Human Capital Development and Migration Patterns in Nigeria: A Ridge and Lasso Regression Analysis Using Python

This study investigates the relationship between human capital development and migration patterns in Nigeria from 1981 to 2021 using Ridge and Lasso regression techniques implemented in Python. Human capital development is proxied by government expenditure on education, health, social services, and gross fixed capital formation, while net migration serves as the dependent variable. The results indicate that human capital development positively influences net migration, suggesting a higher emigration rate relative to immigration. This highlights the paradox of brain drain, where increased investment in education and health enhances skill acquisition but simultaneously encourages outward migration due to limited domestic opportunities. The Ridge regression model, preferred over Lasso due to its robustness against multicollinearity, demonstrates a strong explanatory power with an R-squared value of 0.99. Policy recommendations emphasize the need for strategic interventions, including competitive wages, job creation, and entrepreneurship incentives, to retain skilled labor and mitigate the negative effects of migration. Additionally, fostering foreign direct investment and improving domestic economic conditions can enhance productivity and optimize the benefits of human capital development for national growth.