Exploring Migration Determinants: a Meta-Analysis of Migration Drivers and Estimates

Abstract

Abstract This comprehensive study delves into over 100 empirical articles, examining the influence of structural drivers on both internal and international migration. Employing a meta-analysis approach, we dissect these studies to pinpoint the prevalent migration drivers frequently subjected to quantitative scrutiny. Our investigation extends to scrutinizing major migration drivers in terms of their statistical impact, directional tendencies, and statistical significance. Our findings underscore that indicators such as income or GDP, education, migrant networks, gender, age, and family characteristics are the most commonly scrutinized factors shaping migration patterns. Notably, geographical distance, gender, and migrant networks emerge as highly consistent drivers, exhibiting a remarkable uniformity in both effect direction and statistical significance across the most frequently studied factors. Numerous migration drivers exhibit statistical significance roughly around 50% of the time, while several others fall considerably below this threshold. Intriguingly, we delve into the complex variations characterizing the impact of destination country GDP per capita. Our exploration reveals that articles reporting a negative effect for destination country GDP per capita are more likely to focus on irregular or asylum migration flows. However, an intriguing subset of articles that also explore asylum migration flows finds a positive effect. These nuanced disparities are further influenced by variations in sample composition, control variables, statistical models, and the operationalization of GDP per capita. In sum, our in-depth analysis sheds light on the multifaceted landscape of migration drivers, offering critical insights into both the consensus and divergence within migration research.