Understanding the Dynamics of Brain Drain from Afghanistan: Interplay of Education and Emigration Decision
DOI:
https://doi.org/10.59670/ml.v20i7.4865Abstract
This study investigates the impact of factors influencing the emigration decision of educated Afghans in Afghanistan from 2016 to 2021. The article explores the interplay between understanding the dynamics of brain drain from Afghanistan and utilizing marketing engineering as a progressive platform to optimize managerial decision-making processes in the context of the country's evolving challenges. It delves into how the emigration decisions of educated individuals affect the nation and how harnessing their skills and knowledge through brain gain can benefit marketing management strategies. This interdisciplinary approach seeks to leverage Afghanistan's diaspora as a valuable resource for addressing contemporary marketing challenges. By employing a binary logistic regression model at margins and binary logistic regression with a pool cross-sectional dataset, significant findings are revealed. The pool logistic regression analysis at its margins confirms a significant positive relationship between education and emigration. It indicates that a one-year increase in education increases the probability of emigration by 0.2%. The findings obtained through logistic regression analysis, employing multi-sampling methods, indicates that emigration decision of individuals holding master degree are significantly influenced by political instability and diaspora abroad, rather than economic factors. Similarly, individuals holding bachelor degree, in addition to political instability and family ties abroad also demonstrate a stronger association with insecurity, and female income as determinants of their emigration decisions. In contrast, other educational categories, such as the uneducated, high school graduates, and vocational school graduates, exhibit a noteworthy correlation with all three factors: social, economic, and demographic, influencing their emigration decision. Findings have policy implications for addressing migration challenges in developing countries.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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