Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021
In Tanzania, millions of children continue to engage in hazardous, exploitative jobs, making it difficult for them to receive an education and enjoy a safe upbringing. This study aims to identify the major variables that affect child labor in Tanzania using data from the Integrated Labour Force Surv...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Cogent Social Sciences |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/23311886.2025.2492841 |
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| author | Hebron A. Mtafya Srinivasa Rao Gadde Jairos K. Shinzeh |
| author_facet | Hebron A. Mtafya Srinivasa Rao Gadde Jairos K. Shinzeh |
| author_sort | Hebron A. Mtafya |
| collection | DOAJ |
| description | In Tanzania, millions of children continue to engage in hazardous, exploitative jobs, making it difficult for them to receive an education and enjoy a safe upbringing. This study aims to identify the major variables that affect child labor in Tanzania using data from the Integrated Labour Force Survey 2020/2021. Unweighted binary generalized estimating equation models are used in the study to evaluate the individual, family, and social factors that influence the participation of children in labor. The results show that key influences on child labor in Tanzania include household head education, head of household marital status, family size, location, child age, and household with an employed member. For stakeholders and policymakers creating focused programs and policies to prevent child labor and enhance children’s rights to education and a brighter future, the results provide important information. By being able to account for within-cluster correlations and generate population average values, this model’s use is justified and makes it possible to fully analyze the variables impacting child labor. By comprehending the root causes of child labor, Tanzania may develop evidence-based policies and programs that prioritize children’s health, education, and safety from dangerous jobs. Tanzania would be able to break the cycle of exploitation and poverty that encourages child labor. |
| format | Article |
| id | doaj-art-08fe2fd8849b4210b76e6df148c4f484 |
| institution | OA Journals |
| issn | 2331-1886 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Social Sciences |
| spelling | doaj-art-08fe2fd8849b4210b76e6df148c4f4842025-08-20T02:17:28ZengTaylor & Francis GroupCogent Social Sciences2331-18862025-12-0111110.1080/23311886.2025.2492841Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021Hebron A. Mtafya0Srinivasa Rao Gadde1Jairos K. Shinzeh2Department of Mathematics and Statistics, The University of Dodoma, TanzaniaDepartment of Mathematics and Statistics, The University of Dodoma, TanzaniaDepartment of Mathematics and Statistics, The University of Dodoma, TanzaniaIn Tanzania, millions of children continue to engage in hazardous, exploitative jobs, making it difficult for them to receive an education and enjoy a safe upbringing. This study aims to identify the major variables that affect child labor in Tanzania using data from the Integrated Labour Force Survey 2020/2021. Unweighted binary generalized estimating equation models are used in the study to evaluate the individual, family, and social factors that influence the participation of children in labor. The results show that key influences on child labor in Tanzania include household head education, head of household marital status, family size, location, child age, and household with an employed member. For stakeholders and policymakers creating focused programs and policies to prevent child labor and enhance children’s rights to education and a brighter future, the results provide important information. By being able to account for within-cluster correlations and generate population average values, this model’s use is justified and makes it possible to fully analyze the variables impacting child labor. By comprehending the root causes of child labor, Tanzania may develop evidence-based policies and programs that prioritize children’s health, education, and safety from dangerous jobs. Tanzania would be able to break the cycle of exploitation and poverty that encourages child labor.https://www.tandfonline.com/doi/10.1080/23311886.2025.2492841Child laborunweighted binary generalized estimationforbidden workhousehold headsocial-economic characteristicsStatistics for Social Sciences |
| spellingShingle | Hebron A. Mtafya Srinivasa Rao Gadde Jairos K. Shinzeh Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021 Cogent Social Sciences Child labor unweighted binary generalized estimation forbidden work household head social-economic characteristics Statistics for Social Sciences |
| title | Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021 |
| title_full | Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021 |
| title_fullStr | Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021 |
| title_full_unstemmed | Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021 |
| title_short | Determinants of child labor in Tanzania: a BGEE model analysis of the ILFS 2020/2021 |
| title_sort | determinants of child labor in tanzania a bgee model analysis of the ilfs 2020 2021 |
| topic | Child labor unweighted binary generalized estimation forbidden work household head social-economic characteristics Statistics for Social Sciences |
| url | https://www.tandfonline.com/doi/10.1080/23311886.2025.2492841 |
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