Child Labor in Sindh, Pakistan: Patterns and Areas in Need of Intervention

Nadia Maqbool (), Paul Newton and Tayyab Shah ()
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Nadia Maqbool: Department of Educational Administration, College of Education, University of Saskatchewan, Saskatoon, SK S7N 0X1, Canada
Paul Newton: Department of Educational Administration, College of Education, University of Saskatchewan, Saskatoon, SK S7N 0X1, Canada
Tayyab Shah: CHASR, University of Saskatchewan, Saskatoon, SKS7N 5A4, Canada

Stats, 2024, vol. 7, issue 4, 1-17

Abstract: Child labor remains a predominant issue in Pakistan despite the country’s existing policies and frameworks aimed at abolishing it. Through this study, we investigated the child labor distribution across Sindh and examined the factors that shape the regional patterns. We analyzed the data available through the 2018–19 Sindh Multiple Indicator Cluster Surveys, MICS 6, from 20,030 households with 40,633 children in the 5–17 age bracket. By applying prevalence statistics, chi-square tests, and regression modeling to these data, we investigated the trends in child labor prevalence, identified the correlation between child labor and various socioeconomic and geodemographic variables, and finally mapped the geospatial patterns of child labor across districts in Sindh, enabling us to identify and prioritize the districts in need of immediate intervention. The findings revealed that about 20 percent of the children in Sindh are engaged in child labor, with a high prevalence among males and in the 15–17 age bracket. Moreover, poverty and rural dwellings raise this issue. Other socioeconomic and geographic factors reinforcing this issue are a lack of education among children, mothers, or caretakers and mothers’ or caretakers’ functional difficulties. However, children’s functional difficulties lower their prevalence in labor. Among the 29 districts across Sindh, Kambar Shahdadkot has the highest prevalence of child labor.

Keywords: child labor; logistic regression; geospatial mapping; MICS; spatial patterns; Sindh; Pakistan (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2024
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