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The Impact of Female Education, Trade Openness, Per Capita GDP, and Urbanization on Women’s Employment in South Asia: Application of CS-ARDL Model
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The Impact of Female Education, Trade Openness, Per Capita GDP, and Urbanization on Women’s Employment in South Asia: Application of CS-ARDL Model
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Journal Article
The Impact of Female Education, Trade Openness, Per Capita GDP, and Urbanization on Women’s Employment in South Asia: Application of CS-ARDL Model
2023
Overview
This study examines the impact of female education and other control variables such as trade openness, per capita GDP, urbanization, and male employment on women’s employment opportunities in South Asian countries. The annual data from 1990 to 2020 were evaluated. After determining the existence of slope heterogeneity, cross-sectional dependence, and mixed order stationary in the panel data, the paper applied the Cross-Sectional Autoregressive Distributive Lag (CS-ARDL) model to estimate long and short-run impacts. At the same time, AMG, MG, and CCEMG models have been utilized for checking robustness and validating the findings. According to CS-ARDL findings, female education and trade openness have a significant positive impact on female employment in the short and long term. In contrast, GDP per capita and urbanization are diminishing female employment in the targeted countries in the long run. The AMG, MG, and CCEMG results support the CS-ARDL findings. This shows that these governments should incorporate trade and education for women into their labor strategies. The key contribution of this study is in the field of labor market opportunity for female employment and shows the relative importance of education in determining female employment in South Asia.
