The Determinants of Child Labor in MINT Countries: Dynamic Panel Data Analysis

Süreyya İmre ()
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Süreyya İmre: Istanbul Gelisim University, Faculty of Economic Administrative and Social Sciences, Management Information Systems, Istanbul, Turkey

EKOIST Journal of Econometrics and Statistics, 2021, vol. 0, issue 34, 57-72

Abstract: There are many studies in the literature on child labor. However, most of these studies are based on statistics on children, or the factors that cause child labor are explained as economic concepts. The purpose of this study is to investigate the reasons why school-age children adopt the role of "child laborer" and determine the effects of these factors. In this context, in order to examine the factors affecting child labor in developing countries, this study has tried to determine the factors causing child labor with dynamic panel data analysis using MINT Countries data for the period of 1990-2018. The countries’ development levels and poverty are closely related to child labor. For this reason, the human development index is added to the model as a dependent variable. Considering the studies in the literature, population growth, primary school enrollment rate, primary school duration, and labor force participation rate variables were added to the model as independent variables. At the end of the analysis, all variables were found to be statistically significant. The effect of population growth and the number of primary school students on the human development index was negative, while the effect of other variables was positive.

Keywords: Dynamic panel data models; MINT Countries; Child labor (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ist:ekoist:v:0:y:2021:i:34:p:57-72

DOI: 10.26650/ekoist.2021.34.912176

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