This document analyzes data from Botswana's 2005/06 Labour Force Survey to understand the determinants of child labor and schooling in the country. The key findings are:
1) 21.2% of children worked while schooling, while 2.6% worked without schooling. Being from a female-headed household or having an older age decreased the likelihood of working while schooling.
2) Orphaned children were more likely to work, either with or without schooling, compared to children with one or two living parents.
3) Male children were more likely than females to work while schooling. Males also predominantly worked in agriculture, while females engaged more in unpaid family work and domestic
This study examines the causal effect of child labor on later socioeconomic outcomes using panel data from Vietnam. The authors find that children who worked as children are significantly less likely to be in school and have lower educational attainment five years later. However, these same children have a greater probability of wage employment and higher earnings as young adults. The authors estimate that the earnings gain from work experience exceeds the foregone earnings from reduced schooling, suggesting the net effect of child labor may be positive, at least until early adulthood. Over the longer run, the returns to education are found to increase more than the returns to child labor experience.
Child labor and schooling in Malawi: Does mother’s employment matter ? by Mic...IFPRIMaSSP
The study investigated the impact of mother’s employment on child labor and schooling in Malawi using the Third Integrated Household Survey (IHS3) dataset. Children aged 5 to 17 were sampled from the dataset and used in the analysis. The study employed the Multi-level trivariate probit model by considering the mothers equation as fixed effects model and the child-level equations as random effects probit models. The results showed that mother’s employment is negatively related to child labor but positively related to child schooling. Another finding was the negative relationship between child labor and child schooling. These results did not change when the model was disaggregated to compare the effects for a boy child and girl child. Based on the results, policy recommendations include promoting female employment programs by the government so that eventually, child labor may decline and schooling may be encouraged.
The document discusses poverty and child labor in rural areas of Pakistan. It finds that administrative flaws, lack of resources, and limited employment opportunities have led to widespread poverty. As rural families struggle to meet basic needs, many children are forced into child labor to help support their families financially. The study examines issues through interviews in the village of Bhadana Kalan, identifying factors such as large family sizes, lack of education, rising prices, and drug addiction as contributing to poverty and the need for children to work instead of attending school. It concludes that raising awareness of education's importance and strictly enforcing child labor laws could help address the problems.
This document summarizes a statistics presentation on the factors responsible for child labor. It finds that the major factors contributing to child labor are unemployment and lack of education among parents. Over 40% of child laborers in Pakistan work in manufacturing and children work primarily to support their families living in poverty. The study was conducted in Peshawar through questionnaires and interviews with 35 child laborers ages 6-15 working in shops, restaurants, and workshops. It recommends that the government and NGOs provide job opportunities and education programs to address unemployment, poverty, and illiteracy driving child labor.
This document presents a theoretical framework to analyze child labour using an inter-temporal approach. It summarizes an existing model of child labour and adapts it to a two-period framework. The model shows that child labour is inversely related to the real interest rate - as the interest rate rises, households are induced to reduce their children's participation in work. A rise in the interest rate could occur due to macroeconomic policies like increased government expenditure, which would create a favorable demand shock and raise output and interest rates, leading households to supply less child labor.
Renu Singh's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Socio economic problems of child labor in rajshahi city corporation of bangla...Alexander Decker
This document discusses socio-economic problems of child labor in Rajshahi City Corporation, Bangladesh. It notes that many families rely on children's income for survival, and employers prefer hiring children as they are cheaper. Child labor denies children their rights to education, leisure and exposes them to risks. The study interviewed 560 child laborers in Rajshahi and found long working hours and hazardous conditions negatively impact school attendance and child development. Poverty is a key driver of child labor in Bangladesh. The government has programs aiming to eliminate hazardous child labor and increase access to education, but enforcement remains a challenge.
This document discusses child labor in Aligarh City, India. It aims to understand the socioeconomic conditions of child laborers and their families. The survey found the highest proportions of child laborers were 12-14 years old, male, Muslim, and worked in dhabas/hotels, rag picking, and repair work. Most earned Rs. 2000-2500 monthly and worked 10-12 hours daily. The primary causes of child labor were identified as poverty, lack of education, and unemployment. Solutions proposed included increasing adult wages, equal pay for children, social welfare programs, housing assistance, and improving education access. Eliminating poverty and increasing public spending on the poor were seen as keys to reducing the challenge of child labor long
This study examines the causal effect of child labor on later socioeconomic outcomes using panel data from Vietnam. The authors find that children who worked as children are significantly less likely to be in school and have lower educational attainment five years later. However, these same children have a greater probability of wage employment and higher earnings as young adults. The authors estimate that the earnings gain from work experience exceeds the foregone earnings from reduced schooling, suggesting the net effect of child labor may be positive, at least until early adulthood. Over the longer run, the returns to education are found to increase more than the returns to child labor experience.
Child labor and schooling in Malawi: Does mother’s employment matter ? by Mic...IFPRIMaSSP
The study investigated the impact of mother’s employment on child labor and schooling in Malawi using the Third Integrated Household Survey (IHS3) dataset. Children aged 5 to 17 were sampled from the dataset and used in the analysis. The study employed the Multi-level trivariate probit model by considering the mothers equation as fixed effects model and the child-level equations as random effects probit models. The results showed that mother’s employment is negatively related to child labor but positively related to child schooling. Another finding was the negative relationship between child labor and child schooling. These results did not change when the model was disaggregated to compare the effects for a boy child and girl child. Based on the results, policy recommendations include promoting female employment programs by the government so that eventually, child labor may decline and schooling may be encouraged.
The document discusses poverty and child labor in rural areas of Pakistan. It finds that administrative flaws, lack of resources, and limited employment opportunities have led to widespread poverty. As rural families struggle to meet basic needs, many children are forced into child labor to help support their families financially. The study examines issues through interviews in the village of Bhadana Kalan, identifying factors such as large family sizes, lack of education, rising prices, and drug addiction as contributing to poverty and the need for children to work instead of attending school. It concludes that raising awareness of education's importance and strictly enforcing child labor laws could help address the problems.
This document summarizes a statistics presentation on the factors responsible for child labor. It finds that the major factors contributing to child labor are unemployment and lack of education among parents. Over 40% of child laborers in Pakistan work in manufacturing and children work primarily to support their families living in poverty. The study was conducted in Peshawar through questionnaires and interviews with 35 child laborers ages 6-15 working in shops, restaurants, and workshops. It recommends that the government and NGOs provide job opportunities and education programs to address unemployment, poverty, and illiteracy driving child labor.
This document presents a theoretical framework to analyze child labour using an inter-temporal approach. It summarizes an existing model of child labour and adapts it to a two-period framework. The model shows that child labour is inversely related to the real interest rate - as the interest rate rises, households are induced to reduce their children's participation in work. A rise in the interest rate could occur due to macroeconomic policies like increased government expenditure, which would create a favorable demand shock and raise output and interest rates, leading households to supply less child labor.
Renu Singh's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Socio economic problems of child labor in rajshahi city corporation of bangla...Alexander Decker
This document discusses socio-economic problems of child labor in Rajshahi City Corporation, Bangladesh. It notes that many families rely on children's income for survival, and employers prefer hiring children as they are cheaper. Child labor denies children their rights to education, leisure and exposes them to risks. The study interviewed 560 child laborers in Rajshahi and found long working hours and hazardous conditions negatively impact school attendance and child development. Poverty is a key driver of child labor in Bangladesh. The government has programs aiming to eliminate hazardous child labor and increase access to education, but enforcement remains a challenge.
This document discusses child labor in Aligarh City, India. It aims to understand the socioeconomic conditions of child laborers and their families. The survey found the highest proportions of child laborers were 12-14 years old, male, Muslim, and worked in dhabas/hotels, rag picking, and repair work. Most earned Rs. 2000-2500 monthly and worked 10-12 hours daily. The primary causes of child labor were identified as poverty, lack of education, and unemployment. Solutions proposed included increasing adult wages, equal pay for children, social welfare programs, housing assistance, and improving education access. Eliminating poverty and increasing public spending on the poor were seen as keys to reducing the challenge of child labor long
This last year, the extent of poverty and socio-economic crises in some African countries, particularly in Côte d’Ivoire have favoured child labour. Thus, despite the political fight against this phenomenon, it’s remains a concern. This research therefore aims to identify the determinants of child labour in Côte d’Ivoire, using 2005 data from the national survey on child labour with 5,571 children. The descriptive statistic showed that 1,509 (27.09%) were in child labour category: 743 boys (27.04%) and 766 girls (27.14%). The estimated multinomial logit presented that household poverty and low level of parent’s education remains a determinant of child labour. In addition, the permanent employment of the household in agriculture reduces child labour. Thus, policy makers can modernize agriculture. This strategy will allow the use of modern technology inaccessible to children and improve agricultural productivity. With a guaranteed minimum price for agricultural production poor households will earn higher incomes. In addition, targeted free schooling is required.
Child labor is a significant problem in Nepal, with 1.6 million children aged 5-17 estimated to be engaged in child labor. Agriculture is the largest employer of child laborers, with 95% working in that sector. Hazardous child labor affects over 600,000 children. Nepal has national plans to address child labor but enforcement remains a challenge. Interventions such as education, creating economic opportunities for families, and strengthening laws and inspections are needed to effectively tackle the problem of child labor in Nepal.
Leopoldo Laborda Castillo, Daniel Sotelsek Salem & Leopold Remi Sarr (2014)
The Effect of Poverty, Gender Exclusion, and Child Labor on Out-of-School Rates for Female Children,
Journal of Research in Childhood Education, 28:2, 162-181
Child labours still a hurdle in country developmentAlexander Decker
This document discusses child labor in District Bahawalpur, Pakistan. It aims to identify the nature and extent of child labor in the district, the causes of child labor, and recommend strategies to eradicate it. The study found that many children in rural areas work to contribute to family income, while urban families have children work due to large family size and lack of financial resources. Common causes of child labor included poverty, lack of access to education, and the demand for cheap labor. The document recommends identifying proposals from parents and children to help eradicate child labor in the district.
This document provides information about child labor in Pakistan. It discusses that according to UNICEF, there are approximately 158 million child laborers worldwide, and in Pakistan there are an estimated 3.8 million child laborers between the ages of 5-14. The main causes of child labor in Pakistan are poverty, large family sizes, illiteracy, unemployment, and failure to enforce laws prohibiting it. The document also outlines the effects of child labor, policy approaches to address it, Pakistan's efforts to reduce it through legislation, and recommendations such as increasing access to education and vocational training.
The document reports on a survey of child education and labour in the Ragiguda slum in Bangalore, India. Key findings include:
1) Over half of children aged 6-14 do not attend school, with poverty being a major barrier. Many children must work to support their families.
2) While most parents want their children to be educated to have better lives, some girls only attend school until a certain age.
3) Around 24% of children under 14 work, mainly in households or other informal jobs like cleaning. Poverty is reported as the main reason for child labor.
4) Education is seen as important for obtaining good jobs and becoming financially independent, though many adult residents lack
Dr Ellina Samantroy's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Child labor in pakistan by Farhan Ali RanaFarhan Ali
This document discusses child labor in Pakistan based on a survey from 1996. Some key points:
- The survey found 3.3 million children, or 7% of the workforce, were fully employed. Most were boys in Punjab.
- Main causes of child labor included poverty, lack of education, addicted fathers, working mothers, and the father's profession.
- Children worked in various industries like carpets, workshops, shops, and home services. Many faced hazardous conditions.
- The carpet industry exploited many children through debt bondage systems where they earned half the adult wage.
An additional year of schooling is associated with a 0.107 higher probability of not having a chronic illness for adults in Mongolia. For males it's 0.114 and for females it's 0.100. A mother's additional year of schooling increases the probability her child does not have health complaints by 0.031. However, a father's schooling has no impact on a child's health. While education is linked to better health outcomes, the causal mechanisms are still being investigated.
This working paper examines the impact of early childbearing on education, literacy, and labor market outcomes in four African countries using Demographic and Health Survey data. The authors identify three potential sources of endogeneity in estimating this relationship: unobserved individual motivation and aspirations, shorter decision horizons and risk-taking behaviors among teenagers, and inaccurate reporting due to social stigma. To address these issues, the authors employ an identification strategy that uses a woman's age at menarche to identify the causal effect of teenage motherhood, comparing outcomes for women who had children as teenagers versus later in life.
Zulfiqar Ali's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
a study on cause of primary school dropouts by Peer zada Aneespeer zada Anees
This document discusses a study on the causes of primary school dropouts in Karnataka, India. It provides background on efforts to expand primary education access over the past few decades but notes that dropout rates remain high. The study found that the highest dropout rates in Karnataka are in Gulbarga district, followed by Belgaum. Migration is a major reason for children dropping out. Girls have higher dropout rates than boys. The document also reviews national trends, finding that over 40% of students drop out between classes 1-5, with economic factors and lack of interest being top reasons.
New Microsoft Office PowerPoint Presentation (3)swadha rath
- The document provides statistics and analysis on child labor in Odisha, India from various surveys conducted between 1997-2012. It finds that the number of male child laborers consistently exceeds the number of females. The largest numbers are engaged in hazardous occupations like agriculture, bidi rolling, and food stalls.
- National and state-level programs aim to rehabilitate child laborers through special schools that provide education and vocational training. Over 100,000 children have been removed from labor and reintegrated into formal schooling through these efforts.
- While the number of child laborers is decreasing overall, continued efforts are needed to address the root causes of poverty, lack of access to education, social attitudes, and weak law
This document summarizes an analysis of factors influencing educational attainment in Uganda using data from the 2005/06 Uganda National Household Survey. The analysis develops three regression models to examine the relationship between socioeconomic factors and educational attainment. The basic model relates years of schooling to variables like parents' education, employment hours, household duties, poverty, and pregnancy. For current students, an augmented model adds variables like school costs and distance. For non-students, reasons for non-attendance like distance and school quality are examined. The analysis finds parents' education, poverty, and urban/rural residence most strongly correlate with attainment, while distance effects are inconclusive due to data limitations. Distance and school quality appear to deter non
The role of maternal education in child health - evidence from China.pdfHanaTiti
The document discusses the role of maternal education in child health in China, noting that maternal education has been shown to positively impact child health outcomes. It aims to investigate the influence of mothers' education on the health status of children in China using data from the China Family Panel Studies. The results indicate that maternal education has a significant effect on child health, while household wealth, gender, and living area also influence child health to a lesser degree.
A Sociological Study Of Patterns And Determinants Of Child Labour In IndiaNat Rice
This study examines patterns and determinants of child labor in India using census and survey data. The findings suggest that poverty alone does not determine child labor - gender and caste are also significant factors. Children from lower castes and girls engaged in household activities are more likely to be involved in child labor compared to boys engaged in paid work. While poverty plays a role, factors like gender inequality, caste discrimination, lack of access to education, and social norms also contribute to the high rates of child labor in India. The study aims to provide a more nuanced understanding of the complex issue of child labor beyond simplistic explanations.
This document summarizes a research paper that investigates the effect of increased availability of public pre-kindergarten programs on maternal labor supply in the United States. Using data from 13 states where school districts are organized at the county level, the author employs a differences-in-differences model to compare changes in labor force participation and employment of mothers with four-year-olds in counties with growing pre-K availability over time, relative to counties without increased availability. The results suggest that greater access to public pre-K is associated with statistically significant increases in labor supply for mothers of four-year-olds, both with and without younger children. Specifically, full implementation of pre-K is estimated to increase labor force participation by
This study examines the determinants of child labour in Khyber Pakhtunkhwa, Pakistan through an econometric analysis. Data was collected through surveys of 100 households, with 50 households having children in school and 50 having children working. The results of the econometric model show that the head of household's education and average household income are negatively correlated with child labour, while the age of the child and family size are positively correlated but insignificantly. The study concludes that increasing parental education is necessary to better the future of children, and recommends the government provide more education facilities and skill development centers to reduce child labour.
The document discusses the important role that parents play in a child's educational success. It states that investing time, money, and effort into a child's education can have lasting benefits for the child and society. When parents are involved in a child's education by helping with homework, communicating with teachers, having high expectations, and creating a home environment that supports learning, children tend to have higher test scores and grades, better school attendance, and are more likely to complete high school and pursue further education. The document emphasizes that developing a partnership between parents and teachers is key to promoting students' academic and social development.
This last year, the extent of poverty and socio-economic crises in some African countries, particularly in Côte d’Ivoire have favoured child labour. Thus, despite the political fight against this phenomenon, it’s remains a concern. This research therefore aims to identify the determinants of child labour in Côte d’Ivoire, using 2005 data from the national survey on child labour with 5,571 children. The descriptive statistic showed that 1,509 (27.09%) were in child labour category: 743 boys (27.04%) and 766 girls (27.14%). The estimated multinomial logit presented that household poverty and low level of parent’s education remains a determinant of child labour. In addition, the permanent employment of the household in agriculture reduces child labour. Thus, policy makers can modernize agriculture. This strategy will allow the use of modern technology inaccessible to children and improve agricultural productivity. With a guaranteed minimum price for agricultural production poor households will earn higher incomes. In addition, targeted free schooling is required.
Child labor is a significant problem in Nepal, with 1.6 million children aged 5-17 estimated to be engaged in child labor. Agriculture is the largest employer of child laborers, with 95% working in that sector. Hazardous child labor affects over 600,000 children. Nepal has national plans to address child labor but enforcement remains a challenge. Interventions such as education, creating economic opportunities for families, and strengthening laws and inspections are needed to effectively tackle the problem of child labor in Nepal.
Leopoldo Laborda Castillo, Daniel Sotelsek Salem & Leopold Remi Sarr (2014)
The Effect of Poverty, Gender Exclusion, and Child Labor on Out-of-School Rates for Female Children,
Journal of Research in Childhood Education, 28:2, 162-181
Child labours still a hurdle in country developmentAlexander Decker
This document discusses child labor in District Bahawalpur, Pakistan. It aims to identify the nature and extent of child labor in the district, the causes of child labor, and recommend strategies to eradicate it. The study found that many children in rural areas work to contribute to family income, while urban families have children work due to large family size and lack of financial resources. Common causes of child labor included poverty, lack of access to education, and the demand for cheap labor. The document recommends identifying proposals from parents and children to help eradicate child labor in the district.
This document provides information about child labor in Pakistan. It discusses that according to UNICEF, there are approximately 158 million child laborers worldwide, and in Pakistan there are an estimated 3.8 million child laborers between the ages of 5-14. The main causes of child labor in Pakistan are poverty, large family sizes, illiteracy, unemployment, and failure to enforce laws prohibiting it. The document also outlines the effects of child labor, policy approaches to address it, Pakistan's efforts to reduce it through legislation, and recommendations such as increasing access to education and vocational training.
The document reports on a survey of child education and labour in the Ragiguda slum in Bangalore, India. Key findings include:
1) Over half of children aged 6-14 do not attend school, with poverty being a major barrier. Many children must work to support their families.
2) While most parents want their children to be educated to have better lives, some girls only attend school until a certain age.
3) Around 24% of children under 14 work, mainly in households or other informal jobs like cleaning. Poverty is reported as the main reason for child labor.
4) Education is seen as important for obtaining good jobs and becoming financially independent, though many adult residents lack
Dr Ellina Samantroy's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
Child labor in pakistan by Farhan Ali RanaFarhan Ali
This document discusses child labor in Pakistan based on a survey from 1996. Some key points:
- The survey found 3.3 million children, or 7% of the workforce, were fully employed. Most were boys in Punjab.
- Main causes of child labor included poverty, lack of education, addicted fathers, working mothers, and the father's profession.
- Children worked in various industries like carpets, workshops, shops, and home services. Many faced hazardous conditions.
- The carpet industry exploited many children through debt bondage systems where they earned half the adult wage.
An additional year of schooling is associated with a 0.107 higher probability of not having a chronic illness for adults in Mongolia. For males it's 0.114 and for females it's 0.100. A mother's additional year of schooling increases the probability her child does not have health complaints by 0.031. However, a father's schooling has no impact on a child's health. While education is linked to better health outcomes, the causal mechanisms are still being investigated.
This working paper examines the impact of early childbearing on education, literacy, and labor market outcomes in four African countries using Demographic and Health Survey data. The authors identify three potential sources of endogeneity in estimating this relationship: unobserved individual motivation and aspirations, shorter decision horizons and risk-taking behaviors among teenagers, and inaccurate reporting due to social stigma. To address these issues, the authors employ an identification strategy that uses a woman's age at menarche to identify the causal effect of teenage motherhood, comparing outcomes for women who had children as teenagers versus later in life.
Zulfiqar Ali's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.
a study on cause of primary school dropouts by Peer zada Aneespeer zada Anees
This document discusses a study on the causes of primary school dropouts in Karnataka, India. It provides background on efforts to expand primary education access over the past few decades but notes that dropout rates remain high. The study found that the highest dropout rates in Karnataka are in Gulbarga district, followed by Belgaum. Migration is a major reason for children dropping out. Girls have higher dropout rates than boys. The document also reviews national trends, finding that over 40% of students drop out between classes 1-5, with economic factors and lack of interest being top reasons.
New Microsoft Office PowerPoint Presentation (3)swadha rath
- The document provides statistics and analysis on child labor in Odisha, India from various surveys conducted between 1997-2012. It finds that the number of male child laborers consistently exceeds the number of females. The largest numbers are engaged in hazardous occupations like agriculture, bidi rolling, and food stalls.
- National and state-level programs aim to rehabilitate child laborers through special schools that provide education and vocational training. Over 100,000 children have been removed from labor and reintegrated into formal schooling through these efforts.
- While the number of child laborers is decreasing overall, continued efforts are needed to address the root causes of poverty, lack of access to education, social attitudes, and weak law
This document summarizes an analysis of factors influencing educational attainment in Uganda using data from the 2005/06 Uganda National Household Survey. The analysis develops three regression models to examine the relationship between socioeconomic factors and educational attainment. The basic model relates years of schooling to variables like parents' education, employment hours, household duties, poverty, and pregnancy. For current students, an augmented model adds variables like school costs and distance. For non-students, reasons for non-attendance like distance and school quality are examined. The analysis finds parents' education, poverty, and urban/rural residence most strongly correlate with attainment, while distance effects are inconclusive due to data limitations. Distance and school quality appear to deter non
The role of maternal education in child health - evidence from China.pdfHanaTiti
The document discusses the role of maternal education in child health in China, noting that maternal education has been shown to positively impact child health outcomes. It aims to investigate the influence of mothers' education on the health status of children in China using data from the China Family Panel Studies. The results indicate that maternal education has a significant effect on child health, while household wealth, gender, and living area also influence child health to a lesser degree.
A Sociological Study Of Patterns And Determinants Of Child Labour In IndiaNat Rice
This study examines patterns and determinants of child labor in India using census and survey data. The findings suggest that poverty alone does not determine child labor - gender and caste are also significant factors. Children from lower castes and girls engaged in household activities are more likely to be involved in child labor compared to boys engaged in paid work. While poverty plays a role, factors like gender inequality, caste discrimination, lack of access to education, and social norms also contribute to the high rates of child labor in India. The study aims to provide a more nuanced understanding of the complex issue of child labor beyond simplistic explanations.
This document summarizes a research paper that investigates the effect of increased availability of public pre-kindergarten programs on maternal labor supply in the United States. Using data from 13 states where school districts are organized at the county level, the author employs a differences-in-differences model to compare changes in labor force participation and employment of mothers with four-year-olds in counties with growing pre-K availability over time, relative to counties without increased availability. The results suggest that greater access to public pre-K is associated with statistically significant increases in labor supply for mothers of four-year-olds, both with and without younger children. Specifically, full implementation of pre-K is estimated to increase labor force participation by
This study examines the determinants of child labour in Khyber Pakhtunkhwa, Pakistan through an econometric analysis. Data was collected through surveys of 100 households, with 50 households having children in school and 50 having children working. The results of the econometric model show that the head of household's education and average household income are negatively correlated with child labour, while the age of the child and family size are positively correlated but insignificantly. The study concludes that increasing parental education is necessary to better the future of children, and recommends the government provide more education facilities and skill development centers to reduce child labour.
The document discusses the important role that parents play in a child's educational success. It states that investing time, money, and effort into a child's education can have lasting benefits for the child and society. When parents are involved in a child's education by helping with homework, communicating with teachers, having high expectations, and creating a home environment that supports learning, children tend to have higher test scores and grades, better school attendance, and are more likely to complete high school and pursue further education. The document emphasizes that developing a partnership between parents and teachers is key to promoting students' academic and social development.
This document summarizes the key points from a meeting at Moonlight High School on their mission, vision, guiding principles and current status. It discusses that the school's mission is to ensure rigorous learning for all students through engaging instruction and community collaboration focused on student success. The vision is to produce globally competitive learners ready for college and careers. Current status is positive with increased enrollment and quality education, but infrastructure and academic programs could be improved, as well as strengthening communication between school and parents.
The document discusses a study that aimed to establish the extent to which subject mastery enhances quality teaching for student-teachers during teaching practice. The study found that:
1) Subject mastery allows student-teachers to effectively arrange teaching materials and develop ideas to enrich their content knowledge.
2) Both student-teachers and supervising teachers agreed some students faced difficulties mastering content, hindering quality teaching and curriculum delivery.
3) Improving conditions like classroom size and learning materials could help create an environment more conducive to teaching quality.
This study examines the relationship between teacher-related factors and students' attitudes towards chemistry in secondary schools in Bureti District, Kenya. The study found that teachers' use of teaching methods, availability to students, use of resources, content knowledge, and ability to address negative student attitudes can influence how students view chemistry. It was recommended that teachers encourage positive self-concepts in students, provide guidance and counseling, and ensure equal participation of girls in chemistry. The findings could benefit curriculum developers and chemistry teachers in improving instruction.
This document summarizes a dissertation defense from June 2022 on a study of teachers' perceptions of factors affecting their effectiveness in private primary schools in Kolfe Kernio Sub-City Worda 01, Ethiopia. The study used a qualitative phenomenological design to investigate teachers' experiences. A total of 126 teachers and 7 principals participated. Data was collected through questionnaires, interviews, and analyzed using the Stevick-Colazzi-Keen method. The study aimed to identify teachers' perceptions of teacher-related, school-related, and parent-related factors influencing their effectiveness.
This study analyzed teachers' responses to statements about factors influencing their effectiveness. The findings show that teacher-related factors like school support, recognition, salary, subject knowledge, teaching skills, and interest in teaching influence effectiveness. A positive correlation was found between teacher effectiveness and teacher-related factors, school-related factors, and parent-related factors. The regression model showed that teacher factors had the strongest influence on teacher effectiveness. In conclusion, addressing factors like working conditions, school support, salary, and workload can improve teacher effectiveness.
The document summarizes a baseline study conducted in Uganda that examined factors influencing effectiveness in primary schools. The study assessed conditions in schools, classroom interactions, teacher motivation levels, community involvement, pupil achievement, and made recommendations. Data was collected through school profiles, observations, interviews, and tests in literacy and numeracy. The results provided information on the status of key factors for policymakers to guide educational reforms in Uganda.
This study examined teachers' perceptions of factors affecting their effectiveness in private primary schools in Kolfe Keranio Sub-City, Addis Ababa. Data was collected through questionnaires administered to 126 teachers and interviews with 7 principals. The factors analyzed included teacher-related factors like recognition and salary, school-related factors like facilities and leadership, and parent-related factors like cooperation. Results showed that teachers felt recognition, adequate training, and salary influenced their effectiveness, while principals said support, workload, and working conditions also impacted it. The study concluded that addressing these factors through a supportive environment could improve teacher effectiveness and retention.
This dissertation examines teachers' perceptions of factors affecting their effectiveness in private primary schools in Kolfe Keranio Sub-City Worda 01, Addis Ababa, Ethiopia. The study used a qualitative phenomenological design and surveyed 126 teachers using questionnaires and interviewed 7 school principals. Key findings were that teacher-related factors like recognition, salary, subject knowledge and teaching skills influenced effectiveness, as did school-related factors such as facilities, class size, and instructional leadership. The dissertation analyzed these factors and their relationship to teacher effectiveness.
Conley Elementary has a mission to provide a safe, positive learning environment that maximizes student potential and prepares them to be critical thinkers. The school's goals include increasing passing rates on state assessments to 90% with 50% commended performance, reducing achievement gaps between student groups, integrating more technology, increasing attendance to 98%, decreasing office visits, and promoting community involvement. Beliefs include a safe environment, parental involvement, all students achieving at high levels, accountability, achieving district goals, valuing staff, and personal/professional development. The student body is diverse with over 80% economically disadvantaged, 42.8% African American and 52.1% Hispanic. Special programs include dyslexia and special education services in all classrooms
This document discusses the causes of child labour in India. It identifies several root causes including poverty, large family size, gender biases, low levels of education, caste discrimination, and indebtedness. Poverty is identified as a major driving factor, as it forces children into the workforce to supplement family income. Cultural factors also play a role, as girls often have greater domestic responsibilities and less access to education than boys. Weak public education systems, low literacy rates, and a lack of access to schools in some areas also contribute to the problem by depriving children of educational opportunities.
The document provides an overview and theoretical background of the Academic Phrasebank resource. It describes the resource as a compilation of commonly used phrasal elements in academic English organized according to the main sections of a research paper. The phrases are derived from authentic academic sources and are intended to help academic writers, particularly non-native English speakers, with organizing their writing and incorporating appropriate phrasing. Guidelines are provided on when it is acceptable to reuse phrases from the resource in one's own academic writing.
This document provides a literature review on the history and current state of child labor. It discusses how child labor has historically existed since pre-industrial times but increased substantially during the Industrial Revolution. While developed nations have largely eliminated child labor through economic growth and legislation, it remains a significant problem in developing countries, with ILO estimates of 168 million child laborers globally as of 2012. The literature review covers debates around factors that reduced child labor in developed nations and challenges around measuring the true scope of the problem.
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1. Okurut, F.N. & D.O. Yinusa 15
Determinants of Child Labour and Schooling in
Botswana: Evidence from 2005/2006 Labour Force
Survey
Okurut, F.N. & D.O. Yinusa1
Abstract
The rise in child labour and the negative effect of it on child schooling outcomes is an
important policy issue in developing countries. However, despite almost universal
agreementthatchildlabourisundesirable,thereiswidedisagreementonhowtotackle
the problem. The formulation of policies that are effective in curbing child labour
requires a clear understanding of the key determinants of child employment. This
article contributes to the debate by providing an analysis of the key determinants of
child labour and schooling in an upper middle-income country, Botswana. The study
used the Labour Force Survey (LFS) 2005/06 data from the Central Statistics Office
(CSO) and the multinomial logit model for analytical work. The results suggest that
the probability of children working while schooling is negatively and significantly
influenced by the age of the child, being from a female headed household and
employment status of the household head. However the probability of child labour
and schooling is positively and significantly influenced by child education level, the
number of children in the household, and the household head being engaged mainly
in the agricultural sector.
Key Words: Child Labour, Multinomial Logit Model, Botswana,
JEL: J2, C25, C3
1. Introduction
Theliteratureisrepletewithstudiesonchildlabour.Thegrowinginterestofeconomists
in child labour stems from the rise in child labour in developing countries which
was perceived to have negative consequences on school enrolments and educational
outcomes with serious effects on child health, human capital development and
welfare. Therefore, child labour has become one of the most important policy issues
in the agenda of most countries. More importantly, the demographic and socio-
economic factors causing a child to be engaged in the labour market vary across
countries and continents. For example, the evidence presented in Ray (2000a) shows
that the nature of child labour, its key determinants and, consequently, the strategies
at reducing it, vary between countries. Bonnet (1993) argues that in the African
context the poor quality of child schooling and their lack of apparent relevance to
1.
Both authors are based in the Department of Economics, University of Botswana. Emails: oku-
rutf@mopipi.ub.bw and yinusado@mopipi.ub.bw
2. BOJE: Botswana Journal of Economics
16
the child’s employment skills encourage parents to take their children out of schools
and put them into employment.
However, despite almost universal agreement that child labour is undesirable,
there is wide disagreement on how to tackle the problem. Therefore, the formulation
of policies that are effective in curbing child labour requires an analysis of its key
determinants as this study intends to do. It is important to study determinants of
child labour because: child labour encourages children to drop out of school; it
undermines human capital development and future earnings; reinforces the vicious
cycle of poverty, and runs counter to Botswana Vision 2016 of being “An educated
nation”. The Botswana Employment Act stipulates that no child less than 15 years
shall be employed in any capacity whatsoever. But, a child aged 14 years and not
attending school may be employed on light work not harmful to his/her health or
development (CSO, 2007).
On the policy side, it will be necessary to understand individual and household
characteristics of children involved in child labour. What sectors are the children
mainly involved in child labour? Are the children concurrently working as well as
schooling? What factors motivate children to engage in labour markets given the free
universal education in Botswana? What policy measures should be put in place to
address the problem of child labour as a strategy for poverty alleviation? What does
the Labour Force Survey data 2005/06 tell us about child labour in Botswana? These
issues are investigated in this study using descriptive statistics and a multinomial
logit model.
2. Employment Status of Children in Botswana
The analysis focussed on children of school going age (aged between 7 and 17)
using weighted data with approximately 415,751 children. The children were
decomposed into four employment and schooling states: 1 = working and schooling;
2 = working and not schooling; 3 = not working and schooling; 4 = not working
and not schooling. Of the 415,751 children captured in 2005/06 LFS, 72.4 percent
were involved in schooling only, 21.2 percent were involved in labour market
activities as well as schooling, 2.6 percent were involved in working only, while
4 percent were not working and not schooling. Given Botswana’s vision 2016 of
getting an educated and well informed population, the ideal scenario would be for
all children to be in school without engagement in labour market activities given
the free education policy and the welfare grants system for the poor households.
This therefore motivated the analysis of the socio-economic characteristics of the
chilldren in the various employment and schooling states with a view of getting a
better understanding of the factors that influence child employment and schooling
behaviour. In effect policy concerns are on the approximately 28 percent of all the
children in the three employment and schooling states (i.e. working and schooling;
working and not schooling; not working and not schooling).
3. 17
Table 1: Child Employment and Schooling Status
Child employment and schooling status Frequency Percent
Working and schooling 88,120 21.2
Working and not schooling 10,877 2.6
Not working and schooling 300,135 72.4
Not working and not schooling 16,620 4.0
Total 415,751 100.2
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
Of the 415,751 children, 59 percent were from female headed households, while 41
percent were from male headed households. Within the children from male headed
households, 69.4 percent were involved in schooling only, 22.9 percent were working
and schooling, 3.2 percent were working and not schooling, and 4.5 percent were not
working and not schooling. Within the female headed households, 74.1 percent of the
children were engaged in schooling only, 20 percent were schooling and working,
2.2 percent were working and not schooling, and 3.6 percent were not working and
not schooling. The results suggest that the children from female headed households
are more likely to be engaged in schooling only as compared to children from male
headed households. By implication children from male headed households have a
higher probability of engagement in labour market activities.
Table 2: Child Employment and Schooling Status by Gender of Household Head
Gender of Household Head
Child employment and schooling
status
Male
(N=168,764)
Female
(N=246,987)
Total
(N=415,751)
Working and schooling 22.9 20.0 21.2
Working and not schooling 3.2 2.2 2.6
Not working and schooling 69.4 74.1 72.0
Not working and not schooling 4.5 3.6 4.0
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
The orphan status of the children was generated as a categorical variable: 1 = both
parents alive; 2= only one parent alive; 3 = both parents dead. Of the 415,043
children on whom the parents’ living status was given, 69 percent had both parents
alive, 25 percent had only one parent alive; and 6 percent were complete orphans.
The orphaned children were least likely to be engaged in full time schooling (63.6
percent) as compared to children with single parents (71.3 percent) and children with
both parents alive (73.3 percent). By contrast orphaned children are more likely to
Okurut, F.N. & D.O. Yinusa
4. BOJE: Botswana Journal of Economics
18
be working and schooling (25.3 percent) as compared to children with both parents
alive (20.6 percent) or children with a single parent alive (22 percent). The orphaned
children were also more likely to be working and not schooling, not working and
not schooling as compared to children with either both or one parent alive. It can be
concluded that orphan hood increases the likelihood of children being engaged in
labour market activities. But given the fact that social welfare grants are provided
by the state to orphans to enable them to cope and continue to be in school, this
may imply that the social welfare grants for the orphans do not reach the intended
beneficiaries. This calls for the streamlining of the social welfare grants system to
ensure that the orphans as the intended beneficiaries receive them.
Table 3: Child Employment and Schooling Status by Child
Orphan Status
Child employment and
schooling status
Both Parents
Alive
(N=284,647)
Single Parent
(N=104,901)
Orphan
(N=25,495)
Total
(N=415,043)
Working and schooling 20.6 22.0 25.3 21.2
Working and not
schooling
2.4 2.7 4.6 2.6
Not working and
schooling
73.3 71.3 63.6 72.0
Not working and not
schooling
3.7 4.1 6.5 4.0
Total 100.0 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
There were an approximate equal proportion of female and male children captured
by the survey. The female children were more likely to be engaged in schooling only
(75.1 percent) as compared to male children (69.2 percent), which may partly be
explained by the traditional practices of engaging children in cattle posts. The male
children were more likely to be working and schooling (24.1 percent) as compared
to female children (18.3 percent).
Table 4: Child Employment and Schooling Status by Gender of Child
Child employment and
schooling status
Gender of Child
Male
(N=207,713)
Female
(208,038)
Total
(N= 415,751)
Working and schooling 24.1 18.3 21.2
Working and not schooling 3.5 1.8 2.6
Not working and schooling 69.2 75.1 72.0
Not working and not schooling 3.2 4.8 4.0
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
5. 19
Of the 70,819 children for which the specific sector in which they were employed
was specified, 67.6 percent were working on own family lands/cattle post/farm, 12.4
percent were engaged in unpaid work in a family business, 9 percent were engaged in
self employment, and 6.5 percent were employed by private households. The gender
analysis of the children by the sector of employment suggests that male children
are more likely to be engaged in working on family land/cattle posts/farms (71.6
percent) as compared to female children (61.6 percent). However female children
are more likely to be engaged in private sector employment, unpaid work in a family
business, and employment in private households than male children.
Table 5: Sector of Employment by Gender of Children
Sector Gender of Children
Total
(N=70,819)
Male
(N=42,050)
Female (N=28,769)
Working on own family lands/
cattle post or farm
71.6 61.6 67.6
Central government 0.1 0.3 0.2
Local government 0.3 0.8 0.5
Parastatal 0.1 0.0 0.1
Private sector 2.7 4.3 3.3
Non-government organization 0.0 0.1 0.1
Private household 6.3 6.8 6.5
Business with employees 0.4 0.4 0.4
Business without employees 8.3 10.0 9.0
Unpaid work in a family
business
10.2 15.6 12.4
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
The children are engaged in labour market activities mainly in form of seasonal
employment (39.5 percent), followed by temporary employment (28.7 percent),
casual employment (15.5 percent) and permanent employment (10 percent).
Table 6: Term of Employment by Gender of Children
Term of Employment Gender of Children
Total
(N=70,753)
Male
(N=42,050)
Female (N=28,703)
Permanent 11.1 8.5 10.0
A fixed period contract 0.4 0.7 0.5
Casual 17.7 12.3 15.5
Okurut, F.N. & D.O. Yinusa
6. BOJE: Botswana Journal of Economics
20
Seasonal 34.3 47.1 39.5
Temporary 30.4 26.1 28.7
Don’t know 5.9 5.3 5.6
Other 0.2 0.0 0.1
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
Only 39,170 children stated the main reason for their engagement in labour market
activities. The three main reasons for children to engage in labour market activities
include duty to help family (62.8 percent), to obtain money for own use (12.8 percent),
and to assist the family with money (11.9 percent). The gender decomposition
suggests that female children are more likely to engage in labour market activities
to obtain money to assist the family and also money for personal use as compared to
male children. However the male children are more likely to engage in labour market
activities as a duty to help the family with farming activities as compared to female
children.
Table 7: Main Reasons Children Working
Reason Gender of Children
Total
(N=39,170)
Male
(N=29,972)
Female (15,198)
Assist family with money 10.1 14.6 11.9
To obtain money for own use 12.1 14.0 12.8
Duty to help family e.g. with
farming
67.0 56.1 62.8
Obligation to landlord 0.2 0.0 0.1
Finished school and no other
activity available
0.7 1.7 1.1
School class not operating/
teacher missing
1.4 2.9 2.0
To gain experience/training 1.6 0.0 1.0
Other 0.2 0.4 0.2
Not stated 6.8 10.3 8.1
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
Almost 79.4 percent of all the children engaged in labour market activities are
not given any cash earnings, which is indicative of high unpaid labour among the
children. Approximately 6.7 percent of the children have part of their earnings from
labour market activities paid to parents/adults in the family. This scenario may arise
where the child is employed for example by a private household as a housemaid
7. 21
and the money paid directly to parents/adults in the family, which is indicative of
the exploitation of children. Only 13.5 percent of the children receive their earnings
from labour market activities themselves. The gender decomposition suggests that
both female and male children are equally likely to have part of their earnings paid
to parents/adults in the family. The male children are also more likely not to receive
cash earning for their labour (80.4 percent) as compared to female children (77.9
percent).
Table 8: Earnings from Child Labour Paid to Parent/Adults in Family
Earnings Paid to Parents/
Adults in Family
Gender of Children
Total
(N=39,277)
Male
(N=21,718)
Female (N=13,559)
Yes, all or almost all 2.2 2.1 2.2
Yes, half or more 2.1 2.7 2.3
Yes, less than half 2.2 2.2 2.2
No 13.1 14.2 13.5
No cash earnings 80.4 77.9 79.4
Other 0.0 0.9 0.4
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
While approximately 71.8 percent of the children who are schooling engage in
labour market activities on weekends/holidays which may be argued to be good for
the development of children into responsible citizens, concern is on the rest of the
children who engage in labour market activities daily (or sometimes) before or after
school. By implication such children will not have time to concentrate on their studies
which will have negative effects on their school performance and human capital
development, thereby having adverse effects on their future earnings potential. The
gender decomposition of the children by the time they engage in labour market
activities suggests that the females are more likely to engage daily (or sometimes)
before and after school as compared to male children. The male children are however
more likely to be engaged in labour market activities on weekends/holidays than the
female children. The burden of daily labour market activities therefore falls more
disproportionately on female children.
Table 9: Time when Children who are Schooling and Working Engage in Labor
Market Activities
Time of Engagement in
Labour Market
Male
(N=18,073)
Female
(N=11,939)
Total (N=30,012)
Daily before school/
college
1.5 4.4 2.7
Okurut, F.N. & D.O. Yinusa
8. BOJE: Botswana Journal of Economics
22
Daily after school/college 15.8 18.1 16.7
Daily both before/after
school/college
2.3 3.4 2.7
Weekends/holidays 74.9 67.0 71.8
During school time 1.1 0.0 0.6
Sometimes before/after
school/college
2.5 4.2 3.2
Sometimes both before/
after school/college
1.9 2.9 2.3
Total 100.0 100.0 100.0
Source: Authors’ calculations based on CSO Labour Force Survey (2005/06)
3. Literature Review on Child Labour and Schooling
Studies on the issue of child labour in developing countries have taken two main
dimensions in the literature: those that examine the determinants of work and those
that investigate the consequences of work. The first line of research has led to the
series of both theoretical and empirical research modelling the determinants of child
labour (Brown, Deardorff and Stern, 2002) while the later has dominated much of the
policy debate about stopping child labour (ILO, 2006). Yet distinguishing between
competing theories of the determinants of child labour with empirical studies has
been very challenging. Although, there seem to be some emerging consensus at
the empirical level that lack of access to utilities, return to schooling, school cost,
cultural traditions and local institutions, the family marginal utility of income, level
of education of household head, gender of household head and credit market failure
are key determinants of child labour in developing countries, yet, these determinants
of child labour and many more tend to vary across countries and across regions
(Austen, 2005).
For example, Bonnet (1993) argues in the African context that poor quality of
child schooling and their lack of apparent relevance to the child’s employment skills
encourage parents to take their children out of schools and put them into employment.
The evidence presented in Ray (2000) shows that the nature of child labour, its key
determinants and, consequently, the strategies at reducing it, vary between countries.
Child labour takes different form in different regions. Also, Bhalotra and Heady
(2001) investigated the determinants of child labour in rural household from Ghana
and Pakistan and concluded that, in addition to the number of siblings, factors such
as age, mother’s education, region, ethnic, religion, availability of public transports
and electricity are variables that show some importance to define the number of
hours that children work.
Bock (2002) investigated school attendance and child labour among the
9. 23
Okavango Delta Peoples of Botswana. The study used predictions regarding parental
investment in the embodied capital of offspring generated by evolutionary theory to
examine the pattern of children’s time allocation to labour and schooling. Models
incorporating individual costs and benefits of resource allocation, conflicts of
interests between men and women and between parents and offspring, and the effects
of family composition, subsistence ecology, and gender were developed and applied
to data on time allocation, household demography, and household economy. The
main findings from the study are: (1) The availability of alternative productive tasks
strongly affects intra- and intergenerational labour substitution. (2) The presence of
similarly aged children of the same sex within the household decreases the likelihood
of both boys and girls engaging in a specific productive activity and increases the
likelihood of children’s school attendance. (3) Birth order, the labour needs of the
household, and parents’ marital status all affect school attendance.
UNICEF (2007) investigated the determinants of child labour and school
enrollment using data from 175 countries. The research questions were designed
around three main issues: which factors influence family’s decision to subject the
child to work? Which factors contribute significantly to child not attending school
as a result of its occupation? And what policy options are available for Governments
to intervene in this issue? It was argued that poverty, inequality, access to education,
culture, parents’ education, vulnerability, economic crises, resultant market-oriented
adjustment and transition policies tend to exacerbate inequality, often increasing the
supply of and demand for children’s labour. At the same time, trade liberalization
and the increasing internalization of production have created new markets for
unskilled, cheap labour, often including that of children. “Economic inequalities,
and unregulated rapid growth of market economies, have contributed to child labour
by increasing the vulnerability of poor households on the one hand and reducing
the resources available for state educational and welfare provision on the other.”
(UNICEF, 2007:5). In such contexts, sometimes children’s work makes a critical
contribution to household income and food security, and may thus become more
attractive an option for children and parents than under-funded, low quality education
(de Carvalho Filho, 2008).
Zylberstajn, Pagotto and Pastore (1985) conducted a study in Brazil to show
factors that drive children, teenagers, and women into the labour market. The authors
found that the poorest families use the work of children and teenagers in order to
survive, mainly because of three reasons: father’s handicap, age and health of the
son. When they did this study, there were “...27% of families where the head of
the household did not work due to sickness or job accident, living in total or partial
handicapped conditions. In this group of families, there are 37% whose income
is exclusively formed by the precarious work of minors.” In this case, the option
of these children was not between working or not, but between living or starving.
Despite this “surviving question”, usually others factors are indicated as responsible
for childr labour: the unemployment of members in the household, the rupture of
Okurut, F.N. & D.O. Yinusa
10. BOJE: Botswana Journal of Economics
24
the family core, with the woman becoming head in the absence of the man, and the
invalidity of the household head.
Grootaert (1998) examined the determinants of child labour in Côte d’Ivoire
using a sequential probit model. The author identified five key factors which
affect the household’s decision to supply child labour: the age and the gender of
the child, the education and employment status of the parents, the availability of
within-household employment opportunities, the household’s poverty status and its
geographic location. Similarly, it was found that Parent’s characteristics, especially
education, matter the most at the decision stages involving schooling options. Parents
with no or low education are more likely to choose work options for their children.
This effect was found to be most pronounced in rural areas and for younger children,
and underlines lack of schooling and child labour. The paper concluded by offering a
number of policy measures to address the problem of child labour in Côte d’Ivoire
Chaudhri, Nagar, Rahman and Wilson (1999) conducted a preliminary search
for the factors which affect demand and supply of child labour in India using OLS
technique to estimate both cross sectional and time series data between 1961 and
1991. It was found that child labour is strongly associated with the incidence of
poverty, female participation in labour force, and Non-participation in the school
system. Kambhampati and Rajan (2004) study the determinants of child work and
schooling in rural India using a bivariate probit analysis. They conclude that mother’s
education, rather than employment or wages, is the single most important factor in
reducing a child’s work likelihood. Using data on urban Turkey, Dayioglu and Assad
(2002) also support this finding.
Khanam (2004) analysed the incidence and determinants of child labour and
school attendance in Bangladesh using a multinomial logit model which allows a
joint estimation of the determinants of schooling and working, combining schooling
and work, or doing nothing for 5-17 year old children. The empirical findings from
the article provide evidence that the education of parents significantly increases the
probability that a school-age child will specialise in study. It was also showed that
children whose fathers are employed in a vulnerable occupation are more likely to
work full time or combine work with schooling. Most of the literature on child labour
in developing countries finds that boys are more likely to combine study and work.
However, Khanam (2004) suggests that girls are more likely than boys to combine
schooling with work in Bangladesh.
Although Barros, Mendonça and Velazco (1994) concluded that poverty is
not responsible for the entry of children into the Brazilian labour market, Barros and
Santos (1991) found that the participation rate of children in the Brazilian labour
market is directly and strongly related with the household poverty level. If poverty
was the main cause of child labour, then a larger participation rate should be expected
in areas and periods of bigger poverty. Several demographic and economic features
of the household as a unit affect the supply of child labour. On the demographic
11. 25
side, household size and composition are of foremost importance. Ceteris paribus,
the more children there are in the household, the more likely it is that one of them
will work. The literature has clearly established that larger household size reduces
children’s educational participation and reduces parental investment in schooling
(Lloyd, 1994). A larger household size decreases income per capita and increases the
dependency ratio, and both factors increase the likelihood that a child will need to
generate income as opportunity cost of school attendance.
Recently, Leme and Wajnman (2000) studied the link between school and
work and confirmed that in the decision of just studying, the most important variables
are parents’ education and household income, followed by the number of kids in the
family and the child’s gender. Grootaert and Kanbur (1995) discussed the role of
fertility behavior, the household’s risk management, and government policies with
respect to social expenditure and population control as variables which affect the
supply of child labour. On the demand side, the structure of the labour market and the
prevailing production technology are the two main determinants of child labour. To
these economic variables must be added the legislative framework (nationally and
internationally), which usually involves a ban on child labour that is rarely enforced
effectively, and social factors such as advocacy, awareness raising and community-
based efforts to help child workers and street children.As a final factor, war and civic
strife often draw children into militia.
From the above, it is clear that a number of empirical studies of child labour
have been conducted in recent years. However, as Basu (1999) points out, there
remains considerable scope for good empirical work in this field. At this stage,
patterns are only just beginning to emerge among the variety of results in the
literature, corresponding to the vast variety of regions, types of child work, and
empirical specifications. Indeed, existing beliefs about the causes and consequences
of child labour have tended to be shaped by case studies. These typically interview
working children with the attendant problem of selection bias. A feasible solution
to this problem is the use of large scale representative household surveys as is done
in this study. An advantage of using large scale representative household surveys is
that we have comparable information for children who work and those who do not
work.
Another departure of this study from its predecessors lies in the use of a
multinomial logit estimation strategy that simultaneously analyses child employment
and child schooling. Nearly all the previous attempts (see, for example, Patrinos
and Psacharopoulos (1997), Psacharapoulos (1997), Jensen and Nielsen (1997),
Ray (2000)) have used a single equation based standard binomial logit model to
analyse child labour and child schooling participation. The binomial logit estimation
strategy recognizes only two possibilities in a single estimation, namely, in case of
child labour, the child either works or does not and, in case of schooling, either the
child attends schooling or does not. In reality, however, there are simultaneously
Okurut, F.N. & D.O. Yinusa
12. BOJE: Botswana Journal of Economics
26
four possibilities to choose from: child (a) works and attends school, (b) works
but does not attend school, (c) attends school but does not work, and (d) neither
works nor attends school. While in Botswana a sizeable proportion of children are in
category (a), a large number of children are frequently found in other categories. The
multinomial logit estimation strategy adopted in this study, besides incorporating
the simultaneity of decisions on child employment and child schooling, recognises
these four mutually exclusive and exhaustive possibilities in identifying the key
determinants of child labour.
4. Methodology of the Study
4.1 Model specification
The first major step to understanding the child labour market in Botswana concerns
the factors influencing an individual’s employment and schooling choice. We
endeavour to give insights into the factors influencing the selection into any of the
four child employment and schooling states. The child employment and schooling
states include child working and schooling; child working and not schooling; child
not working and schooling; child not working and not schooling.
We assume individuals are allocated by some data generating process into 4
mutually exclusive employment and schooling states.The equation for the underlying
latent variable is given as in Eq. (1).
* /
............................................(1)
is i is
P Z β ε
= +
where *
is
P is a latent variable representing the th
i individual utility gain from
choosing the th
s employment and schooling choice (s= child working and schooling;
child working and not schooling; child not working and schooling; child not working
and not schooling, indexed s=1,2,3,4). The error term is assumed to be normally
distributed with mean zero and unity variance. The Z vector contains exogenous
factors including individual characteristics such as age, sex, education; household
characteristics such as gender of the household head, education of household head,
household size, and employment status of household head. The individual chooses
an employment and schooling state for which utility is highest.
The probability of choosing the th
s employment state conditional of Z vector
takes the multinomial logit form as expressed in Equation (2). For identification, t
0
β
are normalised to zero, that is, we make not working the base employment state.
'
4
'
1
exp( )
exp( )
( / ) .........................................(2)
it st
s
it st
s
Z
t
Z
P s Z
β
β
=
=
=
∑
13. 4.2 Description of the model variables
Individual demographic characteristics: These include age, sex, education, orphan
status and citizenship. Information on education is collected on the highest grade
attained at the time of the survey. This variable was converted into years of schooling.
Sex of the children is included in the model in dummy form with male as the base
category. The survey collected data on employment for persons aged 7 years and
above and as per the Botswana constitution a child is any person below the age
of 18. For this study child employment was defined as those aged between 7 and
17 completed years. The orphan status was created as a categorical variable (1 =
both parents alive; 2 = one parent alive; 3 = all parents dead). Separate dummies
were created for each of the categories, with both parents dead being the reference
category.
Household characteristics: The household characteristics include education level
of household head, gender of household head, employment status of the household
head, and household size. The education level of the household head was entered as
dummy variables for each of the categories (no formal education, primary education,
junior community secondary education, secondary education, and tertiary education).
The last category included all those individuals who have gone beyond secondary
level education including university graduates and above. No formal education is
used as the base category. For the employment status of the household head, four
employment categories were identified using separate dummies: self employment,
paid employment in the public sector, paid employment in the private sector, and
unpaid labour (reference category). The gender of the household head was entered
as a dummy with male being the base category. The number of children in household
was generated by summing all household members aged less than 18 years.
4.3 Data Sources
The study used Labour Force Survey (LFS) 2005/06 data collected by Central
Statistics Office (CSO) using the two-stage sampling design based on the 2001
Population and Housing Census. In the first stage, the Enumeration Areas (EAs)
were sampled from the total 4,143 EAs delineated in the 2001 Population and
Housing Census with probability proportional to measures of size. The second stage
involved the sampling of households from the sampled EAs. Based on the two stage
sampling method, CSO then computed appropriate weights to make the data to be
representative at the national level.
5. Multinomial Regression Results
The results for the multinomial regression results for the determinants child labour
and employment choice in Botswana are presented in table 5.
Okurut, F.N. & D.O. Yinusa 27
14. Explanatory
Variables
Working and
schooling
Working and not schooling
Not Working and
schooling
Coefficient
z
P>z
Coefficient
z
P>z
Coefficient
z
P>z
Dummy for
female child
(1=female)
-1.223 -16.7 0.0000 -0.843 -8.5 0.0000 -0.542 -7.7 0.0000
Dummy for
female headed
household
(1=female)
-0.514 -6.8 0.0000 0.234 2.2 0.0250 -0.120 -1.7 0.0970
Dummy for
both parent alive
(1=both parents
alive)
0.774 7.4 0.0000 0.270 2.1 0.0350 0.802 8.4 0.0000
Dummy for
single parent
(1=single parent
alive)
1.206 10.1 0.0000 -1.768 -9.0 0.0000 0.903 8.0 0.0000
Education level
of child, in years
of schooling
-0.023 -2.3 0.0240 0.034 2.3 0.0220 -0.196 -20.1 0.0000
Dummy
for primary
education level
of household
head (=1 if
primary)
-0.826 -3.3 0.0010 1.958 8.0 0.0000 -3.029 -12.7 0.0000
Dummy for
junior secondary
education level
of household
head (=1
if junior
secondary)
0.050 0.2 0.8410 1.934 7.1 0.0000 -0.703 -2.9 0.0040
Dummy for
senior secondary
education level
of household
head (=1
if senior
secondary)
-0.189 -1.1 0.2920 1.794 7.2 0.0000 -0.620 -3.6 0.0000
Household size 0.143 3.9 0.0000 -0.407 -8.5 0.0000 0.002 0.1 0.9640
Household size
squared
-0.023 -10.2 0.0000 0.021 7.1 0.0000 -0.013 -6.3 0.0000
Number of
children in
household
0.373 13.2 0.0000 -0.249 -5.7 0.0000 0.292 11.0 0.0000
Constant 1.463 5.3 0.0000 -16.262 1.3 0.2935 4.544 17.4 0.0000
(Outcome Not working and not
schooling is the comparison
group)
BOJE: Botswana Journal of Economics
28
15. Number of obs =
37,623
LR chi2(33) = 8074.21
Prob > chi2 = 0.0000
Pseudo R2 = 0.1318
The dependent variable was a categorical variable which captured the selection of
the individual into any of the four child labour and schooling states, with those not
working and not schooling being the base category. The results suggest that the
model is good with estimated parameters being jointly significantly different from
zero (Prob>chi2 = 0.0000). The significance of each of the parameter estimates is
tested at least at the 10 percent significance level, with the focus being on the P>Z
statistic. If this statistic is less than 0.1, then the parameter estimate is significantly
different from zero at 10 per cent level holding other variables constant.
Relative to the reference category, the probability of children both working and
schooling is negatively and significantly influenced by the gender of the child being
female, being from a female headed household, education level of child, education
level of the household head and household size. By implication children from female
headed households are less likely to engage in child employment while at the same
time schooling as compared to children from male headed households. One possible
explanation to this scenario is that the women value the education of children more
than the males which may be explained by the historical background of the Batswana
(Chernichovsky, 1985). The men used to work in the mines in South Africa leaving
the care of households under the women. While the girls were mainly at school (with
the exception of those that dropped out due to pregnancy or early marriage), the boys
were mainly engaged in cattle posts and this partly explains why women on average
have higher levels of education than the men, hence were more likely to value the
education of children than the men.
The higher the education level of the child, the lower will be the probability
of engagement in child labour and schooling. The intuition of this result may be that
children who have attained a relatively higher level of education are more likely to
have a better understanding of the potential benefits from education and therefore
less likely to engage both in labour market activities and schooling.
Primary education level of the household head has a negative and significant
effect on the probability of child engagement in labour market activities and
schooling. By implication household heads with some education level appreciate
the value of children mainly concentrating on their schooling, hence minimize child
involvement in labour market activities as well. What was puzzling though was the
statistically insignificant effect of higher education levels of household heads.
The variables that captured the employment status of the householdheads (that
is paid employment in either the private or public sectors and self-employment)
were insignificant and therefore dropped from the model. However this was strange
because empirical literature argues that employment generates income to the
Okurut, F.N. & D.O. Yinusa 29
16. household which diminishes the need to engage children in labour market activities
to supplement family earnings, which creates a conducive environment to keep
children in school. Psacharopoulos and Arriagada (1987) in their study in Brazil also
observed that parents’ employment status had a positive and significant effect on the
probability of children being enrolled in school.
The probability of child labour and schooling was positively and significantly
influencedbyhouseholdsize,thenumberofchildreninthehousehold,childrenhaving
both parent alive, and children being from single parent households. The positive
and significant effect of the number of children in the household on the probability
of children being engaged in child labour and schooling may be explained by the
poverty status of the household. Empirical literature argues that poor households
tend to have high numbers of children and as such children are forced to engage in
child labour to supplement family earnings (Psacharopoulos and Arriagada, 1987).
In addition as the number of children increases, per capita schooling resources for
each child decreases, hence forcing the children to participate in the labour market.
Relative to children who are orphans, those with both parents alive or one
parent alive are more likely to be engaged in the labour market as well as schooling
which is quite surprising. In seminar presentation of the preliminary results of this
work, the participants raised that the very serious problem in Botswana is in the
parents living together but not so much whether the parents are alive or not.According
to them, you find several cases where the husband and the wife are living separately
and children in most cases are left under the care of mothers which have serious
implications for children’s schooling and labour market participation. However the
available labour force survey data 2005/06 did not capture this variable of parents
living together and so could not be factored into the analysis.
6. Summary of Results and Policy Implications
Botswana policy on child labour is very clear: no child should be employed
whatsoever while still at school and below the age of 14 (Republic of Botswana,
2002). Heavy penalties were prescribed for offences related to employment of
children ranging from fine of P1,500 to 12 month imprisonments or both. However,
it is the current reality in the country that children are engaged in child labour as
well as schooling. This raised fundamental policy issues in the country. The main
driver of child labour in the Botswana is socioeconomic characteristic of households
where these children come from, in particular poverty status of these households.
These socioeconomic factors may point to increasing levels of poverty or increasing
inequality in income distribution. This is consistent with the Household Income and
Expenditure Survey of 2002/2003 which observes that the Gini income inequality
coefficient rose from 0.537 in 1993/94 to 0.573 in 2002/03 (CSO, 2004). Also, our
results show that children are mainly engaged in work to assist parents or to get
money to support themselves which may be a reflection of inadequate resources
BOJE: Botswana Journal of Economics
30
17. from parents to support the children. The policy implication is that reduction of child
labour market participation depends strongly on economic growth and development,
particularly the reduction of poverty and income inequality.
References
Austen, S. (2005) “The Determinants of Labour Force Participation for Older
Australian Women: A Statistical Analysis of the Negotiating the Life Course
Survey Data” Women in Social & Economic Research Working Paper No 46,
http://www.cbs.curtin.edu.au/wiser (September)
BARROS, Ricardo & SANTOS, (1991) Eleonora. Consequências de Longo Prazo
do Trabalho Precoce. IPEA – Relatório Interno no 6. Rio de Janeiro, july.
BARROS, Ricardo., MENDONÇA, Rosane. & VELAZCO, (1994) Tatiana. Is
Poverty the Main Cause of Child Work in Urban Brazil?. IPEA – Texto para
Discussão no 351. Rio de Janeiro, oct.
Basu, Kaushik (1999) Child Labor: Cause, Consequence, and Cure, with Remarks
on International Labor Standards, Journal of Economic Literature, Vol. 37, no
3, September.
Basu, Kaushik and Ray Rajan (2002) The Collective Model of the Household and
an Unexpected Implication of Child Labor. The World Bank’s Policy Research
Working Paper 2813.
Bhalotra, S. and C. Heady, (2001), “Child Activities in South Asia and Sub-Saharan
Africa: A Comparative Analysis”, Published in P. Lawrence and C. Thirtle,
eds., Africa and Asia in Comparative Development, (London: Macmillan),
(September)
Bhalotra, Sonia and Heady Christopher (2003) Child Farm Labour: The Wealth
Paradox. Discussion Paper No 03/533, Department of Economics, University
of Bristol.
BockJ.(2002),“Evolutionarydemographyandintrahouseholdtimeallocation:school
attendance and child labor among the Okavango Delta Peoples of Botswana”,
American Journal of Human Biology, 14(2):206-21. (March-April).
Brown, D. K.,Alan V. Deardorff and R. M. Stern, (2002), “The Determinants of Child
Labour: Theory and Evidence” Research Seminar in International Economics,
School of Public Policy, The University of Michigan, Discussion Paper No. 486
(Michigan)
Chaudhri, D.P., A.L. Nagar, T. Rahman and E.J. Wilson (1999) (Determinants of
Child Labour in Indian States: Some Empirical Explorations (1961-1991)”
Working Paper 99-9, Department of Economics, University of Wollongong.
Okurut, F.N. & D.O. Yinusa 31
18. Chernichovsky, D. (1985). Socioeconomic and Demographic Aspects of School
Enrollment and Attendance in Rural Botswana. Economic Development and
Cultural Change 32(1), 319-332.
Dayioglu, Meltem and Assa, Ragui (2002) The Determinants of Child Labour in
Urba Turkey. ERF Working Paper Series No. 0302.
de Carvalho Filho, I.E. (2008), “Household IncomeAsADeterminant of Child Labor
and School Enrollment in Brazil: Evidence From A Social Security Reform”
IMF Working Paper, IMF, Washington, D.C. USA.
Edmonds, Eric V. (2006), “A Review of Alessandro Cigno and Furio Rosati’s The
Economics of Child Labour” (Oxford University Press, 2005), The Journal of
Economic Literature, (December).
Emerson, Patrick and Souza Andre (2005) Bargaining Over Sons and Daughters:
Child Labor, School Attendance and Intra-household Gender Bias in Brazil.
Working Paper series No. 0213, Vanderbilt University.
Grootaert, C. and Patrinos, H. A. (Eds.). (1999) The policy analysis of child labor: A
comparative study. New York, NY: St Martin’s Press.
Grootaert, C. and R. Kanbur (1995). “Child Labor: A Review”, Policy Research
Working Paper No. 1454, Washington, DC: The World Bank.
Grootaert, Christiaan (1998), Child Labor in Côte d’Ivoire: Incidence and
Determinants”, Social Development Department, World Bank, Washington,
D.C.
ILO (1996), Child Labour: Targetting the Intolerable, ILO, Geneva.
ILO (2006), The end of child labor: Within reach. ILO, Geneva.
Jensen, P. and H. S. Nielsen. (1997). “Child Labor or School Attendance? Evidence
from Zambia”, Journal of Population Economics, Vol. 10.
Kambhampati, Uma and Rajan, Raji. (2004) Does ChildWork Decrease with Parental
Income? The Luxury Axiom Revisited in India. mimeo: University of Reading
Khanam, R. (2004), “Child Labour in Bangladesh: Determinants and Effects” http://
mpra.ub.uni-muenchen.de/6990/2/Final_Manuscript_IJSE_.pdf
LEME, Maria Carolina, WAJNMAN, Simone.Aalocação do tempo dos adolescentes
brasileiros entre o trabalho e a escola. In: XII Encontro Nacional de Estudos
Populacionais, Anais, ABEP, Caxambú, 2000 (Available in CD-ROM).
Lloyd, C. B. (1994). “Investing in the Next Generation: The Implications of High
Fertility at the Level of the Family.” New York Population Council, Research
Division Working Paper No. 63.
Muniz, J. O. (2001), “An Empirical Approach for Child Labour in Brazil”, A text
BOJE: Botswana Journal of Economics
32
19. of the paper presented at the IUSSP XXIV General Population Conference,
Salvador, Brazil (August).
Patrinos, H.A. and G. Psacharopoulos (1997), “Family Size, Schooling and Child
Labor in Peru – An Empirical Analysis.” Journal of Population Economics,
vol. 10, no. 4, pp. 387-405.
Psacharopoulos, G. (1997), “Child Labor versus Educational Attainment: Some
Evidence from Latin America.” Journal of Population Economics, vol. 10, no.
4, pp. 377-386.
Psacharopoulos, G. and Arriagada, A.M. (1987), “School Participation, Grade
Attainment and Literacy in Brazil: A 1980 Census Analysis”, Discussion
Paper No. EDT86, http://siteresources.worldbank.org/BRAZILINPOREXTN/
Resources/3817166--1185895645304/4044168--1186326902607/38pub_br59.
pdf
Ray, R. (2000) Analysis of Child Labour in Peru and Pakistan: A Comparative
Study. Journal of Population Economics, Vol. 13, No 1, pp. 3-19.
UNICEF, (2007), “Child Labour, Education and Policy Options” Division of Policy
and Planning, Working Papers, NY, USA.
ZYLBERSTAJN, Hélio., et al. (1985) A mulher e o menor na força de trabalho. São
Paulo: Nobel, 1985.
Okurut, F.N. & D.O. Yinusa 33