparable format. The database used for this study contains data on legal minimum ages for children to participate in light work, hazardous work, general employment and full-time work, as well as specified exceptions to these age limits, levels of protection from the worst forms of child labor, legislated minimum wage and work hour protections for young workers, mandated hours of rest and protection from night work, and mechanisms for monitoring and enforcing these laws.
2.2. Analyses conducted
We examined the number of countries that ensure a minimum age of work, as well as how many countries protect children from working until age 15 or over. We also used ordinary least squares regressions to test the association between having a minimum age of employment of 15 or older and secondary school enrolment rates overall and by gender, while controlling for national economic resources and the percentage of the population living in urban areas (measures found in other research to be associated with educational enrolment rates). To control for other policies that might directly influence enrolment rates, we then introduced an additional control for compulsory education at the lower secondary level.
Table 1 provides a summary of the variables included in the analyses. Observations indicate the number of countries with data available for the regression analysis.
Table 1. Variable summary. Variable | Observations | Minimum | Mean | Maximum | Gross secondary enrolment rate | 133 | 12.6 | 79.1 | 131.3 | Net secondary enrolment rate | 94 | 10.2 | 69.0 | 99.5 | Net secondary enrolment rate for females | 93 | 7.8 | 69.2 | 99.9 | Net secondary enrolment rate for males | 93 | 12.2 | 68.3 | 99.4 | Minimum age of work with parental permission is 15 or older (1 = Yes, 0 = No) | 133 | 0 | 0.7 | 1 | PPP adjusted per-capita GDP ($) | 133 | 297 | 12,100 | 70,981 | Percentage of population living in an urban area | 133 | 10.4 | 55.5 | 97.4 | Lower secondary is compulsory (1 = Yes, 0 = No) | 125 | 0 | 0.7 | 1 |
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2.3. Outcomes examined
The gross and net enrolment ratios for secondary education used in this study were drawn from the UNESCO Institute for Statistics (2011) database of education indicators. UNESCO collects information on education policies and outcomes for over 200 countries and territories from governments and international organizations. Data used is the most recent data available for each country from 2008 to 2010. Gross secondary enrolment ratios are calculated as the number of students enrolled in secondary education divided by the number of children in the country who are of official secondary school age. Gross enrolment ratios may exceed 100% if students older or younger than the official school age are enrolled in that level of education. This is particularly common in low-income countries with high repetition rates at the primary level, but also occurs at the secondary level for more than 30 countries in our sample. Net enrolment ratios adjust for these problems by only including students who fall within the official school age range in the calculation of those attending. Net enrolment ratios cannot exceed 100% due to this adjustment, but net enrolment ratios are available for fewer countries than gross enrolment ratios. Despite the limitations of the gross enrolment data, gross enrolment was analyzed in addition to net enrolment to test the robustness of the findings on a larger sample. Net enrolment ratios by gender were also included to test whether policy impacts girls as well as boys.
2.4. Key independent variables
2.4.1. Minimum age of work
We examined an indicator of the existence of a minimum age to work of 15 or higher. The data used in analysis reflects policies in place in 2008. The indicator variable was defined as equal to 1 if the country sets a minimum age to work with parental permission of 15 or higher and equal to 0 otherwise. Parental permission was included to make valid comparisons across countries, as some countries specify a minimum age for general employment but allow children to work at younger ages with parental consent, while others establish a minimum age to work and also require parental consent for children of that age to work. Additionally, although some countries specify a separate and lower minimum age at which children are allowed to perform work that does not jeopardize their health or education (commonly referred to as light work), the age for light work was not used to construct this variable. Since light work by definition cannot interfere with a child's education, we would not expect the minimum age to perform such work to have an impact on school enrolment.
2.4.2. Per capita gross domestic product
In this study, we used the per capita GDP in 2008 from the World Bank's World Development Indicators (World Bank, 2008a) as an indicator of national economic resources. Data were measured in purchasing power parity adjusted constant 2005 international dollars. A log transformation of per capita GDP was used instead of a linear term because changes in income at the lower end of the income spectrum have been found to have a larger impact on enrolment than changes in wealth at the higher end of the income spectrum.
2.4.3. Percent urban
A country's level of urbanization was included as a control in the models. We extracted our data on the percentage of the population living in urban areas in 2008 from the World Bank's World Development Indicators (World Bank, 2008b).
2.4.4. Compulsory education
Since this study is concerned with enrolment rates at the secondary level, we controlled for whether the beginning of secondary school is compulsory. This variable is equal to 1 if lower secondary education is mandatory, and 0 otherwise. Our data are drawn from the World database on comparative education policies for 174 countries from 2008. To obtain this information, researchers reviewed national governments’ reports to the UNESCO International Bureau of Education, the 48th International Conference on Education Reports published by national governments in 2008, information available through the Eurydice – Network on education systems and policies in Europe, and official documents accessible through Planipolis, a portal of education plans and policies from UNESCO Member States. Although governments’ self-reports may overestimate the accessibility of education in their countries, these documents provide an important source of comparison of education policy around the world.
Compulsory education and minimum age to work protections are complimentary policies, which are not highly correlated in our dataset. The correlation coefficient is only 0.20. Table 2 provides the correlation coefficients of all control variables included in the regressions.
Table 2. Regression variable correlation coefficients. Variable | Work not allowed until age 15 | Natural log of per-capita GDP | Percentage of population living in urban area | Natural log of per-capita GDP | 0.30 | | | Percentage of population living in urban area | 0.13 | 0.75 | | Lower secondary is compulsory | 0.20 | 0.50 | 0.37 |
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3. Results
3.1. Descriptive analyses
Around the world, 179 countries (96%) have set a minimum age for children to work with parental permission. Of these, 45 countries (24%) allow children to work before the ILO-recommended age of 15. Four countries (2%) allow work at the age of 12 and an additional two (1%) allow work at age 13. Six countries (3%) have no explicit minimum age for a child to work with parental permission. High-income countries are more likely than low-income countries to have a minimum age to work of 15 or higher (see Table 3). Legislation of minimum age to work also varies greatly by region. All but one country (98%) in Europe and Central Asia has a minimum employment age of 15 or higher, compared to only one country (12%) in South Asia.
Table 3. Summary of child labor legislation by region and income. | 2008 Labor legislation minimum age for work 15 or more | 2012 Labor legislation minimum age for work 15 or more | Americas | 20 (61%) | 20 (61%) | East Asia and Pacific | 19 (70%) | 19 (70%) | Europe and Central Asia | 49 (94%) | 51 (98%) | Middle East and North Africa | 16 (84%) | 17 (89%) | South Asia | 1 (14%) | 1 (12%) | Sub-Saharan Africa | 27 (57%) | 27 (57%) | Low income countries | 21 (60%) | 21 (60%) | Lower-middle income countries | 30 (58%) | 31 (58%) | Upper-middle income countries | 38 (78%) | 38 (78%) | High income countries | 43 (88%) | 45 (92%) |
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3.2. Multivariate models
A legislated minimum age to work of 15 or older was associated with significantly higher net and gross enrolment rates, even after differences in national income and urbanization levels were taken into account. Setting the legal employment age at 15 or older was associated with a 9.2 percentage point higher gross secondary enrolment rate (p ≤ 0.01) (Table 4, Model 1) and similarly a 9.1 percentage point higher net secondary enrolment rate (p < = 0.01) (Table 5, Model 1). For the average low-income country in the regression sample, the model predicts that having a minimum age of work of 15 or higher would be associated with an increase of gross enrolment rates from 38.4% to 47.6% and an increase of net enrolment rates from 30.9% to 40.1%. Given the low levels of secondary school enrolment in many low-income countries, this represents a substantial potential increase in enrolment rates. When net enrolment rates were broken down by gender, the point estimate for female enrolment was slightly higher than for males. Net enrolment rates were 10.4 percentage points higher for females and 9.3 percentage points higher for males in countries with a minimum age to work of 15 or higher (p ≤ 0.01) ( Table 6 and Table 7, Model 1).
Table 4. Gross secondary enrolment rates. | Model 1 | Model 2 | | β | β | Work not allowed until age 15 | 9.20** | 8.68** | Lower secondary is compulsory | | 10.66** | Percentage of the population in urban area | 0.04 | 0.07 | Natural log of per capita GDP | 17.07*** | 14.98*** | Constant | −79.47*** | −71.08*** | N | 133 | 125 | R2 | 0.74 | 0.77 |
**
p ≤ 0.01.
***
p ≤ 0.001.
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Table 5. Net secondary enrolment ratios. | Model 1 | Model 2 | | β | β | Work not allowed until age 15 | 9.10** | 7.90* | Lower secondary is compulsory | | 15.33*** | Percentage of the population in urban area | −0.07 | −0.09 | Natural log of per capita GDP | 16.96*** | 14.77*** | Constant | −83.31*** | −73.47*** | N | 95 | 90 | R2 | 0.70 | 0.75 |
*
p ≤ 0.05.
**
p ≤ 0.01.
***
p ≤ 0.001.
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Table 6. Net secondary enrolment ratios for females. | Model 1 | Model 2 | | β | β | Work not allowed until age 15 | 10.37** | 9.47** | Lower secondary is compulsory | | 12.57** | Percentage of the population in urban area | −0.04 | −0.06 | Natural log of per capita GDP | 16.96*** | 15.28*** | Constant | −85.74*** | −78.49*** | N | 93 | 89 | R2 | 0.71 | 0.74 |
**
p ≤ 0.01.
***
p ≤ 0.001.
Table options
Table 7. Net secondary enrolment ratios for males. | Model 1 | Model 2 | | β | β | Work not allowed until age 15 | 9.30** | 7.75* | Lower secondary is compulsory | | 17.62*** | Percentage of the population in urban area | −0.10 | −0.12 | Natural log of per capita GDP | 16.65*** | 14.17*** | Constant | −79.68*** | −68.31*** | N | 93 | 89 | R2 | 0.68 | 0.75 |
*
p ≤ 0.05.
**
p ≤ 0.01.
***
p ≤ 0.001.
Table options
Next, we examined the relationship between enrolment rates and policy when compulsory schooling was also taken into account. Setting a legal age for employment as 15 or higher remained statistically significant and positive with only a small change in the magnitude, suggesting that both minimum age of employment laws and compulsory schooling policies contribute to higher enrolment rates. Specifically, when taking compulsory education into account, a minimum age of employment of 15 or higher was associated with an 8.7 percentage point increase in gross enrolment rates (p ≤ 0.01) and a 7.9 percentage point increase in net secondary school enrolment rates (p ≤ 0.05) ( Table 4 and Table 5, Model 2). For the average low-income country in the regression sample, this is estimated to be an increase from 25.4% to 33.3% net enrolment for countries without compulsory lower secondary education and an increase from 40.7% to 48.6% for countries with compulsory lower secondary. When enrolment rates were broken down by gender, the coefficient on minimum age of employment also remained statistically significant with only a small change in magnitude. Net enrolment rates were 9.5 percentage points higher for females (p ≤ 0.01) and 7.8 percentage points higher for males (p ≤ 0.05) in this model ( Table 6 and Table 7, Model 2).
4. Discussion
Worldwide, 52 countries (28%) allow children to be employed at age 14 or under with parental permission or have no minimum legislated age of employment. When exceptions to minimum age laws are taken into account, 81 countries (44%) allow 14-year-olds to work. Our analyses demonstrate that having a minimum age of employment of 15 or over is significantly associated with increased enrolment in secondary education for males, for females, and overall, independently of per capita GDP, the level of urbanization, and the availability of compulsory lower secondary education. Importantly, minimum age of employment laws are positively related to the enrolment rates of girls as well as boys, despite gender differences in the nature of labor participation and household schooling choices.
Although this study used enrolment rates as a measure of secondary school outcomes because these data are available globally, it will be important for future studies to measure secondary school attendance, completion rates, and learning outcomes to obtain a more detailed picture of how child labor legislation affects educational outcomes. Longitudinal datasets should be developed so that future studies can examine how changing policies impact outcomes, which would provide better evidence of causality. It will be particularly important for researchers to combine household surveys and longitudinal data in multi-level modeling that takes into account policy, community, and household characteristics simultaneously.
Longitudinal and multilevel datasets would also allow the exploration in further detail of the impact of compulsory schooling laws and regulations on the minimum age of employment. While these analyses suggest that both minimum age of employment and compulsory education laws are important to children remaining enrolled in school at the secondary level, the relationship between these policies is unclear. Is there an additional benefit to countries having both policies as the enforcement of compulsory education is easier if children do not have opportunities to legally work and vice versa? Or is it more important for countries to have at least one policy in place? Due to the limited sample size, we cannot fully explore these issues.
Despite these limitations, the data suggests an argument for governments to raise the age at which children can be employed to 15 or higher. In order to increase their effectiveness, such measures should include sanctions for employers who hire children below age 15. Combining a legislated minimum age with compulsory education will further strengthen children's opportunity to complete secondary school. When schooling is compulsory, states implicitly accept a greater responsibility for providing it; if compulsory secondary education laws compel the state to increase the quality and accessibility of education at this level, then education may be perceived as worth the opportunity cost of lost income from children's labor. At the same time, increasing the minimum age of employment and making secondary school compulsory will be most effective as pathways to improving school outcomes if combined with financial assistance for children's families to relieve the economic burden from lost income in the short-term (Arends-Kuenning and Amin, 2004, International Labour Organization, 2006, Tabatabai, 2010 and World Bank, 2001). In order for these laws to succeed without jeopardizing families’ ability to meet their needs in the long run, they should also go hand in hand with measures to ensure that households can be sustained on adult incomes.
There is reason to believe that progress can be made in legislating against child labor. 161 countries around the world have ratified the ILO's 1973 Minimum Age Convention, which requires states to set a minimum age of general employment that ‘shall not be less than the age of completion of compulsory schooling and, in any case, shall not be less than 15 years,’ with only a 1-year difference permissible based on the level of economic and educational development. Furthermore, all but two countries have ratified the Convention on the Rights of the Child, which obligates states to set a minimum age of employment and recognizes ‘the right of the child to be protected from […] performing any work that is likely […] to interfere with the child's education’ (Office of the High Commissioner for Human Rights, 1989). The cost of eliminating child labor as a constraint on children's education is not necessarily prohibitive: it is estimated that on a national scale, the benefits of policies that eradicate child labor and universalize primary and lower secondary education would outweigh the costs by 6.7–1 over a twenty-year period (International Programme on the Elimination of Child Labour, 2003).
Prohibiting youth from working until at least the age of 15 and making secondary education compulsory can change the way families calculate the costs and benefits of sending their children to school. If adult wages rise and youth educational attainment increases as a result of child labor bans, countries can expect to experience a decrease in overall poverty and growth in human capital.
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Retrieved from: http://www.ilo.org/ilolex/cgi-lex/convde.pl?C138. * 5. * International Labour Organization, 2006 * International Labour Organization * Eliminating child labour: The promise of conditional cash transfers * International Labour Office, Geneva (2006) * 6. * International Labour Organization, 2010 * International Labour Organization * Accelerating action against child labour: Report of the director-general, international labour conference 99th session * International Labour Office, Geneva (2010) * 7. * International, 2003 * International Programme on the Elimination of Child Labour * Investing in every child: An economic study of the costs and benefits of eliminating child labour * International Labour Office, Geneva (2003) * 8. * Khang et al., 2004 * Y.H. Khang, J.W. Lynch, G.A. Kaplan * Health inequalities in Korea: Age- and sex-specific educational differences in the 10 leading causes of death * International Journal of Epidemiology, 33 (2) (2004), pp. 299–308 * 9. * Lievre et al., 2008 * A. Lievre, D. Alley, E. Crimmins * Educational differentials in life expectancy with cognitive impairment among the elderly in the United States * Journal of Aging and Health, 20 (4) (2008), pp. 456–477 * 10. * Nielsen, 2009 * H.D. Nielsen * Moving toward free primary education: Policy issues and implementation challenges * UNICEF Social and Economic Policy Working Paper (2009) Retrieved from:http://www.unicef.org/socialpolicy/files/Postscript_Formatted_SFAI_SOA_Review_11_December_2009.pdf * 11. * Office of the High Commissioner for Human Rights, 1989 * Office of the High Commissioner for Human Rights. (1989). Convention on the rights of the child. Retrieved from:http://www2.ohchr.org/english/law/crc.htm#art32. * 12. * Oreopoulos, 2005 * P. Oreopoulos * Canadian compulsory school laws and their impact on educational attainment and future earnings * Statistics Canada, Ottawa (2005) * 13. * Oreopoulos, 2006 * P. Oreopoulos * The compelling effects of compulsory schooling: Evidence from Canada * Canadian Journal of Economics, 39 (1) (2006), pp. 22–52 * 14. * OECD, 2008 * Organisation for Economic Co-operation and Development (OECD) * Education at a glance 2008: OECD indicators * OECD, Paris (2008) * 15. * Patrinos and Psacharopoulos, 1995 * G. Patrinos, H.A. Psacharopoulos * Educational performance and child labor in Paraguay * International Journal of Educational Development, 15 (1) (1995), pp. 47–60 * 16. * Plan International, 2008 * Plan International * Paying the price: The economic cost of failing to educate girls * Plan International, Surrey (2008) * 17. * Roos et al., 1998 * E. Roos, E. Lahelma, M. Virtanen, R. Prättälä, P. 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(2011). Table 5: Enrolment ratios by ISCED level. Available at: http://stats.uis.unesco.org/unesco. Accessed 22.06.12. * 5. * World Bank, 2001 * World Bank. (2001). Brazil: Eradicating child labor (Report No. 21858-BR). Retrieved from:http://ddp-ext.worldbank.org/EdStats/BRAimp01.pdf. * 6. * World Bank, 2008a * Bank. World * GDP per capita PPP (constant 2005 international $) * World Development Indicators (2008) Retrieved from:http://data.worldbank.org/indicator/NY.GDP.PCAP.PP.KD * 7. * World Bank, 2008b * Bank. World * Urban population: % of total * World Development Indicators (2008) Retrieved from: http://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS * 8. * Zhang and Minxia, 2006 * T. Zhang, Z. Minxia * Universalizing nine-year compulsory education for poverty reduction in rural China * Review of Education, 52 (2006), pp. 261–285 *

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