Abstract
This paper aims to investigate the long-run and short-run dynamics of important determinants
of child labor at macroeconomic level in the case of Pakistan. The import distinction of this
paper is that it is the first attempt to investigate the long-run and short-impacts of determinants
of child labor by using time series estimation technique of Autoregressive Distributive Lags
Model (ARDL). The long-run findingssuggest that an increase in GDPper capita and gross primary school enrollment leads toward the reduction of incidence of child labor. Despite the fact
that engagement of children in any kind of economic activitiesislegally banned but due to lack
of enforcement of laws and poor institutional support child labor is common in Pakistan. Similarly, an improvement in the quality of existing institutions can potentially contribute in the reduction of child labor. However, the positive and significant sign of the coefficient of young
dependency (YD)suggeststhat higher dependency of young children isincreasing the incidence
of child labor in Pakistan. The overall findings suggest that in short-run the determinants, such
as GDP, School enrolment, dependency, and institutional quality have similar impact on child
labor, the impact of growth in per capita income is apparent in the reduction of child labor. The
findings of this paper is suggesting that merely economic growth is not sufficient enough to reduce the extent of child labor in Pakistan, we have to align such efforts with policies aiming to
achieve demographic and gender empowerment.
Usman AZHAR, Samina KHALIL. (2020) A DYNAMIC STUDY OF CHILD LABOR MARKET AND ITS DETERMINANTS IN PAKISTAN: A Time Series Analysis, Pakistan Journal of Applied Economics, Volume 30, Issue 1.
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