Factors Determining Child Labor: Empirical Evidence from Khyber Pakhtunkhwa, Pakistan


Children are forced to work when their families face financial pressures due to poverty, illness, or the loss of jobs. There is, however, still a perceived lack of research on the key factors contributing to child labor in Pakistan. This study examines the determinants of child labor in Mardan and Nowshera districts of Khyber Pakhtunkhwa, a province of Pakistan. A total of 200 households were interviewed. A semi-structured questionnaire was developed to collect data from the family heads whose children are in child labor. A stepwise-regression model was adopted to explore the strength of the relationship between independent variables and dependent variable. The dependent variable was the child labor ratio and the independent variables were the socio-economic and demographic’ characteristics such as age, education, family size, parents’ occupation, the number of adult males and females, family income. The findings show that the family size was the most important determinant of child labor. Likewise, the number of adult females, parents’ occupation as daily wages labor, and the parents’ age had a positive influence on the extent of child labor. However, the number of adult males, family income, and parents’ education had a negative relationship with the extent of child labor. The questionnaire survey had shown that families considered poverty to be the main reason behind child labor, unemployment was the second reason and the third was number of dependent females within the families. Therefore, the government may target these families from lower socio-economic backgrounds to disseminate information about family planning and also include these people in the current governmental program to help them financially.

Author Biographies

Sikandar Sikandar, Abdul Wali Khan University, Mardan, Pakistan

Sikandar is presently working at the Directorate of Admissions at Abdul Wali Khan University, Mardan, Pakistan. His areas of research include agricultural finance, development studies, climate change, and disaster risk reduction.

Sanaullah Panezai, University of Balochistan Quetta, Pakistan

Sanaullah Panezai is an Assistant Professor at the University of Balochistan Quetta, Pakistan, and the Editor-in-Chief of the Journal of Geography and Social Sciences. His areas of research include primary healthcare, climate change, and poverty.

Shahab E. Saqib, The Higher Education Department, Khyber Pakhtunkhwa, Pakistan

Dr. Shahab E. Saqib has completed his Master & PhD from Asian Institute of Technology, Thailand, in the field of Regional and Rural Development Planning with excellent thesis grades. His areas of specialization are environmental economics, climate change, food security, and health economics. Today, he is working as an Assistant Professor in the field of commerce education and management sciences, the Higher Education Department, Khyber Pakhtunkhwa, Pakistan.

Said Muhammad, Zhengzhou University, China; The Higher Education Department, Khyber Pakhtunkhwa, Pakistan

Said Muhammad is a PhD candidate at Zhengzhou University, China. He is also working as a Lecturer (Commerce) in the field of commerce education and management sciences, the Higher Education Department, Khyber Pakhtunkhwa, Pakistan. His areas of research include climate finance, entrepreneurship, and poverty.

Bilal Bilal, Abdul Wali Khan University, Mardan, Pakistan

Bilal is a Master of Economics candidate at Abdul Wali Khan University, Mardan, Pakistan. His main research interests cover development studies in risk management.

Imran Khan, Abdul Wali Khan University, Mardan, Pakistan

Imran Khan is a Master candidate, Financial Aid Office at Abdul Wali Khan University, Mardan, Pakistan. He has been conducting research in the area of climate change and its implications.


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How to Cite
Sikandar, S., Panezai, S., Saqib, S., Muhammad, S., Bilal, B., & Khan, I. (2022). Factors Determining Child Labor: Empirical Evidence from Khyber Pakhtunkhwa, Pakistan. Changing Societies & Personalities, 6(1), 123–143. doi:10.15826/csp.2022.6.1.166